datadog_api_client.v1.model package

Submodules

datadog_api_client.v1.model.access_role module

class AccessRole(arg: None)

class AccessRole(arg: ModelComposed)

class AccessRole(*args, **kwargs)

Bases: ModelSimple

The access role of the user. Options are st (standard user), adm (admin user), or ro (read-only user).

Parameters:

• value (str) – Must be one of [“st”, “adm”, “ro”, “ERROR”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.add_signal_to_incident_request module

class AddSignalToIncidentRequest(arg: None)

class AddSignalToIncidentRequest(arg: ModelComposed)

class AddSignalToIncidentRequest(*args, **kwargs)

Bases: ModelNormal

Attributes describing which incident to add the signal to.

Parameters:

• add_to_signal_timeline (bool, optional) – Whether to post the signal on the incident timeline.

• incident_id (int) – Public ID attribute of the incident to which the signal will be added.

• version (int, optional) – Version of the updated signal. If server side version is higher, update will be rejected.

datadog_api_client.v1.model.agent_check module

class AgentCheck(arg: None)

class AgentCheck(arg: ModelComposed)

class AgentCheck(*args, **kwargs)

Bases: ModelSimple

Array of strings.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.alert_graph_widget_definition module

class AlertGraphWidgetDefinition(arg: None)

class AlertGraphWidgetDefinition(arg: ModelComposed)

class AlertGraphWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Alert graphs are timeseries graphs showing the current status of any monitor defined on your system.

Parameters:

• alert_id (str) – ID of the alert to use in the widget.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – The title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (AlertGraphWidgetDefinitionType) – Type of the alert graph widget.

• viz_type (WidgetVizType) – Whether to display the Alert Graph as a timeseries or a top list.

datadog_api_client.v1.model.alert_graph_widget_definition_type module

class AlertGraphWidgetDefinitionType(arg: None)

class AlertGraphWidgetDefinitionType(arg: ModelComposed)

class AlertGraphWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the alert graph widget.

Parameters:

• value (str) – If omitted defaults to “alert_graph”. Must be one of [“alert_graph”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.alert_value_widget_definition module

class AlertValueWidgetDefinition(arg: None)

class AlertValueWidgetDefinition(arg: ModelComposed)

class AlertValueWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Alert values are query values showing the current value of the metric in any monitor defined on your system.

Parameters:

• alert_id (str) – ID of the alert to use in the widget.

• precision (int, optional) – Number of decimal to show. If not defined, will use the raw value.

• text_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of value in the widget.

• type (AlertValueWidgetDefinitionType) – Type of the alert value widget.

• unit (str, optional) – Unit to display with the value.

datadog_api_client.v1.model.alert_value_widget_definition_type module

class AlertValueWidgetDefinitionType(arg: None)

class AlertValueWidgetDefinitionType(arg: ModelComposed)

class AlertValueWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the alert value widget.

Parameters:

• value (str) – If omitted defaults to “alert_value”. Must be one of [“alert_value”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.api_error_response module

class APIErrorResponse(arg: None)

class APIErrorResponse(arg: ModelComposed)

class APIErrorResponse(*args, **kwargs)

Bases: ModelNormal

Error response object.

Parameters:

errors ([str]) – Array of errors returned by the API.

datadog_api_client.v1.model.api_key module

class ApiKey(arg: None)

class ApiKey(arg: ModelComposed)

class ApiKey(*args, **kwargs)

Bases: ModelNormal

Datadog API key.

Parameters:

• created (str, optional) – Date of creation of the API key.

• created_by (str, optional) – Datadog user handle that created the API key.

• key (str, optional) – API key.

• name (str, optional) – Name of your API key.

datadog_api_client.v1.model.api_key_list_response module

class ApiKeyListResponse(arg: None)

class ApiKeyListResponse(arg: ModelComposed)

class ApiKeyListResponse(*args, **kwargs)

Bases: ModelNormal

List of API and application keys available for a given organization.

Parameters:

api_keys ([ApiKey], optional) – Array of API keys.

datadog_api_client.v1.model.api_key_response module

class ApiKeyResponse(arg: None)

class ApiKeyResponse(arg: ModelComposed)

class ApiKeyResponse(*args, **kwargs)

Bases: ModelNormal

An API key with its associated metadata.

Parameters:

api_key (ApiKey, optional) – Datadog API key.

datadog_api_client.v1.model.apm_stats_query_column_type module

class ApmStatsQueryColumnType(arg: None)

class ApmStatsQueryColumnType(arg: ModelComposed)

class ApmStatsQueryColumnType(*args, **kwargs)

Bases: ModelNormal

Column properties.

Parameters:

• alias (str, optional) – A user-assigned alias for the column.

• cell_display_mode (TableWidgetCellDisplayMode, optional) – Define a display mode for the table cell.

• name (str) – Column name.

• order (WidgetSort, optional) – Widget sorting methods.

datadog_api_client.v1.model.apm_stats_query_definition module

class ApmStatsQueryDefinition(arg: None)

class ApmStatsQueryDefinition(arg: ModelComposed)

class ApmStatsQueryDefinition(*args, **kwargs)

Bases: ModelNormal

The APM stats query for table and distributions widgets.

Parameters:

• columns ([ApmStatsQueryColumnType], optional) – Column properties used by the front end for display.

• env (str) – Environment name.

• name (str) – Operation name associated with service.

• primary_tag (str) – The organization’s host group name and value.

• resource (str, optional) – Resource name.

• row_type (ApmStatsQueryRowType) – The level of detail for the request.

• service (str) – Service name.

datadog_api_client.v1.model.apm_stats_query_row_type module

class ApmStatsQueryRowType(arg: None)

class ApmStatsQueryRowType(arg: ModelComposed)

class ApmStatsQueryRowType(*args, **kwargs)

Bases: ModelSimple

The level of detail for the request.

Parameters:

• value (str) – Must be one of [“service”, “resource”, “span”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.application_key module

class ApplicationKey(arg: None)

class ApplicationKey(arg: ModelComposed)

class ApplicationKey(*args, **kwargs)

Bases: ModelNormal

An application key with its associated metadata.

Parameters:

• hash (str, optional) – Hash of an application key.

• name (str, optional) – Name of an application key.

• owner (str, optional) – Owner of an application key.

datadog_api_client.v1.model.application_key_list_response module

class ApplicationKeyListResponse(arg: None)

class ApplicationKeyListResponse(arg: ModelComposed)

class ApplicationKeyListResponse(*args, **kwargs)

Bases: ModelNormal

An application key response.

Parameters:

application_keys ([ApplicationKey], optional) – Array of application keys.

datadog_api_client.v1.model.application_key_response module

class ApplicationKeyResponse(arg: None)

class ApplicationKeyResponse(arg: ModelComposed)

class ApplicationKeyResponse(*args, **kwargs)

Bases: ModelNormal

An application key response.

Parameters:

application_key (ApplicationKey, optional) – An application key with its associated metadata.

datadog_api_client.v1.model.authentication_validation_response module

class AuthenticationValidationResponse(arg: None)

class AuthenticationValidationResponse(arg: ModelComposed)

class AuthenticationValidationResponse(*args, **kwargs)

Bases: ModelNormal

Represent validation endpoint responses.

Parameters:

valid (bool, optional) – Return true if the authentication response is valid.

datadog_api_client.v1.model.aws_account module

class AWSAccount(arg: None)

class AWSAccount(arg: ModelComposed)

class AWSAccount(*args, **kwargs)

Bases: ModelNormal

Returns the AWS account associated with this integration.

Parameters:

• access_key_id (str, optional) – Your AWS access key ID. Only required if your AWS account is a GovCloud or China account.

• account_id (str, optional) – Your AWS Account ID without dashes.

• account_specific_namespace_rules ({str: (bool,)}, optional) – An object (in the form {"namespace1":true/false, "namespace2":true/false} ) containing user-supplied overrides for AWS namespace metric collection. Important : This field only contains namespaces explicitly configured through API calls, not the comprehensive enabled or disabled status of all namespaces. If a namespace is absent from this field, it uses Datadog’s internal defaults (all namespaces enabled by default, except AWS/SQS , AWS/ElasticMapReduce , and AWS/Usage ). For a complete view of all namespace statuses, use the V2 AWS Integration API instead.

• cspm_resource_collection_enabled (bool, optional) – Whether Datadog collects cloud security posture management resources from your AWS account. This includes additional resources not covered under the general resource_collection.

• excluded_regions ([str], optional) – An array of AWS regions to exclude from metrics collection.

• extended_resource_collection_enabled (bool, optional) – Whether Datadog collects additional attributes and configuration information about the resources in your AWS account. Required for cspm_resource_collection.

• filter_tags ([str], optional) – The array of EC2 tags (in the form key:value ) defines a filter that Datadog uses when collecting metrics from EC2. Wildcards, such as ? (for single characters) and * (for multiple characters) can also be used. Only hosts that match one of the defined tags will be imported into Datadog. The rest will be ignored. Host matching a given tag can also be excluded by adding ! before the tag. For example, env:production,instance-type:c1.*,!region:us-east-1

• host_tags ([str], optional) – Array of tags (in the form key:value ) to add to all hosts and metrics reporting through this integration.

• metrics_collection_enabled (bool, optional) – Whether Datadog collects metrics for this AWS account.

• resource_collection_enabled (bool, optional) – Deprecated in favor of ‘extended_resource_collection_enabled’. Whether Datadog collects a standard set of resources from your AWS account. Deprecated.

• role_name (str, optional) – Your Datadog role delegation name.

• secret_access_key (str, optional) – Your AWS secret access key. Only required if your AWS account is a GovCloud or China account.

datadog_api_client.v1.model.aws_account_and_lambda_request module

class AWSAccountAndLambdaRequest(arg: None)

class AWSAccountAndLambdaRequest(arg: ModelComposed)

class AWSAccountAndLambdaRequest(*args, **kwargs)

Bases: ModelNormal

AWS account ID and Lambda ARN.

Parameters:

• account_id (str) – Your AWS Account ID without dashes.

• lambda_arn (str) – ARN of the Datadog Lambda created during the Datadog-Amazon Web services Log collection setup.

datadog_api_client.v1.model.aws_account_create_response module

class AWSAccountCreateResponse(arg: None)

class AWSAccountCreateResponse(arg: ModelComposed)

class AWSAccountCreateResponse(*args, **kwargs)

Bases: ModelNormal

The Response returned by the AWS Create Account call.

Parameters:

external_id (str, optional) – AWS external_id.

datadog_api_client.v1.model.aws_account_delete_request module

class AWSAccountDeleteRequest(arg: None)

class AWSAccountDeleteRequest(arg: ModelComposed)

class AWSAccountDeleteRequest(*args, **kwargs)

Bases: ModelNormal

List of AWS accounts to delete.

Parameters:

• access_key_id (str, optional) – Your AWS access key ID. Only required if your AWS account is a GovCloud or China account.

• account_id (str, optional) – Your AWS Account ID without dashes.

• role_name (str, optional) – Your Datadog role delegation name.

datadog_api_client.v1.model.aws_account_list_response module

class AWSAccountListResponse(arg: None)

class AWSAccountListResponse(arg: ModelComposed)

class AWSAccountListResponse(*args, **kwargs)

Bases: ModelNormal

List of enabled AWS accounts.

Parameters:

accounts ([AWSAccount], optional) – List of enabled AWS accounts.

datadog_api_client.v1.model.aws_event_bridge_account_configuration module

class AWSEventBridgeAccountConfiguration(arg: None)

class AWSEventBridgeAccountConfiguration(arg: ModelComposed)

class AWSEventBridgeAccountConfiguration(*args, **kwargs)

Bases: ModelNormal

The EventBridge configuration for one AWS account.

Parameters:

• account_id (str, optional) – Your AWS Account ID without dashes.

• event_hubs ([AWSEventBridgeSource], optional) – Array of AWS event sources associated with this account.

• tags ([str], optional) – Array of tags (in the form key:value ) which are added to all hosts and metrics reporting through the main AWS integration.

datadog_api_client.v1.model.aws_event_bridge_create_request module

class AWSEventBridgeCreateRequest(arg: None)

class AWSEventBridgeCreateRequest(arg: ModelComposed)

class AWSEventBridgeCreateRequest(*args, **kwargs)

Bases: ModelNormal

An object used to create an EventBridge source.

Parameters:

• account_id (str, optional) – Your AWS Account ID without dashes.

• create_event_bus (bool, optional) – True if Datadog should create the event bus in addition to the event source. Requires the events:CreateEventBus permission.

• event_generator_name (str, optional) – The given part of the event source name, which is then combined with an assigned suffix to form the full name.

• region (str, optional) – The event source’s AWS region.

datadog_api_client.v1.model.aws_event_bridge_create_response module

class AWSEventBridgeCreateResponse(arg: None)

class AWSEventBridgeCreateResponse(arg: ModelComposed)

class AWSEventBridgeCreateResponse(*args, **kwargs)

Bases: ModelNormal

A created EventBridge source.

Parameters:

• event_source_name (str, optional) – The event source name.

• has_bus (bool, optional) – True if the event bus was created in addition to the source.

• region (str, optional) –

  The event source’s AWS region.

• status (AWSEventBridgeCreateStatus, optional) – The event source status “created”.

datadog_api_client.v1.model.aws_event_bridge_create_status module

class AWSEventBridgeCreateStatus(arg: None)

class AWSEventBridgeCreateStatus(arg: ModelComposed)

class AWSEventBridgeCreateStatus(*args, **kwargs)

Bases: ModelSimple

The event source status “created”.

Parameters:

• value (str) – If omitted defaults to “created”. Must be one of [“created”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.aws_event_bridge_delete_request module

class AWSEventBridgeDeleteRequest(arg: None)

class AWSEventBridgeDeleteRequest(arg: ModelComposed)

class AWSEventBridgeDeleteRequest(*args, **kwargs)

Bases: ModelNormal

An object used to delete an EventBridge source.

Parameters:

• account_id (str, optional) – Your AWS Account ID without dashes.

• event_generator_name (str, optional) – The event source name.

• region (str, optional) –

  The event source’s AWS region.

datadog_api_client.v1.model.aws_event_bridge_delete_response module

class AWSEventBridgeDeleteResponse(arg: None)

class AWSEventBridgeDeleteResponse(arg: ModelComposed)

class AWSEventBridgeDeleteResponse(*args, **kwargs)

Bases: ModelNormal

An indicator of the successful deletion of an EventBridge source.

Parameters:

status (AWSEventBridgeDeleteStatus, optional) – The event source status “empty”.

datadog_api_client.v1.model.aws_event_bridge_delete_status module

class AWSEventBridgeDeleteStatus(arg: None)

class AWSEventBridgeDeleteStatus(arg: ModelComposed)

class AWSEventBridgeDeleteStatus(*args, **kwargs)

Bases: ModelSimple

The event source status “empty”.

Parameters:

• value (str) – If omitted defaults to “empty”. Must be one of [“empty”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.aws_event_bridge_list_response module

class AWSEventBridgeListResponse(arg: None)

class AWSEventBridgeListResponse(arg: ModelComposed)

class AWSEventBridgeListResponse(*args, **kwargs)

Bases: ModelNormal

An object describing the EventBridge configuration for multiple accounts.

Parameters:

• accounts ([AWSEventBridgeAccountConfiguration], optional) – List of accounts with their event sources.

• is_installed (bool, optional) – True if the EventBridge sub-integration is enabled for your organization.

datadog_api_client.v1.model.aws_event_bridge_source module

class AWSEventBridgeSource(arg: None)

class AWSEventBridgeSource(arg: ModelComposed)

class AWSEventBridgeSource(*args, **kwargs)

Bases: ModelNormal

An EventBridge source.

Parameters:

• name (str, optional) – The event source name.

• region (str, optional) –

  The event source’s AWS region.

datadog_api_client.v1.model.aws_logs_async_error module

class AWSLogsAsyncError(arg: None)

class AWSLogsAsyncError(arg: ModelComposed)

class AWSLogsAsyncError(*args, **kwargs)

Bases: ModelNormal

Description of errors.

Parameters:

• code (str, optional) – Code properties

• message (str, optional) – Message content.

datadog_api_client.v1.model.aws_logs_async_response module

class AWSLogsAsyncResponse(arg: None)

class AWSLogsAsyncResponse(arg: ModelComposed)

class AWSLogsAsyncResponse(*args, **kwargs)

Bases: ModelNormal

A list of all Datadog-AWS logs integrations available in your Datadog organization.

Parameters:

• errors ([AWSLogsAsyncError], optional) – List of errors.

• status (str, optional) – Status of the properties.

datadog_api_client.v1.model.aws_logs_lambda module

class AWSLogsLambda(arg: None)

class AWSLogsLambda(arg: ModelComposed)

class AWSLogsLambda(*args, **kwargs)

Bases: ModelNormal

Description of the Lambdas.

Parameters:

arn (str, optional) – Available ARN IDs.

datadog_api_client.v1.model.aws_logs_list_response module

class AWSLogsListResponse(arg: None)

class AWSLogsListResponse(arg: ModelComposed)

class AWSLogsListResponse(*args, **kwargs)

Bases: ModelNormal

A list of all Datadog-AWS logs integrations available in your Datadog organization.

Parameters:

• account_id (str, optional) – Your AWS Account ID without dashes.

• lambdas ([AWSLogsLambda], optional) – List of ARNs configured in your Datadog account.

• services ([str], optional) – Array of services IDs.

datadog_api_client.v1.model.aws_logs_list_services_response module

class AWSLogsListServicesResponse(arg: None)

class AWSLogsListServicesResponse(arg: ModelComposed)

class AWSLogsListServicesResponse(*args, **kwargs)

Bases: ModelNormal

The list of current AWS services for which Datadog offers automatic log collection.

Parameters:

• id (str, optional) – Key value in returned object.

• label (str, optional) – Name of service available for configuration with Datadog logs.

datadog_api_client.v1.model.aws_logs_services_request module

class AWSLogsServicesRequest(arg: None)

class AWSLogsServicesRequest(arg: ModelComposed)

class AWSLogsServicesRequest(*args, **kwargs)

Bases: ModelNormal

A list of current AWS services for which Datadog offers automatic log collection.

Parameters:

• account_id (str) – Your AWS Account ID without dashes.

• services ([str]) – Array of services IDs set to enable automatic log collection. Discover the list of available services with the get list of AWS log ready services API endpoint.

datadog_api_client.v1.model.aws_namespace module

class AWSNamespace(arg: None)

class AWSNamespace(arg: ModelComposed)

class AWSNamespace(*args, **kwargs)

Bases: ModelSimple

The namespace associated with the tag filter entry.

Parameters:

• value (str) – Must be one of [“elb”, “application_elb”, “sqs”, “rds”, “custom”, “network_elb”, “lambda”, “step_functions”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.aws_tag_filter module

class AWSTagFilter(arg: None)

class AWSTagFilter(arg: ModelComposed)

class AWSTagFilter(*args, **kwargs)

Bases: ModelNormal

A tag filter.

Parameters:

• namespace (AWSNamespace, optional) – The namespace associated with the tag filter entry.

• tag_filter_str (str, optional) – The tag filter string.

datadog_api_client.v1.model.aws_tag_filter_create_request module

class AWSTagFilterCreateRequest(arg: None)

class AWSTagFilterCreateRequest(arg: ModelComposed)

class AWSTagFilterCreateRequest(*args, **kwargs)

Bases: ModelNormal

The objects used to set an AWS tag filter.

Parameters:

• account_id (str, optional) – Your AWS Account ID without dashes.

• namespace (AWSNamespace, optional) – The namespace associated with the tag filter entry.

• tag_filter_str (str, optional) – The tag filter string.

datadog_api_client.v1.model.aws_tag_filter_delete_request module

class AWSTagFilterDeleteRequest(arg: None)

class AWSTagFilterDeleteRequest(arg: ModelComposed)

class AWSTagFilterDeleteRequest(*args, **kwargs)

Bases: ModelNormal

The objects used to delete an AWS tag filter entry.

Parameters:

• account_id (str, optional) – The unique identifier of your AWS account.

• namespace (AWSNamespace, optional) – The namespace associated with the tag filter entry.

datadog_api_client.v1.model.aws_tag_filter_list_response module

class AWSTagFilterListResponse(arg: None)

class AWSTagFilterListResponse(arg: ModelComposed)

class AWSTagFilterListResponse(*args, **kwargs)

Bases: ModelNormal

An array of tag filter rules by namespace and tag filter string.

Parameters:

filters ([AWSTagFilter], optional) – An array of tag filters.

datadog_api_client.v1.model.azure_account module

class AzureAccount(arg: None)

class AzureAccount(arg: ModelComposed)

class AzureAccount(*args, **kwargs)

Bases: ModelNormal

Datadog-Azure integrations configured for your organization.

Parameters:

• app_service_plan_filters (str, optional) – Limit the Azure app service plans that are pulled into Datadog using tags. Only app service plans that match one of the defined tags are imported into Datadog.

• automute (bool, optional) – Silence monitors for expected Azure VM shutdowns.

• client_id (str, optional) – Your Azure web application ID.

• client_secret (str, optional) – Your Azure web application secret key.

• container_app_filters (str, optional) – Limit the Azure container apps that are pulled into Datadog using tags. Only container apps that match one of the defined tags are imported into Datadog.

• cspm_enabled (bool, optional) – When enabled, Datadog’s Cloud Security Management product scans resource configurations monitored by this app registration. Note: This requires resource_collection_enabled to be set to true.

• custom_metrics_enabled (bool, optional) – Enable custom metrics for your organization.

• errors ([str], optional) – Errors in your configuration.

• host_filters (str, optional) – Limit the Azure instances that are pulled into Datadog by using tags. Only hosts that match one of the defined tags are imported into Datadog.

• metrics_enabled (bool, optional) – Enable Azure metrics for your organization.

• metrics_enabled_default (bool, optional) – Enable Azure metrics for your organization for resource providers where no resource provider config is specified.

• new_client_id (str, optional) – Your New Azure web application ID.

• new_tenant_name (str, optional) – Your New Azure Active Directory ID.

• resource_collection_enabled (bool, optional) – When enabled, Datadog collects metadata and configuration info from cloud resources (compute instances, databases, load balancers, etc.) monitored by this app registration.

• resource_provider_configs ([ResourceProviderConfig], optional) – Configuration settings applied to resources from the specified Azure resource providers.

• tenant_name (str, optional) – Your Azure Active Directory ID.

• usage_metrics_enabled (bool, optional) – Enable azure.usage metrics for your organization.

datadog_api_client.v1.model.azure_account_list_response module

class AzureAccountListResponse(arg: None)

class AzureAccountListResponse(arg: ModelComposed)

class AzureAccountListResponse(*args, **kwargs)

Bases: ModelSimple

Accounts configured for your organization.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.cancel_downtimes_by_scope_request module

class CancelDowntimesByScopeRequest(arg: None)

class CancelDowntimesByScopeRequest(arg: ModelComposed)

class CancelDowntimesByScopeRequest(*args, **kwargs)

Bases: ModelNormal

Cancel downtimes according to scope.

Parameters:

scope (str) – The scope(s) to which the downtime applies and must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).

datadog_api_client.v1.model.canceled_downtimes_ids module

class CanceledDowntimesIds(arg: None)

class CanceledDowntimesIds(arg: ModelComposed)

class CanceledDowntimesIds(*args, **kwargs)

Bases: ModelNormal

Object containing array of IDs of canceled downtimes.

Parameters:

cancelled_ids ([int], optional) – ID of downtimes that were canceled.

datadog_api_client.v1.model.change_widget_definition module

class ChangeWidgetDefinition(arg: None)

class ChangeWidgetDefinition(arg: ModelComposed)

class ChangeWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The Change graph shows you the change in a value over the time period chosen.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• requests ([ChangeWidgetRequest]) –

  Array of one request object to display in the widget.

  See the dedicated Request JSON schema documentation

  to learn how to build the REQUEST_SCHEMA.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (ChangeWidgetDefinitionType) – Type of the change widget.

datadog_api_client.v1.model.change_widget_definition_type module

class ChangeWidgetDefinitionType(arg: None)

class ChangeWidgetDefinitionType(arg: ModelComposed)

class ChangeWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the change widget.

Parameters:

• value (str) – If omitted defaults to “change”. Must be one of [“change”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.change_widget_request module

class ChangeWidgetRequest(arg: None)

class ChangeWidgetRequest(arg: ModelComposed)

class ChangeWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated change widget.

Parameters:

• apm_query (LogQueryDefinition, optional) – The log query.

• change_type (WidgetChangeType, optional) – Show the absolute or the relative change.

• compare_to (WidgetCompareTo, optional) – Timeframe used for the change comparison.

• event_query (LogQueryDefinition, optional) – The log query.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• increase_good (bool, optional) – Whether to show increase as good.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• order_by (WidgetOrderBy, optional) – What to order by.

• order_dir (WidgetSort, optional) – Widget sorting methods.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Query definition.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• show_present (bool, optional) – Whether to show the present value.

datadog_api_client.v1.model.check_can_delete_monitor_response module

class CheckCanDeleteMonitorResponse(arg: None)

class CheckCanDeleteMonitorResponse(arg: ModelComposed)

class CheckCanDeleteMonitorResponse(*args, **kwargs)

Bases: ModelNormal

Response of monitor IDs that can or can’t be safely deleted.

Parameters:

• data (CheckCanDeleteMonitorResponseData) – Wrapper object with the list of monitor IDs.

• errors ({str: ([str],)}, none_type, optional) – A mapping of Monitor ID to strings denoting where it’s used.

datadog_api_client.v1.model.check_can_delete_monitor_response_data module

class CheckCanDeleteMonitorResponseData(arg: None)

class CheckCanDeleteMonitorResponseData(arg: ModelComposed)

class CheckCanDeleteMonitorResponseData(*args, **kwargs)

Bases: ModelNormal

Wrapper object with the list of monitor IDs.

Parameters:

ok ([int], optional) – An array of Monitor IDs that can be safely deleted.

datadog_api_client.v1.model.check_can_delete_slo_response module

class CheckCanDeleteSLOResponse(arg: None)

class CheckCanDeleteSLOResponse(arg: ModelComposed)

class CheckCanDeleteSLOResponse(*args, **kwargs)

Bases: ModelNormal

A service level objective response containing the requested object.

Parameters:

• data (CheckCanDeleteSLOResponseData, optional) – An array of service level objective objects.

• errors ({str: (str,)}, optional) – A mapping of SLO id to it’s current usages.

datadog_api_client.v1.model.check_can_delete_slo_response_data module

class CheckCanDeleteSLOResponseData(arg: None)

class CheckCanDeleteSLOResponseData(arg: ModelComposed)

class CheckCanDeleteSLOResponseData(*args, **kwargs)

Bases: ModelNormal

An array of service level objective objects.

Parameters:

ok ([str], optional) – An array of SLO IDs that can be safely deleted.

datadog_api_client.v1.model.check_status_widget_definition module

class CheckStatusWidgetDefinition(arg: None)

class CheckStatusWidgetDefinition(arg: ModelComposed)

class CheckStatusWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Check status shows the current status or number of results for any check performed.

Parameters:

• check (str) – Name of the check to use in the widget.

• group (str, optional) – Group reporting a single check.

• group_by ([str], optional) – List of tag prefixes to group by in the case of a cluster check.

• grouping (WidgetGrouping) – The kind of grouping to use.

• tags ([str], optional) – List of tags used to filter the groups reporting a cluster check.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (CheckStatusWidgetDefinitionType) – Type of the check status widget.

datadog_api_client.v1.model.check_status_widget_definition_type module

class CheckStatusWidgetDefinitionType(arg: None)

class CheckStatusWidgetDefinitionType(arg: ModelComposed)

class CheckStatusWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the check status widget.

Parameters:

• value (str) – If omitted defaults to “check_status”. Must be one of [“check_status”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.content_encoding module

class ContentEncoding(arg: None)

class ContentEncoding(arg: ModelComposed)

class ContentEncoding(*args, **kwargs)

Bases: ModelSimple

HTTP header used to compress the media-type.

Parameters:

• value (str) – Must be one of [“gzip”, “deflate”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.creator module

class Creator(arg: None)

class Creator(arg: ModelComposed)

class Creator(*args, **kwargs)

Bases: ModelNormal

Object describing the creator of the shared element.

Parameters:

• email (str, optional) – Email of the creator.

• handle (str, optional) – Handle of the creator.

• name (str, none_type, optional) – Name of the creator.

datadog_api_client.v1.model.dashboard module

class Dashboard(arg: None)

class Dashboard(arg: ModelComposed)

class Dashboard(*args, **kwargs)

Bases: ModelNormal

A dashboard is Datadog’s tool for visually tracking, analyzing, and displaying key performance metrics, which enable you to monitor the health of your infrastructure.

Parameters:

• author_handle (str, optional) – Identifier of the dashboard author.

• author_name (str, none_type, optional) – Name of the dashboard author.

• created_at (datetime, optional) – Creation date of the dashboard.

• description (str, none_type, optional) – Description of the dashboard.

• id (str, optional) – ID of the dashboard.

• is_read_only (bool, optional) –

  Whether this dashboard is read-only. If True, only the author and admins can make changes to it.

  This property is deprecated; please use the Restriction Policies API instead to manage write authorization for individual dashboards. Deprecated.

• layout_type (DashboardLayoutType) – Layout type of the dashboard.

• modified_at (datetime, optional) – Modification date of the dashboard.

• notify_list ([str], none_type, optional) – List of handles of users to notify when changes are made to this dashboard.

• reflow_type (DashboardReflowType, optional) – Reflow type for a new dashboard layout dashboard. Set this only when layout type is ‘ordered’. If set to ‘fixed’, the dashboard expects all widgets to have a layout, and if it’s set to ‘auto’, widgets should not have layouts.

• restricted_roles ([str], optional) – A list of role identifiers. Only the author and users associated with at least one of these roles can edit this dashboard.

• tags ([str], none_type, optional) – List of team names representing ownership of a dashboard.

• template_variable_presets ([DashboardTemplateVariablePreset], none_type, optional) – Array of template variables saved views.

• template_variables ([DashboardTemplateVariable], none_type, optional) – List of template variables for this dashboard.

• title (str) – Title of the dashboard.

• url (str, optional) – The URL of the dashboard.

• widgets ([Widget]) – List of widgets to display on the dashboard.

datadog_api_client.v1.model.dashboard_bulk_action_data module

class DashboardBulkActionData(arg: None)

class DashboardBulkActionData(arg: ModelComposed)

class DashboardBulkActionData(*args, **kwargs)

Bases: ModelNormal

Dashboard bulk action request data.

Parameters:

• id (str) – Dashboard resource ID.

• type (DashboardResourceType) – Dashboard resource type.

datadog_api_client.v1.model.dashboard_bulk_action_data_list module

class DashboardBulkActionDataList(arg: None)

class DashboardBulkActionDataList(arg: ModelComposed)

class DashboardBulkActionDataList(*args, **kwargs)

Bases: ModelSimple

List of dashboard bulk action request data objects.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.dashboard_bulk_delete_request module

class DashboardBulkDeleteRequest(arg: None)

class DashboardBulkDeleteRequest(arg: ModelComposed)

class DashboardBulkDeleteRequest(*args, **kwargs)

Bases: ModelNormal

Dashboard bulk delete request body.

Parameters:

data (DashboardBulkActionDataList) – List of dashboard bulk action request data objects.

datadog_api_client.v1.model.dashboard_delete_response module

class DashboardDeleteResponse(arg: None)

class DashboardDeleteResponse(arg: ModelComposed)

class DashboardDeleteResponse(*args, **kwargs)

Bases: ModelNormal

Response from the delete dashboard call.

Parameters:

deleted_dashboard_id (str, optional) – ID of the deleted dashboard.

datadog_api_client.v1.model.dashboard_global_time module

class DashboardGlobalTime(arg: None)

class DashboardGlobalTime(arg: ModelComposed)

class DashboardGlobalTime(*args, **kwargs)

Bases: ModelNormal

Object containing the live span selection for the dashboard.

Parameters:

live_span (DashboardGlobalTimeLiveSpan, optional) – Dashboard global time live_span selection

datadog_api_client.v1.model.dashboard_global_time_live_span module

class DashboardGlobalTimeLiveSpan(arg: None)

class DashboardGlobalTimeLiveSpan(arg: ModelComposed)

class DashboardGlobalTimeLiveSpan(*args, **kwargs)

Bases: ModelSimple

Dashboard global time live_span selection

Parameters:

• value (str) – Must be one of [“15m”, “1h”, “4h”, “1d”, “2d”, “1w”, “1mo”, “3mo”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.dashboard_invite_type module

class DashboardInviteType(arg: None)

class DashboardInviteType(arg: ModelComposed)

class DashboardInviteType(*args, **kwargs)

Bases: ModelSimple

Type for shared dashboard invitation request body.

Parameters:

• value (str) – If omitted defaults to “public_dashboard_invitation”. Must be one of [“public_dashboard_invitation”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.dashboard_layout_type module

class DashboardLayoutType(arg: None)

class DashboardLayoutType(arg: ModelComposed)

class DashboardLayoutType(*args, **kwargs)

Bases: ModelSimple

Layout type of the dashboard.

Parameters:

• value (str) – Must be one of [“ordered”, “free”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.dashboard_list module

class DashboardList(arg: None)

class DashboardList(arg: ModelComposed)

class DashboardList(*args, **kwargs)

Bases: ModelNormal

Your Datadog Dashboards.

Parameters:

• author (Creator, optional) – Object describing the creator of the shared element.

• created (datetime, optional) – Date of creation of the dashboard list.

• dashboard_count (int, optional) – The number of dashboards in the list.

• id (int, optional) – The ID of the dashboard list.

• is_favorite (bool, optional) – Whether or not the list is in the favorites.

• modified (datetime, optional) – Date of last edition of the dashboard list.

• name (str) – The name of the dashboard list.

• type (str, optional) – The type of dashboard list.

datadog_api_client.v1.model.dashboard_list_delete_response module

class DashboardListDeleteResponse(arg: None)

class DashboardListDeleteResponse(arg: ModelComposed)

class DashboardListDeleteResponse(*args, **kwargs)

Bases: ModelNormal

Deleted dashboard details.

Parameters:

deleted_dashboard_list_id (int, optional) – ID of the deleted dashboard list.

datadog_api_client.v1.model.dashboard_list_list_response module

class DashboardListListResponse(arg: None)

class DashboardListListResponse(arg: ModelComposed)

class DashboardListListResponse(*args, **kwargs)

Bases: ModelNormal

Information on your dashboard lists.

Parameters:

dashboard_lists ([DashboardList], optional) – List of all your dashboard lists.

datadog_api_client.v1.model.dashboard_reflow_type module

class DashboardReflowType(arg: None)

class DashboardReflowType(arg: ModelComposed)

class DashboardReflowType(*args, **kwargs)

Bases: ModelSimple

Reflow type for a new dashboard layout dashboard. Set this only when layout type is ‘ordered’.

If set to ‘fixed’, the dashboard expects all widgets to have a layout, and if it’s set to ‘auto’, widgets should not have layouts.

Parameters:

• value (str) – Must be one of [“auto”, “fixed”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.dashboard_resource_type module

class DashboardResourceType(arg: None)

class DashboardResourceType(arg: ModelComposed)

class DashboardResourceType(*args, **kwargs)

Bases: ModelSimple

Dashboard resource type.

Parameters:

• value (str) – If omitted defaults to “dashboard”. Must be one of [“dashboard”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.dashboard_restore_request module

class DashboardRestoreRequest(arg: None)

class DashboardRestoreRequest(arg: ModelComposed)

class DashboardRestoreRequest(*args, **kwargs)

Bases: ModelNormal

Dashboard restore request body.

Parameters:

data (DashboardBulkActionDataList) – List of dashboard bulk action request data objects.

datadog_api_client.v1.model.dashboard_share_type module

class DashboardShareType(arg: None)

class DashboardShareType(arg: ModelComposed)

class DashboardShareType(*args, **kwargs)

Bases: ModelSimple

Type of sharing access (either open to anyone who has the public URL or invite-only).

Parameters:

• value (str) – Must be one of [“open”, “invite”, “embed”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.dashboard_summary module

class DashboardSummary(arg: None)

class DashboardSummary(arg: ModelComposed)

class DashboardSummary(*args, **kwargs)

Bases: ModelNormal

Dashboard summary response.

Parameters:

dashboards ([DashboardSummaryDefinition], optional) – List of dashboard definitions.

datadog_api_client.v1.model.dashboard_summary_definition module

class DashboardSummaryDefinition(arg: None)

class DashboardSummaryDefinition(arg: ModelComposed)

class DashboardSummaryDefinition(*args, **kwargs)

Bases: ModelNormal

Dashboard definition.

Parameters:

• author_handle (str, optional) – Identifier of the dashboard author.

• created_at (datetime, optional) – Creation date of the dashboard.

• description (str, none_type, optional) – Description of the dashboard.

• id (str, optional) – Dashboard identifier.

• is_read_only (bool, optional) –

  Whether this dashboard is read-only. If True, only the author and admins can make changes to it.

  This property is deprecated; please use the Restriction Policies API instead to manage write authorization for individual dashboards. Deprecated.

• layout_type (DashboardLayoutType, optional) – Layout type of the dashboard.

• modified_at (datetime, optional) – Modification date of the dashboard.

• title (str, optional) – Title of the dashboard.

• url (str, optional) – URL of the dashboard.

datadog_api_client.v1.model.dashboard_template_variable module

class DashboardTemplateVariable(arg: None)

class DashboardTemplateVariable(arg: ModelComposed)

class DashboardTemplateVariable(*args, **kwargs)

Bases: ModelNormal

Template variable.

Parameters:

• available_values ([str], none_type, optional) – The list of values that the template variable drop-down is limited to.

• default (str, none_type, optional) – (deprecated) The default value for the template variable on dashboard load. Cannot be used in conjunction with defaults. Deprecated.

• defaults ([str], optional) – One or many default values for template variables on load. If more than one default is specified, they will be unioned together with OR. Cannot be used in conjunction with default.

• name (str) – The name of the variable.

• prefix (str, none_type, optional) – The tag prefix associated with the variable. Only tags with this prefix appear in the variable drop-down.

• type (str, none_type, optional) – The type of variable. This is to differentiate between filter variables (interpolated in query) and group by variables (interpolated into group by).

datadog_api_client.v1.model.dashboard_template_variable_preset module

class DashboardTemplateVariablePreset(arg: None)

class DashboardTemplateVariablePreset(arg: ModelComposed)

class DashboardTemplateVariablePreset(*args, **kwargs)

Bases: ModelNormal

Template variables saved views.

Parameters:

• name (str, optional) – The name of the variable.

• template_variables ([DashboardTemplateVariablePresetValue], optional) – List of variables.

datadog_api_client.v1.model.dashboard_template_variable_preset_value module

class DashboardTemplateVariablePresetValue(arg: None)

class DashboardTemplateVariablePresetValue(arg: ModelComposed)

class DashboardTemplateVariablePresetValue(*args, **kwargs)

Bases: ModelNormal

Template variables saved views.

Parameters:

• name (str, optional) – The name of the variable.

• value (str, optional) – (deprecated) The value of the template variable within the saved view. Cannot be used in conjunction with values. Deprecated.

• values ([str], optional) – One or many template variable values within the saved view, which will be unioned together using OR if more than one is specified. Cannot be used in conjunction with value.

datadog_api_client.v1.model.dashboard_type module

class DashboardType(arg: None)

class DashboardType(arg: ModelComposed)

class DashboardType(*args, **kwargs)

Bases: ModelSimple

The type of the associated private dashboard.

Parameters:

• value (str) – Must be one of [“custom_timeboard”, “custom_screenboard”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.delete_shared_dashboard_response module

class DeleteSharedDashboardResponse(arg: None)

class DeleteSharedDashboardResponse(arg: ModelComposed)

class DeleteSharedDashboardResponse(*args, **kwargs)

Bases: ModelNormal

Response containing token of deleted shared dashboard.

Parameters:

deleted_public_dashboard_token (str, optional) – Token associated with the shared dashboard that was revoked.

datadog_api_client.v1.model.deleted_monitor module

class DeletedMonitor(arg: None)

class DeletedMonitor(arg: ModelComposed)

class DeletedMonitor(*args, **kwargs)

Bases: ModelNormal

Response from the delete monitor call.

Parameters:

deleted_monitor_id (int, optional) – ID of the deleted monitor.

datadog_api_client.v1.model.distribution_point module

class DistributionPoint(arg: None)

class DistributionPoint(arg: ModelComposed)

class DistributionPoint(*args, **kwargs)

Bases: ModelSimple

Array of distribution points.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.distribution_points_content_encoding module

class DistributionPointsContentEncoding(arg: None)

class DistributionPointsContentEncoding(arg: ModelComposed)

class DistributionPointsContentEncoding(*args, **kwargs)

Bases: ModelSimple

HTTP header used to compress the media-type.

Parameters:

• value (str) – If omitted defaults to “deflate”. Must be one of [“deflate”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.distribution_points_payload module

class DistributionPointsPayload(arg: None)

class DistributionPointsPayload(arg: ModelComposed)

class DistributionPointsPayload(*args, **kwargs)

Bases: ModelNormal

The distribution points payload.

Parameters:

series ([DistributionPointsSeries]) – A list of distribution points series to submit to Datadog.

datadog_api_client.v1.model.distribution_points_series module

class DistributionPointsSeries(arg: None)

class DistributionPointsSeries(arg: ModelComposed)

class DistributionPointsSeries(*args, **kwargs)

Bases: ModelNormal

A distribution points metric to submit to Datadog.

Parameters:

• host (str, optional) – The name of the host that produced the distribution point metric.

• metric (str) – The name of the distribution points metric.

• points ([DistributionPoint]) – Points relating to the distribution point metric. All points must be tuples with timestamp and a list of values (cannot be a string). Timestamps should be in POSIX time in seconds.

• tags ([str], optional) – A list of tags associated with the distribution point metric.

• type (DistributionPointsType, optional) – The type of the distribution point.

datadog_api_client.v1.model.distribution_points_type module

class DistributionPointsType(arg: None)

class DistributionPointsType(arg: ModelComposed)

class DistributionPointsType(*args, **kwargs)

Bases: ModelSimple

The type of the distribution point.

Parameters:

• value (str) – If omitted defaults to “distribution”. Must be one of [“distribution”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.distribution_widget_definition module

class DistributionWidgetDefinition(arg: None)

class DistributionWidgetDefinition(arg: ModelComposed)

class DistributionWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The Distribution visualization is another way of showing metrics aggregated across one or several tags, such as hosts. Unlike the heat map, a distribution graph’s x-axis is quantity rather than time.

Parameters:

• custom_links ([WidgetCustomLink], optional) – A list of custom links.

• legend_size (str, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar. Deprecated.

• markers ([WidgetMarker], optional) – List of markers.

• requests ([DistributionWidgetRequest]) –

  Array of one request object to display in the widget.

  See the dedicated Request JSON schema documentation

  to learn how to build the REQUEST_SCHEMA.

• show_legend (bool, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar. Deprecated.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (DistributionWidgetDefinitionType) – Type of the distribution widget.

• xaxis (DistributionWidgetXAxis, optional) – X Axis controls for the distribution widget.

• yaxis (DistributionWidgetYAxis, optional) – Y Axis controls for the distribution widget.

datadog_api_client.v1.model.distribution_widget_definition_type module

class DistributionWidgetDefinitionType(arg: None)

class DistributionWidgetDefinitionType(arg: ModelComposed)

class DistributionWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the distribution widget.

Parameters:

• value (str) – If omitted defaults to “distribution”. Must be one of [“distribution”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.distribution_widget_histogram_request_query module

class DistributionWidgetHistogramRequestQuery(arg: None)

class DistributionWidgetHistogramRequestQuery(arg: ModelComposed)

class DistributionWidgetHistogramRequestQuery(*args, **kwargs)

Bases: ModelComposed

Query definition for Distribution Widget Histogram Request

Parameters:

• aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.

• name (str) – Name of the query for use in formulas.

• query (str) – Metrics query definition.

• compute (FormulaAndFunctionEventQueryDefinitionCompute) – Compute options.

• group_by ([FormulaAndFunctionEventQueryGroupBy], optional) – Group by options.

• indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.

• search (FormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.

• storage (str, optional) – Option for storage location. Feature in Private Beta.

• env (str) – APM environment.

• operation_name (str, optional) – Name of operation on service.

• primary_tag_name (str, optional) – Name of the second primary tag used within APM. Required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog

• primary_tag_value (str, optional) – Value of the second primary tag by which to filter APM data. primary_tag_name must also be specified.

• resource_name (str, optional) – APM resource name.

• service (str) – APM service name.

• stat (FormulaAndFunctionApmResourceStatName) – APM resource stat name.

datadog_api_client.v1.model.distribution_widget_histogram_request_type module

class DistributionWidgetHistogramRequestType(arg: None)

class DistributionWidgetHistogramRequestType(arg: ModelComposed)

class DistributionWidgetHistogramRequestType(*args, **kwargs)

Bases: ModelSimple

Request type for the histogram request.

Parameters:

• value (str) – If omitted defaults to “histogram”. Must be one of [“histogram”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.distribution_widget_request module

class DistributionWidgetRequest(arg: None)

class DistributionWidgetRequest(arg: ModelComposed)

class DistributionWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated distribution widget.

Parameters:

• apm_query (LogQueryDefinition, optional) – The log query.

• apm_stats_query (ApmStatsQueryDefinition, optional) – The APM stats query for table and distributions widgets.

• event_query (LogQueryDefinition, optional) – The log query.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Widget query.

• query (DistributionWidgetHistogramRequestQuery, optional) – Query definition for Distribution Widget Histogram Request

• request_type (DistributionWidgetHistogramRequestType, optional) – Request type for the histogram request.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• style (WidgetStyle, optional) – Widget style definition.

datadog_api_client.v1.model.distribution_widget_x_axis module

class DistributionWidgetXAxis(arg: None)

class DistributionWidgetXAxis(arg: ModelComposed)

class DistributionWidgetXAxis(*args, **kwargs)

Bases: ModelNormal

X Axis controls for the distribution widget.

Parameters:

• include_zero (bool, optional) – True includes zero.

• max (str, optional) – Specifies maximum value to show on the x-axis. It takes a number, percentile (p90 === 90th percentile), or auto for default behavior.

• min (str, optional) – Specifies minimum value to show on the x-axis. It takes a number, percentile (p90 === 90th percentile), or auto for default behavior.

• scale (str, optional) – Specifies the scale type. Possible values are linear.

datadog_api_client.v1.model.distribution_widget_y_axis module

class DistributionWidgetYAxis(arg: None)

class DistributionWidgetYAxis(arg: ModelComposed)

class DistributionWidgetYAxis(*args, **kwargs)

Bases: ModelNormal

Y Axis controls for the distribution widget.

Parameters:

• include_zero (bool, optional) – True includes zero.

• label (str, optional) – The label of the axis to display on the graph.

• max (str, optional) – Specifies the maximum value to show on the y-axis. It takes a number, or auto for default behavior.

• min (str, optional) – Specifies minimum value to show on the y-axis. It takes a number, or auto for default behavior.

• scale (str, optional) – Specifies the scale type. Possible values are linear or log.

datadog_api_client.v1.model.downtime module

class Downtime(arg: None)

class Downtime(arg: ModelComposed)

class Downtime(*args, **kwargs)

Bases: ModelNormal

Downtiming gives you greater control over monitor notifications by allowing you to globally exclude scopes from alerting. Downtime settings, which can be scheduled with start and end times, prevent all alerting related to specified Datadog tags.

Parameters:

• active (bool, optional) – If a scheduled downtime currently exists.

• active_child (DowntimeChild, none_type, optional) – The downtime object definition of the active child for the original parent recurring downtime. This field will only exist on recurring downtimes.

• canceled (int, none_type, optional) – If a scheduled downtime is canceled.

• creator_id (int, optional) – User ID of the downtime creator.

• disabled (bool, optional) – If a downtime has been disabled.

• downtime_type (int, optional) – 0 for a downtime applied on * or all, 1 when the downtime is only scoped to hosts, or 2 when the downtime is scoped to anything but hosts.

• end (int, none_type, optional) – POSIX timestamp to end the downtime. If not provided, the downtime is in effect indefinitely until you cancel it.

• id (int, optional) – The downtime ID.

• message (str, none_type, optional) – A message to include with notifications for this downtime. Email notifications can be sent to specific users by using the same @username notation as events.

• monitor_id (int, none_type, optional) – A single monitor to which the downtime applies. If not provided, the downtime applies to all monitors.

• monitor_tags ([str], optional) – A comma-separated list of monitor tags. For example, tags that are applied directly to monitors, not tags that are used in monitor queries (which are filtered by the scope parameter), to which the downtime applies. The resulting downtime applies to monitors that match ALL provided monitor tags. For example, service:postgres AND team:frontend.

• mute_first_recovery_notification (bool, optional) – If the first recovery notification during a downtime should be muted.

• notify_end_states ([NotifyEndState], optional) – States for which notify_end_types sends out notifications for.

• notify_end_types ([NotifyEndType], optional) – If set, notifies if a monitor is in an alert-worthy state ( ALERT , WARNING , or NO DATA ) when this downtime expires or is canceled. Applied to monitors that change states during the downtime (such as from OK to ALERT , WARNING , or NO DATA ), and to monitors that already have an alert-worthy state when downtime begins.

• parent_id (int, none_type, optional) – ID of the parent Downtime.

• recurrence (DowntimeRecurrence, none_type, optional) – An object defining the recurrence of the downtime.

• scope ([str], optional) – The scope(s) to which the downtime applies and must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).

• start (int, optional) – POSIX timestamp to start the downtime. If not provided, the downtime starts the moment it is created.

• timezone (str, optional) – The timezone in which to display the downtime’s start and end times in Datadog applications.

• updater_id (int, none_type, optional) – ID of the last user that updated the downtime.

datadog_api_client.v1.model.downtime_child module

class DowntimeChild(arg: None)

class DowntimeChild(arg: ModelComposed)

class DowntimeChild(*args, **kwargs)

Bases: ModelNormal

The downtime object definition of the active child for the original parent recurring downtime. This field will only exist on recurring downtimes.

Parameters:

• active (bool, optional) – If a scheduled downtime currently exists.

• canceled (int, none_type, optional) – If a scheduled downtime is canceled.

• creator_id (int, optional) – User ID of the downtime creator.

• disabled (bool, optional) – If a downtime has been disabled.

• downtime_type (int, optional) – 0 for a downtime applied on * or all, 1 when the downtime is only scoped to hosts, or 2 when the downtime is scoped to anything but hosts.

• end (int, none_type, optional) – POSIX timestamp to end the downtime. If not provided, the downtime is in effect indefinitely until you cancel it.

• id (int, optional) – The downtime ID.

• message (str, none_type, optional) – A message to include with notifications for this downtime. Email notifications can be sent to specific users by using the same @username notation as events.

• monitor_id (int, none_type, optional) – A single monitor to which the downtime applies. If not provided, the downtime applies to all monitors.

• monitor_tags ([str], optional) – A comma-separated list of monitor tags. For example, tags that are applied directly to monitors, not tags that are used in monitor queries (which are filtered by the scope parameter), to which the downtime applies. The resulting downtime applies to monitors that match ALL provided monitor tags. For example, service:postgres AND team:frontend.

• mute_first_recovery_notification (bool, optional) – If the first recovery notification during a downtime should be muted.

• notify_end_states ([NotifyEndState], optional) – States for which notify_end_types sends out notifications for.

• notify_end_types ([NotifyEndType], optional) – If set, notifies if a monitor is in an alert-worthy state ( ALERT , WARNING , or NO DATA ) when this downtime expires or is canceled. Applied to monitors that change states during the downtime (such as from OK to ALERT , WARNING , or NO DATA ), and to monitors that already have an alert-worthy state when downtime begins.

• parent_id (int, none_type, optional) – ID of the parent Downtime.

• recurrence (DowntimeRecurrence, none_type, optional) – An object defining the recurrence of the downtime.

• scope ([str], optional) – The scope(s) to which the downtime applies and must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).

• start (int, optional) – POSIX timestamp to start the downtime. If not provided, the downtime starts the moment it is created.

• timezone (str, optional) – The timezone in which to display the downtime’s start and end times in Datadog applications.

• updater_id (int, none_type, optional) – ID of the last user that updated the downtime.

datadog_api_client.v1.model.downtime_recurrence module

class DowntimeRecurrence(arg: None)

class DowntimeRecurrence(arg: ModelComposed)

class DowntimeRecurrence(*args, **kwargs)

Bases: ModelNormal

An object defining the recurrence of the downtime.

Parameters:

• period (int, optional) – How often to repeat as an integer. For example, to repeat every 3 days, select a type of days and a period of 3.

• rrule (str, optional) –

  The RRULE standard for defining recurring events ( requires to set “type” to rrule ) For example, to have a recurring event on the first day of each month, set the type to rrule and set the FREQ to MONTHLY and BYMONTHDAY to 1. Most common rrule options from the iCalendar Spec are supported.

  Note : Attributes specifying the duration in RRULE are not supported (for example, DTSTART , DTEND , DURATION ). More examples available in this downtime guide

• type (str, optional) – The type of recurrence. Choose from days , weeks , months , years , rrule.

• until_date (int, none_type, optional) – The date at which the recurrence should end as a POSIX timestamp. until_occurences and until_date are mutually exclusive.

• until_occurrences (int, none_type, optional) – How many times the downtime is rescheduled. until_occurences and until_date are mutually exclusive.

• week_days ([str], none_type, optional) – A list of week days to repeat on. Choose from Mon , Tue , Wed , Thu , Fri , Sat or Sun. Only applicable when type is weeks. First letter must be capitalized.

datadog_api_client.v1.model.event module

class Event(arg: None)

class Event(arg: ModelComposed)

class Event(*args, **kwargs)

Bases: ModelNormal

Object representing an event.

Parameters:

• alert_type (EventAlertType, optional) – If an alert event is enabled, set its type. For example, error , warning , info , success , user_update , recommendation , and snapshot.

• date_happened (int, optional) – POSIX timestamp of the event. Must be sent as an integer (that is no quotes). Limited to events up to 18 hours in the past and two hours in the future.

• device_name (str, optional) – A device name.

• host (str, optional) – Host name to associate with the event. Any tags associated with the host are also applied to this event.

• id (int, optional) – Integer ID of the event.

• id_str (str, optional) – Handling IDs as large 64-bit numbers can cause loss of accuracy issues with some programming languages. Instead, use the string representation of the Event ID to avoid losing accuracy.

• payload (str, optional) – Payload of the event.

• priority (EventPriority, none_type, optional) – The priority of the event. For example, normal or low.

• source_type_name (str, optional) – The type of event being posted. Option examples include nagios, hudson, jenkins, my_apps, chef, puppet, git, bitbucket, etc. The list of standard source attribute values available here.

• tags ([str], optional) – A list of tags to apply to the event.

• text (str, optional) – The body of the event. Limited to 4000 characters. The text supports markdown. To use markdown in the event text, start the text block with %%% \n and end the text block with \n %%%. Use msg_text with the Datadog Ruby library.

• title (str, optional) – The event title.

• url (str, optional) – URL of the event.

datadog_api_client.v1.model.event_alert_type module

class EventAlertType(arg: None)

class EventAlertType(arg: ModelComposed)

class EventAlertType(*args, **kwargs)

Bases: ModelSimple

If an alert event is enabled, set its type.

For example, error, warning, info, success, user_update, recommendation, and snapshot.

Parameters:

• value (str) – Must be one of [“error”, “warning”, “info”, “success”, “user_update”, “recommendation”, “snapshot”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.event_create_request module

class EventCreateRequest(arg: None)

class EventCreateRequest(arg: ModelComposed)

class EventCreateRequest(*args, **kwargs)

Bases: ModelNormal

Object representing an event.

Parameters:

• aggregation_key (str, optional) – An arbitrary string to use for aggregation. Limited to 100 characters. If you specify a key, all events using that key are grouped together in the Event Stream.

• alert_type (EventAlertType, optional) – If an alert event is enabled, set its type. For example, error , warning , info , success , user_update , recommendation , and snapshot.

• date_happened (int, optional) – POSIX timestamp of the event. Must be sent as an integer (that is no quotes). Limited to events no older than 18 hours

• device_name (str, optional) – A device name.

• host (str, optional) – Host name to associate with the event. Any tags associated with the host are also applied to this event.

• priority (EventPriority, none_type, optional) – The priority of the event. For example, normal or low.

• related_event_id (int, optional) – ID of the parent event. Must be sent as an integer (that is no quotes).

• source_type_name (str, optional) –

  The type of event being posted. Option examples include nagios, hudson, jenkins, my_apps, chef, puppet, git, bitbucket, etc. A complete list of source attribute values available here.

• tags ([str], optional) – A list of tags to apply to the event.

• text (str) – The body of the event. Limited to 4000 characters. The text supports markdown. To use markdown in the event text, start the text block with %%% \n and end the text block with \n %%%. Use msg_text with the Datadog Ruby library.

• title (str) – The event title.

datadog_api_client.v1.model.event_create_response module

class EventCreateResponse(arg: None)

class EventCreateResponse(arg: ModelComposed)

class EventCreateResponse(*args, **kwargs)

Bases: ModelNormal

Object containing an event response.

Parameters:

• event (Event, optional) – Object representing an event.

• status (str, optional) – A status.

datadog_api_client.v1.model.event_list_response module

class EventListResponse(arg: None)

class EventListResponse(arg: ModelComposed)

class EventListResponse(*args, **kwargs)

Bases: ModelNormal

An event list response.

Parameters:

• events ([Event], optional) – An array of events.

• status (str, optional) – A status.

datadog_api_client.v1.model.event_priority module

class EventPriority(arg: None)

class EventPriority(arg: ModelComposed)

class EventPriority(*args, **kwargs)

Bases: ModelSimple

The priority of the event. For example, normal or low.

Parameters:

• value (str) – Must be one of [“normal”, “low”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.event_query_definition module

class EventQueryDefinition(arg: None)

class EventQueryDefinition(arg: ModelComposed)

class EventQueryDefinition(*args, **kwargs)

Bases: ModelNormal

The event query.

Parameters:

• search (str) – The query being made on the event.

• tags_execution (str) – The execution method for multi-value filters. Can be either and or or.

datadog_api_client.v1.model.event_response module

class EventResponse(arg: None)

class EventResponse(arg: ModelComposed)

class EventResponse(*args, **kwargs)

Bases: ModelNormal

Object containing an event response.

Parameters:

• event (Event, optional) – Object representing an event.

• status (str, optional) – A status.

datadog_api_client.v1.model.event_stream_widget_definition module

class EventStreamWidgetDefinition(arg: None)

class EventStreamWidgetDefinition(arg: ModelComposed)

class EventStreamWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The event stream is a widget version of the stream of events on the Event Stream view. Only available on FREE layout dashboards.

Parameters:

• event_size (WidgetEventSize, optional) – Size to use to display an event.

• query (str) – Query to filter the event stream with.

• tags_execution (str, optional) – The execution method for multi-value filters. Can be either and or or.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (EventStreamWidgetDefinitionType) – Type of the event stream widget.

datadog_api_client.v1.model.event_stream_widget_definition_type module

class EventStreamWidgetDefinitionType(arg: None)

class EventStreamWidgetDefinitionType(arg: ModelComposed)

class EventStreamWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the event stream widget.

Parameters:

• value (str) – If omitted defaults to “event_stream”. Must be one of [“event_stream”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.event_timeline_widget_definition module

class EventTimelineWidgetDefinition(arg: None)

class EventTimelineWidgetDefinition(arg: ModelComposed)

class EventTimelineWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The event timeline is a widget version of the timeline that appears at the top of the Event Stream view. Only available on FREE layout dashboards.

Parameters:

• query (str) – Query to filter the event timeline with.

• tags_execution (str, optional) – The execution method for multi-value filters. Can be either and or or.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (EventTimelineWidgetDefinitionType) – Type of the event timeline widget.

datadog_api_client.v1.model.event_timeline_widget_definition_type module

class EventTimelineWidgetDefinitionType(arg: None)

class EventTimelineWidgetDefinitionType(arg: ModelComposed)

class EventTimelineWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the event timeline widget.

Parameters:

• value (str) – If omitted defaults to “event_timeline”. Must be one of [“event_timeline”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_apm_dependency_stat_name module

class FormulaAndFunctionApmDependencyStatName(arg: None)

class FormulaAndFunctionApmDependencyStatName(arg: ModelComposed)

class FormulaAndFunctionApmDependencyStatName(*args, **kwargs)

Bases: ModelSimple

APM statistic.

Parameters:

• value (str) – Must be one of [“avg_duration”, “avg_root_duration”, “avg_spans_per_trace”, “error_rate”, “pct_exec_time”, “pct_of_traces”, “total_traces_count”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_apm_dependency_stats_data_source module

class FormulaAndFunctionApmDependencyStatsDataSource(arg: None)

class FormulaAndFunctionApmDependencyStatsDataSource(arg: ModelComposed)

class FormulaAndFunctionApmDependencyStatsDataSource(*args, **kwargs)

Bases: ModelSimple

Data source for APM dependency stats queries.

Parameters:

• value (str) – If omitted defaults to “apm_dependency_stats”. Must be one of [“apm_dependency_stats”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_apm_dependency_stats_query_definition module

class FormulaAndFunctionApmDependencyStatsQueryDefinition(arg: None)

class FormulaAndFunctionApmDependencyStatsQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionApmDependencyStatsQueryDefinition(*args, **kwargs)

Bases: ModelNormal

A formula and functions APM dependency stats query.

Parameters:

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionApmDependencyStatsDataSource) – Data source for APM dependency stats queries.

• env (str) – APM environment.

• is_upstream (bool, optional) – Determines whether stats for upstream or downstream dependencies should be queried.

• name (str) – Name of query to use in formulas.

• operation_name (str) – Name of operation on service.

• primary_tag_name (str, optional) – The name of the second primary tag used within APM; required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog.

• primary_tag_value (str, optional) – Filter APM data by the second primary tag. primary_tag_name must also be specified.

• resource_name (str) – APM resource.

• service (str) – APM service.

• stat (FormulaAndFunctionApmDependencyStatName) – APM statistic.

datadog_api_client.v1.model.formula_and_function_apm_resource_stat_name module

class FormulaAndFunctionApmResourceStatName(arg: None)

class FormulaAndFunctionApmResourceStatName(arg: ModelComposed)

class FormulaAndFunctionApmResourceStatName(*args, **kwargs)

Bases: ModelSimple

APM resource stat name.

Parameters:

• value (str) – Must be one of [“errors”, “error_rate”, “hits”, “latency_avg”, “latency_distribution”, “latency_max”, “latency_p50”, “latency_p75”, “latency_p90”, “latency_p95”, “latency_p99”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_apm_resource_stats_data_source module

class FormulaAndFunctionApmResourceStatsDataSource(arg: None)

class FormulaAndFunctionApmResourceStatsDataSource(arg: ModelComposed)

class FormulaAndFunctionApmResourceStatsDataSource(*args, **kwargs)

Bases: ModelSimple

Data source for APM resource stats queries.

Parameters:

• value (str) – If omitted defaults to “apm_resource_stats”. Must be one of [“apm_resource_stats”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_apm_resource_stats_query_definition module

class FormulaAndFunctionApmResourceStatsQueryDefinition(arg: None)

class FormulaAndFunctionApmResourceStatsQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionApmResourceStatsQueryDefinition(*args, **kwargs)

Bases: ModelNormal

APM resource stats query using formulas and functions.

Parameters:

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionApmResourceStatsDataSource) – Data source for APM resource stats queries.

• env (str) – APM environment.

• group_by ([str], optional) – Array of fields to group results by.

• name (str) – Name of this query to use in formulas.

• operation_name (str, optional) – Name of operation on service.

• primary_tag_name (str, optional) – Name of the second primary tag used within APM. Required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog

• primary_tag_value (str, optional) – Value of the second primary tag by which to filter APM data. primary_tag_name must also be specified.

• resource_name (str, optional) – APM resource name.

• service (str) – APM service name.

• stat (FormulaAndFunctionApmResourceStatName) – APM resource stat name.

datadog_api_client.v1.model.formula_and_function_cloud_cost_data_source module

class FormulaAndFunctionCloudCostDataSource(arg: None)

class FormulaAndFunctionCloudCostDataSource(arg: ModelComposed)

class FormulaAndFunctionCloudCostDataSource(*args, **kwargs)

Bases: ModelSimple

Data source for Cloud Cost queries.

Parameters:

• value (str) – If omitted defaults to “cloud_cost”. Must be one of [“cloud_cost”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_cloud_cost_query_definition module

class FormulaAndFunctionCloudCostQueryDefinition(arg: None)

class FormulaAndFunctionCloudCostQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionCloudCostQueryDefinition(*args, **kwargs)

Bases: ModelNormal

A formula and functions Cloud Cost query.

Parameters:

• aggregator (WidgetAggregator, optional) – Aggregator used for the request.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionCloudCostDataSource) – Data source for Cloud Cost queries.

• name (str) – Name of the query for use in formulas.

• query (str) – Query for Cloud Cost data.

datadog_api_client.v1.model.formula_and_function_event_aggregation module

class FormulaAndFunctionEventAggregation(arg: None)

class FormulaAndFunctionEventAggregation(arg: ModelComposed)

class FormulaAndFunctionEventAggregation(*args, **kwargs)

Bases: ModelSimple

Aggregation methods for event platform queries.

Parameters:

• value (str) – Must be one of [“count”, “cardinality”, “median”, “pc75”, “pc90”, “pc95”, “pc98”, “pc99”, “sum”, “min”, “max”, “avg”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_event_query_definition module

class FormulaAndFunctionEventQueryDefinition(arg: None)

class FormulaAndFunctionEventQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionEventQueryDefinition(*args, **kwargs)

Bases: ModelNormal

A formula and functions events query.

Parameters:

• compute (FormulaAndFunctionEventQueryDefinitionCompute) – Compute options.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionEventsDataSource) – Data source for event platform-based queries.

• group_by ([FormulaAndFunctionEventQueryGroupBy], optional) – Group by options.

• indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.

• name (str) – Name of the query for use in formulas.

• search (FormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.

• storage (str, optional) – Option for storage location. Feature in Private Beta.

datadog_api_client.v1.model.formula_and_function_event_query_definition_compute module

class FormulaAndFunctionEventQueryDefinitionCompute(arg: None)

class FormulaAndFunctionEventQueryDefinitionCompute(arg: ModelComposed)

class FormulaAndFunctionEventQueryDefinitionCompute(*args, **kwargs)

Bases: ModelNormal

Compute options.

Parameters:

• aggregation (FormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.

• interval (int, optional) – A time interval in milliseconds.

• metric (str, optional) – Measurable attribute to compute.

datadog_api_client.v1.model.formula_and_function_event_query_definition_search module

class FormulaAndFunctionEventQueryDefinitionSearch(arg: None)

class FormulaAndFunctionEventQueryDefinitionSearch(arg: ModelComposed)

class FormulaAndFunctionEventQueryDefinitionSearch(*args, **kwargs)

Bases: ModelNormal

Search options.

Parameters:

query (str) – Events search string.

datadog_api_client.v1.model.formula_and_function_event_query_group_by module

class FormulaAndFunctionEventQueryGroupBy(arg: None)

class FormulaAndFunctionEventQueryGroupBy(arg: ModelComposed)

class FormulaAndFunctionEventQueryGroupBy(*args, **kwargs)

Bases: ModelNormal

List of objects used to group by.

Parameters:

• facet (str) – Event facet.

• limit (int, optional) – Number of groups to return.

• sort (FormulaAndFunctionEventQueryGroupBySort, optional) – Options for sorting group by results.

datadog_api_client.v1.model.formula_and_function_event_query_group_by_sort module

class FormulaAndFunctionEventQueryGroupBySort(arg: None)

class FormulaAndFunctionEventQueryGroupBySort(arg: ModelComposed)

class FormulaAndFunctionEventQueryGroupBySort(*args, **kwargs)

Bases: ModelNormal

Options for sorting group by results.

Parameters:

• aggregation (FormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.

• metric (str, optional) – Metric used for sorting group by results.

• order (QuerySortOrder, optional) – Direction of sort.

datadog_api_client.v1.model.formula_and_function_events_data_source module

class FormulaAndFunctionEventsDataSource(arg: None)

class FormulaAndFunctionEventsDataSource(arg: ModelComposed)

class FormulaAndFunctionEventsDataSource(*args, **kwargs)

Bases: ModelSimple

Data source for event platform-based queries.

Parameters:

• value (str) – Must be one of [“logs”, “spans”, “network”, “rum”, “security_signals”, “profiles”, “audit”, “events”, “ci_tests”, “ci_pipelines”, “incident_analytics”, “product_analytics”, “on_call_events”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_metric_aggregation module

class FormulaAndFunctionMetricAggregation(arg: None)

class FormulaAndFunctionMetricAggregation(arg: ModelComposed)

class FormulaAndFunctionMetricAggregation(*args, **kwargs)

Bases: ModelSimple

The aggregation methods available for metrics queries.

Parameters:

• value (str) – Must be one of [“avg”, “min”, “max”, “sum”, “last”, “area”, “l2norm”, “percentile”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_metric_data_source module

class FormulaAndFunctionMetricDataSource(arg: None)

class FormulaAndFunctionMetricDataSource(arg: ModelComposed)

class FormulaAndFunctionMetricDataSource(*args, **kwargs)

Bases: ModelSimple

Data source for metrics queries.

Parameters:

• value (str) – If omitted defaults to “metrics”. Must be one of [“metrics”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_metric_query_definition module

class FormulaAndFunctionMetricQueryDefinition(arg: None)

class FormulaAndFunctionMetricQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionMetricQueryDefinition(*args, **kwargs)

Bases: ModelNormal

A formula and functions metrics query.

Parameters:

• aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.

• name (str) – Name of the query for use in formulas.

• query (str) – Metrics query definition.

datadog_api_client.v1.model.formula_and_function_process_query_data_source module

class FormulaAndFunctionProcessQueryDataSource(arg: None)

class FormulaAndFunctionProcessQueryDataSource(arg: ModelComposed)

class FormulaAndFunctionProcessQueryDataSource(*args, **kwargs)

Bases: ModelSimple

Data sources that rely on the process backend.

Parameters:

• value (str) – Must be one of [“process”, “container”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_process_query_definition module

class FormulaAndFunctionProcessQueryDefinition(arg: None)

class FormulaAndFunctionProcessQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionProcessQueryDefinition(*args, **kwargs)

Bases: ModelNormal

Process query using formulas and functions.

Parameters:

• aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionProcessQueryDataSource) – Data sources that rely on the process backend.

• is_normalized_cpu (bool, optional) – Whether to normalize the CPU percentages.

• limit (int, optional) – Number of hits to return.

• metric (str) – Process metric name.

• name (str) – Name of query for use in formulas.

• sort (QuerySortOrder, optional) – Direction of sort.

• tag_filters ([str], optional) – An array of tags to filter by.

• text_filter (str, optional) – Text to use as filter.

datadog_api_client.v1.model.formula_and_function_query_definition module

class FormulaAndFunctionQueryDefinition(arg: None)

class FormulaAndFunctionQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionQueryDefinition(*args, **kwargs)

Bases: ModelComposed

A formula and function query.

Parameters:

• aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.

• name (str) – Name of the query for use in formulas.

• query (str) – Metrics query definition.

• compute (FormulaAndFunctionEventQueryDefinitionCompute) – Compute options.

• group_by ([FormulaAndFunctionEventQueryGroupBy], optional) – Group by options.

• indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.

• search (FormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.

• storage (str, optional) – Option for storage location. Feature in Private Beta.

• is_normalized_cpu (bool, optional) – Whether to normalize the CPU percentages.

• limit (int, optional) – Number of hits to return.

• metric (str) – Process metric name.

• sort (QuerySortOrder, optional) – Direction of sort.

• tag_filters ([str], optional) – An array of tags to filter by.

• text_filter (str, optional) – Text to use as filter.

• env (str) – APM environment.

• is_upstream (bool, optional) – Determines whether stats for upstream or downstream dependencies should be queried.

• operation_name (str) – Name of operation on service.

• primary_tag_name (str, optional) – The name of the second primary tag used within APM; required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog.

• primary_tag_value (str, optional) – Filter APM data by the second primary tag. primary_tag_name must also be specified.

• resource_name (str) – APM resource.

• service (str) – APM service.

• stat (FormulaAndFunctionApmDependencyStatName) – APM statistic.

• additional_query_filters (str, optional) – Additional filters applied to the SLO query.

• group_mode (FormulaAndFunctionSLOGroupMode, optional) – Group mode to query measures.

• measure (FormulaAndFunctionSLOMeasure) – SLO measures queries.

• slo_id (str) – ID of an SLO to query measures.

• slo_query_type (FormulaAndFunctionSLOQueryType, optional) – Name of the query for use in formulas.

datadog_api_client.v1.model.formula_and_function_response_format module

class FormulaAndFunctionResponseFormat(arg: None)

class FormulaAndFunctionResponseFormat(arg: ModelComposed)

class FormulaAndFunctionResponseFormat(*args, **kwargs)

Bases: ModelSimple

Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

Parameters:

• value (str) – Must be one of [“timeseries”, “scalar”, “event_list”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_slo_data_source module

class FormulaAndFunctionSLODataSource(arg: None)

class FormulaAndFunctionSLODataSource(arg: ModelComposed)

class FormulaAndFunctionSLODataSource(*args, **kwargs)

Bases: ModelSimple

Data source for SLO measures queries.

Parameters:

• value (str) – If omitted defaults to “slo”. Must be one of [“slo”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_slo_group_mode module

class FormulaAndFunctionSLOGroupMode(arg: None)

class FormulaAndFunctionSLOGroupMode(arg: ModelComposed)

class FormulaAndFunctionSLOGroupMode(*args, **kwargs)

Bases: ModelSimple

Group mode to query measures.

Parameters:

• value (str) – Must be one of [“overall”, “components”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_slo_measure module

class FormulaAndFunctionSLOMeasure(arg: None)

class FormulaAndFunctionSLOMeasure(arg: ModelComposed)

class FormulaAndFunctionSLOMeasure(*args, **kwargs)

Bases: ModelSimple

SLO measures queries.

Parameters:

• value (str) – Must be one of [“good_events”, “bad_events”, “good_minutes”, “bad_minutes”, “slo_status”, “error_budget_remaining”, “burn_rate”, “error_budget_burndown”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_and_function_slo_query_definition module

class FormulaAndFunctionSLOQueryDefinition(arg: None)

class FormulaAndFunctionSLOQueryDefinition(arg: ModelComposed)

class FormulaAndFunctionSLOQueryDefinition(*args, **kwargs)

Bases: ModelNormal

A formula and functions metrics query.

Parameters:

• additional_query_filters (str, optional) – Additional filters applied to the SLO query.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionSLODataSource) – Data source for SLO measures queries.

• group_mode (FormulaAndFunctionSLOGroupMode, optional) – Group mode to query measures.

• measure (FormulaAndFunctionSLOMeasure) – SLO measures queries.

• name (str, optional) – Name of the query for use in formulas.

• slo_id (str) – ID of an SLO to query measures.

• slo_query_type (FormulaAndFunctionSLOQueryType, optional) – Name of the query for use in formulas.

datadog_api_client.v1.model.formula_and_function_slo_query_type module

class FormulaAndFunctionSLOQueryType(arg: None)

class FormulaAndFunctionSLOQueryType(arg: ModelComposed)

class FormulaAndFunctionSLOQueryType(*args, **kwargs)

Bases: ModelSimple

Name of the query for use in formulas.

Parameters:

• value (str) – Must be one of [“metric”, “monitor”, “time_slice”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.formula_type module

class FormulaType(arg: None)

class FormulaType(arg: ModelComposed)

class FormulaType(*args, **kwargs)

Bases: ModelSimple

Set the sort type to formula.

Parameters:

• value (str) – If omitted defaults to “formula”. Must be one of [“formula”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.free_text_widget_definition module

class FreeTextWidgetDefinition(arg: None)

class FreeTextWidgetDefinition(arg: ModelComposed)

class FreeTextWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Free text is a widget that allows you to add headings to your screenboard. Commonly used to state the overall purpose of the dashboard. Only available on FREE layout dashboards.

Parameters:

• color (str, optional) – Color of the text.

• font_size (str, optional) – Size of the text.

• text (str) – Text to display.

• text_align (WidgetTextAlign, optional) – How to align the text on the widget.

• type (FreeTextWidgetDefinitionType) – Type of the free text widget.

datadog_api_client.v1.model.free_text_widget_definition_type module

class FreeTextWidgetDefinitionType(arg: None)

class FreeTextWidgetDefinitionType(arg: ModelComposed)

class FreeTextWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the free text widget.

Parameters:

• value (str) – If omitted defaults to “free_text”. Must be one of [“free_text”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.funnel_query module

class FunnelQuery(arg: None)

class FunnelQuery(arg: ModelComposed)

class FunnelQuery(*args, **kwargs)

Bases: ModelNormal

Updated funnel widget.

Parameters:

• data_source (FunnelSource) – Source from which to query items to display in the funnel.

• query_string (str) – The widget query.

• steps ([FunnelStep]) – List of funnel steps.

datadog_api_client.v1.model.funnel_request_type module

class FunnelRequestType(arg: None)

class FunnelRequestType(arg: ModelComposed)

class FunnelRequestType(*args, **kwargs)

Bases: ModelSimple

Widget request type.

Parameters:

• value (str) – If omitted defaults to “funnel”. Must be one of [“funnel”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.funnel_source module

class FunnelSource(arg: None)

class FunnelSource(arg: ModelComposed)

class FunnelSource(*args, **kwargs)

Bases: ModelSimple

Source from which to query items to display in the funnel.

Parameters:

• value (str) – If omitted defaults to “rum”. Must be one of [“rum”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.funnel_step module

class FunnelStep(arg: None)

class FunnelStep(arg: ModelComposed)

class FunnelStep(*args, **kwargs)

Bases: ModelNormal

The funnel step.

Parameters:

• facet (str) – The facet of the step.

• value (str) – The value of the step.

datadog_api_client.v1.model.funnel_widget_definition module

class FunnelWidgetDefinition(arg: None)

class FunnelWidgetDefinition(arg: ModelComposed)

class FunnelWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The funnel visualization displays a funnel of user sessions that maps a sequence of view navigation and user interaction in your application.

Parameters:

• requests ([FunnelWidgetRequest]) – Request payload used to query items.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – The title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – The size of the title.

• type (FunnelWidgetDefinitionType) – Type of funnel widget.

datadog_api_client.v1.model.funnel_widget_definition_type module

class FunnelWidgetDefinitionType(arg: None)

class FunnelWidgetDefinitionType(arg: ModelComposed)

class FunnelWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of funnel widget.

Parameters:

• value (str) – If omitted defaults to “funnel”. Must be one of [“funnel”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.funnel_widget_request module

class FunnelWidgetRequest(arg: None)

class FunnelWidgetRequest(arg: ModelComposed)

class FunnelWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated funnel widget.

Parameters:

• query (FunnelQuery) – Updated funnel widget.

• request_type (FunnelRequestType) – Widget request type.

datadog_api_client.v1.model.gcp_account module

class GCPAccount(arg: None)

class GCPAccount(arg: ModelComposed)

class GCPAccount(*args, **kwargs)

Bases: ModelNormal

Your Google Cloud Platform Account.

Parameters:

• auth_provider_x509_cert_url (str, optional) – Should be https://www.googleapis.com/oauth2/v1/certs.

• auth_uri (str, optional) – Should be https://accounts.google.com/o/oauth2/auth.

• automute (bool, optional) – Silence monitors for expected GCE instance shutdowns.

• client_email (str, optional) – Your email found in your JSON service account key.

• client_id (str, optional) – Your ID found in your JSON service account key.

• client_x509_cert_url (str, optional) – Should be https://www.googleapis.com/robot/v1/metadata/x509/$CLIENT_EMAIL where $CLIENT_EMAIL is the email found in your JSON service account key.

• cloud_run_revision_filters ([str], optional) – List of filters to limit the Cloud Run revisions that are pulled into Datadog by using tags. Only Cloud Run revision resources that apply to specified filters are imported into Datadog. Note: This field is deprecated. Instead, use monitored_resource_configs with type=cloud_run_revision Deprecated.

• errors ([str], optional) – An array of errors.

• host_filters (str, optional) – A comma-separated list of filters to limit the VM instances that are pulled into Datadog by using tags. Only VM instance resources that apply to specified filters are imported into Datadog. Note: This field is deprecated. Instead, use monitored_resource_configs with type=gce_instance Deprecated.

• is_cspm_enabled (bool, optional) – When enabled, Datadog will activate the Cloud Security Monitoring product for this service account. Note: This requires resource_collection_enabled to be set to true.

• is_resource_change_collection_enabled (bool, optional) – When enabled, Datadog scans for all resource change data in your Google Cloud environment.

• is_security_command_center_enabled (bool, optional) – When enabled, Datadog will attempt to collect Security Command Center Findings. Note: This requires additional permissions on the service account.

• monitored_resource_configs ([GCPMonitoredResourceConfig], optional) – Configurations for GCP monitored resources.

• private_key (str, optional) – Your private key name found in your JSON service account key.

• private_key_id (str, optional) – Your private key ID found in your JSON service account key.

• project_id (str, optional) – Your Google Cloud project ID found in your JSON service account key.

• resource_collection_enabled (bool, optional) – When enabled, Datadog scans for all resources in your GCP environment.

• token_uri (str, optional) – Should be https://accounts.google.com/o/oauth2/token.

• type (str, optional) – The value for service_account found in your JSON service account key.

datadog_api_client.v1.model.gcp_account_list_response module

class GCPAccountListResponse(arg: None)

class GCPAccountListResponse(arg: ModelComposed)

class GCPAccountListResponse(*args, **kwargs)

Bases: ModelSimple

Array of GCP account responses.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.gcp_monitored_resource_config module

class GCPMonitoredResourceConfig(arg: None)

class GCPMonitoredResourceConfig(arg: ModelComposed)

class GCPMonitoredResourceConfig(*args, **kwargs)

Bases: ModelNormal

Configuration for a GCP monitored resource.

Parameters:

• filters ([str], optional) – List of filters to limit the monitored resources that are pulled into Datadog by using tags. Only monitored resources that apply to specified filters are imported into Datadog.

• type (GCPMonitoredResourceConfigType, optional) – The GCP monitored resource type. Only a subset of resource types are supported.

datadog_api_client.v1.model.gcp_monitored_resource_config_type module

class GCPMonitoredResourceConfigType(arg: None)

class GCPMonitoredResourceConfigType(arg: ModelComposed)

class GCPMonitoredResourceConfigType(*args, **kwargs)

Bases: ModelSimple

The GCP monitored resource type. Only a subset of resource types are supported.

Parameters:

• value (str) – Must be one of [“cloud_function”, “cloud_run_revision”, “gce_instance”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.geomap_widget_definition module

class GeomapWidgetDefinition(arg: None)

class GeomapWidgetDefinition(arg: ModelComposed)

class GeomapWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

This visualization displays a series of values by country on a world map.

Parameters:

• custom_links ([WidgetCustomLink], optional) – A list of custom links.

• requests ([GeomapWidgetRequest]) –

  Array of one request object to display in the widget. The request must contain a group-by tag whose value is a country ISO code.

  See the Request JSON schema documentation for information about building the REQUEST_SCHEMA.

• style (GeomapWidgetDefinitionStyle) – The style to apply to the widget.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – The title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – The size of the title.

• type (GeomapWidgetDefinitionType) – Type of the geomap widget.

• view (GeomapWidgetDefinitionView) – The view of the world that the map should render.

datadog_api_client.v1.model.geomap_widget_definition_style module

class GeomapWidgetDefinitionStyle(arg: None)

class GeomapWidgetDefinitionStyle(arg: ModelComposed)

class GeomapWidgetDefinitionStyle(*args, **kwargs)

Bases: ModelNormal

The style to apply to the widget.

Parameters:

• palette (str) – The color palette to apply to the widget.

• palette_flip (bool) – Whether to flip the palette tones.

datadog_api_client.v1.model.geomap_widget_definition_type module

class GeomapWidgetDefinitionType(arg: None)

class GeomapWidgetDefinitionType(arg: ModelComposed)

class GeomapWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the geomap widget.

Parameters:

• value (str) – If omitted defaults to “geomap”. Must be one of [“geomap”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.geomap_widget_definition_view module

class GeomapWidgetDefinitionView(arg: None)

class GeomapWidgetDefinitionView(arg: ModelComposed)

class GeomapWidgetDefinitionView(*args, **kwargs)

Bases: ModelNormal

The view of the world that the map should render.

Parameters:

focus (str) – The 2-letter ISO code of a country to focus the map on. Or WORLD.

datadog_api_client.v1.model.geomap_widget_request module

class GeomapWidgetRequest(arg: None)

class GeomapWidgetRequest(arg: ModelComposed)

class GeomapWidgetRequest(*args, **kwargs)

Bases: ModelNormal

An updated geomap widget.

Parameters:

• columns ([ListStreamColumn], optional) – Widget columns.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• log_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – The widget metrics query.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• query (ListStreamQuery, optional) – Updated list stream widget.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• sort (WidgetSortBy, optional) – The controls for sorting the widget.

datadog_api_client.v1.model.graph_snapshot module

class GraphSnapshot(arg: None)

class GraphSnapshot(arg: ModelComposed)

class GraphSnapshot(*args, **kwargs)

Bases: ModelNormal

Object representing a graph snapshot.

Parameters:

• graph_def (str, optional) – A JSON document defining the graph. graph_def can be used instead of metric_query. The JSON document uses the grammar defined here and should be formatted to a single line then URL encoded.

• metric_query (str, optional) – The metric query. One of metric_query or graph_def is required.

• snapshot_url (str, optional) – URL of your graph snapshot.

datadog_api_client.v1.model.group_type module

class GroupType(arg: None)

class GroupType(arg: ModelComposed)

class GroupType(*args, **kwargs)

Bases: ModelSimple

Set the sort type to group.

Parameters:

• value (str) – If omitted defaults to “group”. Must be one of [“group”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.group_widget_definition module

class GroupWidgetDefinition(arg: None)

class GroupWidgetDefinition(arg: ModelComposed)

class GroupWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The groups widget allows you to keep similar graphs together on your timeboard. Each group has a custom header, can hold one to many graphs, and is collapsible.

Parameters:

• background_color (str, optional) – Background color of the group title.

• banner_img (str, optional) – URL of image to display as a banner for the group.

• layout_type (WidgetLayoutType) – Layout type of the group.

• show_title (bool, optional) – Whether to show the title or not.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• type (GroupWidgetDefinitionType) – Type of the group widget.

• widgets ([Widget]) – List of widget groups.

datadog_api_client.v1.model.group_widget_definition_type module

class GroupWidgetDefinitionType(arg: None)

class GroupWidgetDefinitionType(arg: ModelComposed)

class GroupWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the group widget.

Parameters:

• value (str) – If omitted defaults to “group”. Must be one of [“group”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.heat_map_widget_definition module

class HeatMapWidgetDefinition(arg: None)

class HeatMapWidgetDefinition(arg: ModelComposed)

class HeatMapWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The heat map visualization shows metrics aggregated across many tags, such as hosts. The more hosts that have a particular value, the darker that square is.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• events ([WidgetEvent], optional) – List of widget events.

• legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.

• requests ([HeatMapWidgetRequest]) – List of widget types.

• show_legend (bool, optional) – Whether or not to display the legend on this widget.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (HeatMapWidgetDefinitionType) – Type of the heat map widget.

• yaxis (WidgetAxis, optional) – Axis controls for the widget.

datadog_api_client.v1.model.heat_map_widget_definition_type module

class HeatMapWidgetDefinitionType(arg: None)

class HeatMapWidgetDefinitionType(arg: ModelComposed)

class HeatMapWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the heat map widget.

Parameters:

• value (str) – If omitted defaults to “heatmap”. Must be one of [“heatmap”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.heat_map_widget_request module

class HeatMapWidgetRequest(arg: None)

class HeatMapWidgetRequest(arg: ModelComposed)

class HeatMapWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated heat map widget.

Parameters:

• apm_query (LogQueryDefinition, optional) – The log query.

• event_query (EventQueryDefinition, optional) – The event query.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Widget query.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• style (WidgetStyle, optional) – Widget style definition.

datadog_api_client.v1.model.host module

class Host(arg: None)

class Host(arg: ModelComposed)

class Host(*args, **kwargs)

Bases: ModelNormal

Object representing a host.

Parameters:

• aliases ([str], optional) – Host aliases collected by Datadog.

• apps ([str], optional) – The Datadog integrations reporting metrics for the host.

• aws_name (str, optional) – AWS name of your host.

• host_name (str, optional) – The host name.

• id (int, optional) – The host ID.

• is_muted (bool, optional) – If a host is muted or unmuted.

• last_reported_time (int, optional) – Last time the host reported a metric data point.

• meta (HostMeta, optional) – Metadata associated with your host.

• metrics (HostMetrics, optional) – Host Metrics collected.

• mute_timeout (int, none_type, optional) – Timeout of the mute applied to your host.

• name (str, optional) – The host name.

• sources ([str], optional) – Source or cloud provider associated with your host.

• tags_by_source ({str: ([str],)}, optional) – List of tags for each source (AWS, Datadog Agent, Chef..).

• up (bool, optional) – Displays UP when the expected metrics are received and displays ??? if no metrics are received.

datadog_api_client.v1.model.host_list_response module

class HostListResponse(arg: None)

class HostListResponse(arg: ModelComposed)

class HostListResponse(*args, **kwargs)

Bases: ModelNormal

Response with Host information from Datadog.

Parameters:

• host_list ([Host], optional) – Array of hosts.

• total_matching (int, optional) – Number of host matching the query.

• total_returned (int, optional) – Number of host returned.

datadog_api_client.v1.model.host_map_request module

class HostMapRequest(arg: None)

class HostMapRequest(arg: ModelComposed)

class HostMapRequest(*args, **kwargs)

Bases: ModelNormal

Updated host map.

Parameters:

• apm_query (LogQueryDefinition, optional) – The log query.

• event_query (LogQueryDefinition, optional) – The log query.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Query definition.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

datadog_api_client.v1.model.host_map_widget_definition module

class HostMapWidgetDefinition(arg: None)

class HostMapWidgetDefinition(arg: ModelComposed)

class HostMapWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The host map widget graphs any metric across your hosts using the same visualization available from the main Host Map page.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• group ([str], optional) – List of tag prefixes to group by.

• no_group_hosts (bool, optional) – Whether to show the hosts that don’t fit in a group.

• no_metric_hosts (bool, optional) – Whether to show the hosts with no metrics.

• node_type (WidgetNodeType, optional) – Which type of node to use in the map.

• notes (str, optional) – Notes on the title.

• requests (HostMapWidgetDefinitionRequests) – List of definitions.

• scope ([str], optional) – List of tags used to filter the map.

• style (HostMapWidgetDefinitionStyle, optional) – The style to apply to the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (HostMapWidgetDefinitionType) – Type of the host map widget.

datadog_api_client.v1.model.host_map_widget_definition_requests module

class HostMapWidgetDefinitionRequests(arg: None)

class HostMapWidgetDefinitionRequests(arg: ModelComposed)

class HostMapWidgetDefinitionRequests(*args, **kwargs)

Bases: ModelNormal

List of definitions.

Parameters:

• fill (HostMapRequest, optional) – Updated host map.

• size (HostMapRequest, optional) – Updated host map.

datadog_api_client.v1.model.host_map_widget_definition_style module

class HostMapWidgetDefinitionStyle(arg: None)

class HostMapWidgetDefinitionStyle(arg: ModelComposed)

class HostMapWidgetDefinitionStyle(*args, **kwargs)

Bases: ModelNormal

The style to apply to the widget.

Parameters:

• fill_max (str, optional) – Max value to use to color the map.

• fill_min (str, optional) – Min value to use to color the map.

• palette (str, optional) – Color palette to apply to the widget.

• palette_flip (bool, optional) – Whether to flip the palette tones.

datadog_api_client.v1.model.host_map_widget_definition_type module

class HostMapWidgetDefinitionType(arg: None)

class HostMapWidgetDefinitionType(arg: ModelComposed)

class HostMapWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the host map widget.

Parameters:

• value (str) – If omitted defaults to “hostmap”. Must be one of [“hostmap”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.host_meta module

class HostMeta(arg: None)

class HostMeta(arg: ModelComposed)

class HostMeta(*args, **kwargs)

Bases: ModelNormal

Metadata associated with your host.

Parameters:

• agent_checks ([AgentCheck], optional) – A list of Agent checks running on the host.

• agent_version (str, optional) – The Datadog Agent version.

• cpu_cores (int, optional) – The number of cores.

• fbsd_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – An array of Mac versions.

• gohai (str, optional) – JSON string containing system information.

• install_method (HostMetaInstallMethod, optional) – Agent install method.

• mac_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – An array of Mac versions.

• machine (str, optional) – The machine architecture.

• nix_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – Array of Unix versions.

• platform (str, optional) – The OS platform.

• processor (str, optional) – The processor.

• python_v (str, optional) – The Python version.

• socket_fqdn (str, optional) – The socket fqdn.

• socket_hostname (str, optional) – The socket hostname.

• win_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – An array of Windows versions.

datadog_api_client.v1.model.host_meta_install_method module

class HostMetaInstallMethod(arg: None)

class HostMetaInstallMethod(arg: ModelComposed)

class HostMetaInstallMethod(*args, **kwargs)

Bases: ModelNormal

Agent install method.

Parameters:

• installer_version (str, optional) – The installer version.

• tool (str, optional) – Tool used to install the agent.

• tool_version (str, optional) – The tool version.

datadog_api_client.v1.model.host_metrics module

class HostMetrics(arg: None)

class HostMetrics(arg: ModelComposed)

class HostMetrics(*args, **kwargs)

Bases: ModelNormal

Host Metrics collected.

Parameters:

• cpu (float, optional) – The percent of CPU used (everything but idle).

• iowait (float, optional) – The percent of CPU spent waiting on the IO (not reported for all platforms).

• load (float, optional) – The system load over the last 15 minutes.

datadog_api_client.v1.model.host_mute_response module

class HostMuteResponse(arg: None)

class HostMuteResponse(arg: ModelComposed)

class HostMuteResponse(*args, **kwargs)

Bases: ModelNormal

Response with the list of muted host for your organization.

Parameters:

• action (str, optional) – Action applied to the hosts.

• end (int, optional) – POSIX timestamp in seconds when the host is unmuted.

• hostname (str, optional) – The host name.

• message (str, optional) – Message associated with the mute.

datadog_api_client.v1.model.host_mute_settings module

class HostMuteSettings(arg: None)

class HostMuteSettings(arg: ModelComposed)

class HostMuteSettings(*args, **kwargs)

Bases: ModelNormal

Combination of settings to mute a host.

Parameters:

• end (int, optional) – POSIX timestamp in seconds when the host is unmuted. If omitted, the host remains muted until explicitly unmuted.

• message (str, optional) – Message to associate with the muting of this host.

• override (bool, optional) – If true and the host is already muted, replaces existing host mute settings.

datadog_api_client.v1.model.host_tags module

class HostTags(arg: None)

class HostTags(arg: ModelComposed)

class HostTags(*args, **kwargs)

Bases: ModelNormal

Set of tags to associate with your host.

Parameters:

• host (str, optional) – Your host name.

• tags ([str], optional) – A list of tags to apply to the host.

datadog_api_client.v1.model.host_totals module

class HostTotals(arg: None)

class HostTotals(arg: ModelComposed)

class HostTotals(*args, **kwargs)

Bases: ModelNormal

Total number of host currently monitored by Datadog.

Parameters:

• total_active (int, optional) – Total number of active host (UP and ???) reporting to Datadog.

• total_up (int, optional) – Number of host that are UP and reporting to Datadog.

datadog_api_client.v1.model.hourly_usage_attribution_body module

class HourlyUsageAttributionBody(arg: None)

class HourlyUsageAttributionBody(arg: ModelComposed)

class HourlyUsageAttributionBody(*args, **kwargs)

Bases: ModelNormal

The usage for one set of tags for one hour.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The name of the organization.

• public_id (str, optional) – The organization public ID.

• region (str, optional) – The region of the Datadog instance that the organization belongs to.

• tag_config_source (str, optional) – The source of the usage attribution tag configuration and the selected tags in the format of <source_org_name>:::<selected tag 1>///<selected tag 2>///<selected tag 3>.

• tags (UsageAttributionTagNames, none_type, optional) –

  Tag keys and values.

  A null value here means that the requested tag breakdown cannot be applied because it does not match the tags configured for usage attribution. In this scenario the API returns the total usage, not broken down by tags.

• total_usage_sum (float, optional) – Total product usage for the given tags within the hour.

• updated_at (str, optional) – Shows the most recent hour in the current month for all organizations where usages are calculated.

• usage_type (HourlyUsageAttributionUsageType, optional) – Supported products for hourly usage attribution requests. The following values have been deprecated : estimated_indexed_spans_usage , estimated_ingested_spans_usage.

datadog_api_client.v1.model.hourly_usage_attribution_metadata module

class HourlyUsageAttributionMetadata(arg: None)

class HourlyUsageAttributionMetadata(arg: ModelComposed)

class HourlyUsageAttributionMetadata(*args, **kwargs)

Bases: ModelNormal

The object containing document metadata.

Parameters:

pagination (HourlyUsageAttributionPagination, optional) – The metadata for the current pagination.

datadog_api_client.v1.model.hourly_usage_attribution_pagination module

class HourlyUsageAttributionPagination(arg: None)

class HourlyUsageAttributionPagination(arg: ModelComposed)

class HourlyUsageAttributionPagination(*args, **kwargs)

Bases: ModelNormal

The metadata for the current pagination.

Parameters:

next_record_id (str, none_type, optional) – The cursor to get the next results (if any). To make the next request, use the same parameters and add next_record_id.

datadog_api_client.v1.model.hourly_usage_attribution_response module

class HourlyUsageAttributionResponse(arg: None)

class HourlyUsageAttributionResponse(arg: ModelComposed)

class HourlyUsageAttributionResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the hourly usage attribution by tag(s).

Parameters:

• metadata (HourlyUsageAttributionMetadata, optional) – The object containing document metadata.

• usage ([HourlyUsageAttributionBody], optional) – Get the hourly usage attribution by tag(s).

datadog_api_client.v1.model.hourly_usage_attribution_usage_type module

class HourlyUsageAttributionUsageType(arg: None)

class HourlyUsageAttributionUsageType(arg: ModelComposed)

class HourlyUsageAttributionUsageType(*args, **kwargs)

Bases: ModelSimple

Supported products for hourly usage attribution requests.

The following values have been deprecated: estimated_indexed_spans_usage, estimated_ingested_spans_usage.

Parameters:

• value (str) – Must be one of [“api_usage”, “apm_fargate_usage”, “apm_host_usage”, “apm_usm_usage”, “appsec_fargate_usage”, “appsec_usage”, “asm_serverless_traced_invocations_usage”, “asm_serverless_traced_invocations_percentage”, “browser_usage”, “ci_pipeline_indexed_spans_usage”, “ci_test_indexed_spans_usage”, “ci_visibility_itr_usage”, “cloud_siem_usage”, “code_security_host_usage”, “container_excl_agent_usage”, “container_usage”, “cspm_containers_usage”, “cspm_hosts_usage”, “custom_event_usage”, “custom_ingested_timeseries_usage”, “custom_timeseries_usage”, “cws_containers_usage”, “cws_fargate_task_usage”, “cws_hosts_usage”, “data_jobs_monitoring_usage”, “data_stream_monitoring_usage”, “dbm_hosts_usage”, “dbm_queries_usage”, “error_tracking_usage”, “error_tracking_percentage”, “estimated_indexed_spans_usage”, “estimated_ingested_spans_usage”, “fargate_usage”, “functions_usage”, “incident_management_monthly_active_users_usage”, “indexed_spans_usage”, “infra_host_usage”, “ingested_logs_bytes_usage”, “ingested_spans_bytes_usage”, “invocations_usage”, “lambda_traced_invocations_usage”, “llm_observability_usage”, “logs_indexed_15day_usage”, “logs_indexed_180day_usage”, “logs_indexed_1day_usage”, “logs_indexed_30day_usage”, “logs_indexed_360day_usage”, “logs_indexed_3day_usage”, “logs_indexed_45day_usage”, “logs_indexed_60day_usage”, “logs_indexed_7day_usage”, “logs_indexed_90day_usage”, “logs_indexed_custom_retention_usage”, “mobile_app_testing_usage”, “ndm_netflow_usage”, “npm_host_usage”, “network_device_wireless_usage”, “obs_pipeline_bytes_usage”, “obs_pipelines_vcpu_usage”, “online_archive_usage”, “product_analytics_session_usage”, “profiled_container_usage”, “profiled_fargate_usage”, “profiled_host_usage”, “published_app”, “rum_browser_mobile_sessions_usage”, “rum_ingested_usage”, “rum_investigate_usage”, “rum_replay_sessions_usage”, “rum_session_replay_add_on_usage”, “sca_fargate_usage”, “sds_scanned_bytes_usage”, “serverless_apps_usage”, “siem_analyzed_logs_add_on_usage”, “siem_ingested_bytes_usage”, “snmp_usage”, “universal_service_monitoring_usage”, “vuln_management_hosts_usage”, “workflow_executions_usage”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.http_log module

class HTTPLog(arg: None)

class HTTPLog(arg: ModelComposed)

class HTTPLog(*args, **kwargs)

Bases: ModelSimple

Structured log message.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.http_log_error module

class HTTPLogError(arg: None)

class HTTPLogError(arg: ModelComposed)

class HTTPLogError(*args, **kwargs)

Bases: ModelNormal

Invalid query performed.

Parameters:

• code (int) – Error code.

• message (str) – Error message.

datadog_api_client.v1.model.http_log_item module

class HTTPLogItem(arg: None)

class HTTPLogItem(arg: ModelComposed)

class HTTPLogItem(*args, **kwargs)

Bases: ModelNormal

Logs that are sent over HTTP.

Parameters:

• ddsource (str, optional) – The integration name associated with your log: the technology from which the log originated. When it matches an integration name, Datadog automatically installs the corresponding parsers and facets. See reserved attributes.

• ddtags (str, optional) – Tags associated with your logs.

• hostname (str, optional) – The name of the originating host of the log.

• message (str) – The message reserved attribute of your log. By default, Datadog ingests the value of the message attribute as the body of the log entry. That value is then highlighted and displayed in the Logstream, where it is indexed for full text search.

• service (str, optional) –

  The name of the application or service generating the log events. It is used to switch from Logs to APM, so make sure you define the same value when you use both products. See reserved attributes.

datadog_api_client.v1.model.i_frame_widget_definition module

class IFrameWidgetDefinition(arg: None)

class IFrameWidgetDefinition(arg: ModelComposed)

class IFrameWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The iframe widget allows you to embed a portion of any other web page on your dashboard. Only available on FREE layout dashboards.

Parameters:

• type (IFrameWidgetDefinitionType) – Type of the iframe widget.

• url (str) – URL of the iframe.

datadog_api_client.v1.model.i_frame_widget_definition_type module

class IFrameWidgetDefinitionType(arg: None)

class IFrameWidgetDefinitionType(arg: ModelComposed)

class IFrameWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the iframe widget.

Parameters:

• value (str) – If omitted defaults to “iframe”. Must be one of [“iframe”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.idp_form_data module

class IdpFormData(arg: None)

class IdpFormData(arg: ModelComposed)

class IdpFormData(*args, **kwargs)

Bases: ModelNormal

Object describing the IdP configuration.

Parameters:

idp_file (file_type) – The path to the XML metadata file you wish to upload.

datadog_api_client.v1.model.idp_response module

class IdpResponse(arg: None)

class IdpResponse(arg: ModelComposed)

class IdpResponse(*args, **kwargs)

Bases: ModelNormal

The IdP response object.

Parameters:

message (str) – Identity provider response.

datadog_api_client.v1.model.image_widget_definition module

class ImageWidgetDefinition(arg: None)

class ImageWidgetDefinition(arg: ModelComposed)

class ImageWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The image widget allows you to embed an image on your dashboard. An image can be a PNG, JPG, or animated GIF. Only available on FREE layout dashboards.

Parameters:

• has_background (bool, optional) – Whether to display a background or not.

• has_border (bool, optional) – Whether to display a border or not.

• horizontal_align (WidgetHorizontalAlign, optional) – Horizontal alignment.

• margin (WidgetMargin, optional) – Size of the margins around the image. Note : small and large values are deprecated.

• sizing (WidgetImageSizing, optional) – How to size the image on the widget. The values are based on the image object-fit CSS properties. Note : zoom , fit and center values are deprecated.

• type (ImageWidgetDefinitionType) – Type of the image widget.

• url (str) – URL of the image.

• url_dark_theme (str, optional) – URL of the image in dark mode.

• vertical_align (WidgetVerticalAlign, optional) – Vertical alignment.

datadog_api_client.v1.model.image_widget_definition_type module

class ImageWidgetDefinitionType(arg: None)

class ImageWidgetDefinitionType(arg: ModelComposed)

class ImageWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the image widget.

Parameters:

• value (str) – If omitted defaults to “image”. Must be one of [“image”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.intake_payload_accepted module

class IntakePayloadAccepted(arg: None)

class IntakePayloadAccepted(arg: ModelComposed)

class IntakePayloadAccepted(*args, **kwargs)

Bases: ModelNormal

The payload accepted for intake.

Parameters:

status (str, optional) – The status of the intake payload.

datadog_api_client.v1.model.ip_prefixes_agents module

class IPPrefixesAgents(arg: None)

class IPPrefixesAgents(arg: ModelComposed)

class IPPrefixesAgents(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Agent endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_api module

class IPPrefixesAPI(arg: None)

class IPPrefixesAPI(arg: ModelComposed)

class IPPrefixesAPI(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the API endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_apm module

class IPPrefixesAPM(arg: None)

class IPPrefixesAPM(arg: ModelComposed)

class IPPrefixesAPM(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the APM endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_global module

class IPPrefixesGlobal(arg: None)

class IPPrefixesGlobal(arg: ModelComposed)

class IPPrefixesGlobal(*args, **kwargs)

Bases: ModelNormal

Available prefix information for all Datadog endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_logs module

class IPPrefixesLogs(arg: None)

class IPPrefixesLogs(arg: ModelComposed)

class IPPrefixesLogs(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Logs endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_orchestrator module

class IPPrefixesOrchestrator(arg: None)

class IPPrefixesOrchestrator(arg: ModelComposed)

class IPPrefixesOrchestrator(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Orchestrator endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_process module

class IPPrefixesProcess(arg: None)

class IPPrefixesProcess(arg: ModelComposed)

class IPPrefixesProcess(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Process endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_remote_configuration module

class IPPrefixesRemoteConfiguration(arg: None)

class IPPrefixesRemoteConfiguration(arg: ModelComposed)

class IPPrefixesRemoteConfiguration(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Remote Configuration endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_synthetics module

class IPPrefixesSynthetics(arg: None)

class IPPrefixesSynthetics(arg: ModelComposed)

class IPPrefixesSynthetics(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Synthetics endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv4_by_location ({str: ([str],)}, optional) – List of IPv4 prefixes by location.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

• prefixes_ipv6_by_location ({str: ([str],)}, optional) – List of IPv6 prefixes by location.

datadog_api_client.v1.model.ip_prefixes_synthetics_private_locations module

class IPPrefixesSyntheticsPrivateLocations(arg: None)

class IPPrefixesSyntheticsPrivateLocations(arg: ModelComposed)

class IPPrefixesSyntheticsPrivateLocations(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Synthetics Private Locations endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_prefixes_webhooks module

class IPPrefixesWebhooks(arg: None)

class IPPrefixesWebhooks(arg: ModelComposed)

class IPPrefixesWebhooks(*args, **kwargs)

Bases: ModelNormal

Available prefix information for the Webhook endpoints.

Parameters:

• prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.

• prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

datadog_api_client.v1.model.ip_ranges module

class IPRanges(arg: None)

class IPRanges(arg: ModelComposed)

class IPRanges(*args, **kwargs)

Bases: ModelNormal

IP ranges.

Parameters:

• agents (IPPrefixesAgents, optional) – Available prefix information for the Agent endpoints.

• api (IPPrefixesAPI, optional) – Available prefix information for the API endpoints.

• apm (IPPrefixesAPM, optional) – Available prefix information for the APM endpoints.

• _global (IPPrefixesGlobal, optional) – Available prefix information for all Datadog endpoints.

• logs (IPPrefixesLogs, optional) – Available prefix information for the Logs endpoints.

• modified (str, optional) – Date when last updated, in the form YYYY-MM-DD-hh-mm-ss.

• orchestrator (IPPrefixesOrchestrator, optional) – Available prefix information for the Orchestrator endpoints.

• process (IPPrefixesProcess, optional) – Available prefix information for the Process endpoints.

• remote_configuration (IPPrefixesRemoteConfiguration, optional) – Available prefix information for the Remote Configuration endpoints.

• synthetics (IPPrefixesSynthetics, optional) – Available prefix information for the Synthetics endpoints.

• synthetics_private_locations (IPPrefixesSyntheticsPrivateLocations, optional) – Available prefix information for the Synthetics Private Locations endpoints.

• version (int, optional) – Version of the IP list.

• webhooks (IPPrefixesWebhooks, optional) – Available prefix information for the Webhook endpoints.

datadog_api_client.v1.model.list_stream_column module

class ListStreamColumn(arg: None)

class ListStreamColumn(arg: ModelComposed)

class ListStreamColumn(*args, **kwargs)

Bases: ModelNormal

Widget column.

Parameters:

• field (str) – Widget column field.

• width (ListStreamColumnWidth) – Widget column width.

datadog_api_client.v1.model.list_stream_column_width module

class ListStreamColumnWidth(arg: None)

class ListStreamColumnWidth(arg: ModelComposed)

class ListStreamColumnWidth(*args, **kwargs)

Bases: ModelSimple

Widget column width.

Parameters:

• value (str) – Must be one of [“auto”, “compact”, “full”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.list_stream_compute_aggregation module

class ListStreamComputeAggregation(arg: None)

class ListStreamComputeAggregation(arg: ModelComposed)

class ListStreamComputeAggregation(*args, **kwargs)

Bases: ModelSimple

Aggregation value.

Parameters:

• value (str) – Must be one of [“count”, “cardinality”, “median”, “pc75”, “pc90”, “pc95”, “pc98”, “pc99”, “sum”, “min”, “max”, “avg”, “earliest”, “latest”, “most_frequent”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.list_stream_compute_items module

class ListStreamComputeItems(arg: None)

class ListStreamComputeItems(arg: ModelComposed)

class ListStreamComputeItems(*args, **kwargs)

Bases: ModelNormal

List of facets and aggregations which to compute.

Parameters:

• aggregation (ListStreamComputeAggregation) – Aggregation value.

• facet (str, optional) – Facet name.

datadog_api_client.v1.model.list_stream_group_by_items module

class ListStreamGroupByItems(arg: None)

class ListStreamGroupByItems(arg: ModelComposed)

class ListStreamGroupByItems(*args, **kwargs)

Bases: ModelNormal

List of facets on which to group.

Parameters:

facet (str) – Facet name.

datadog_api_client.v1.model.list_stream_query module

class ListStreamQuery(arg: None)

class ListStreamQuery(arg: ModelComposed)

class ListStreamQuery(*args, **kwargs)

Bases: ModelNormal

Updated list stream widget.

Parameters:

• clustering_pattern_field_path (str, optional) – Specifies the field for logs pattern clustering. Usable only with logs_pattern_stream.

• compute ([ListStreamComputeItems], optional) – Compute configuration for the List Stream Widget. Compute can be used only with the logs_transaction_stream (from 1 to 5 items) list stream source.

• data_source (ListStreamSource) – Source from which to query items to display in the stream.

• event_size (WidgetEventSize, optional) – Size to use to display an event.

• group_by ([ListStreamGroupByItems], optional) – Group by configuration for the List Stream Widget. Group by can be used only with logs_pattern_stream (up to 4 items) or logs_transaction_stream (one group by item is required) list stream source.

• indexes ([str], optional) – List of indexes.

• query_string (str) – Widget query.

• sort (WidgetFieldSort, optional) – Which column and order to sort by

• storage (str, optional) – Option for storage location. Feature in Private Beta.

datadog_api_client.v1.model.list_stream_response_format module

class ListStreamResponseFormat(arg: None)

class ListStreamResponseFormat(arg: ModelComposed)

class ListStreamResponseFormat(*args, **kwargs)

Bases: ModelSimple

Widget response format.

Parameters:

• value (str) – If omitted defaults to “event_list”. Must be one of [“event_list”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.list_stream_source module

class ListStreamSource(arg: None)

class ListStreamSource(arg: ModelComposed)

class ListStreamSource(*args, **kwargs)

Bases: ModelSimple

Source from which to query items to display in the stream.

Parameters:

• value (str) – If omitted defaults to “apm_issue_stream”. Must be one of [“logs_stream”, “audit_stream”, “ci_pipeline_stream”, “ci_test_stream”, “rum_issue_stream”, “apm_issue_stream”, “trace_stream”, “logs_issue_stream”, “logs_pattern_stream”, “logs_transaction_stream”, “event_stream”, “rum_stream”, “llm_observability_stream”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.list_stream_widget_definition module

class ListStreamWidgetDefinition(arg: None)

class ListStreamWidgetDefinition(arg: ModelComposed)

class ListStreamWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The list stream visualization displays a table of recent events in your application that match a search criteria using user-defined columns.

Parameters:

• legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.

• requests ([ListStreamWidgetRequest]) – Request payload used to query items.

• show_legend (bool, optional) – Whether or not to display the legend on this widget.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (ListStreamWidgetDefinitionType) – Type of the list stream widget.

datadog_api_client.v1.model.list_stream_widget_definition_type module

class ListStreamWidgetDefinitionType(arg: None)

class ListStreamWidgetDefinitionType(arg: ModelComposed)

class ListStreamWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the list stream widget.

Parameters:

• value (str) – If omitted defaults to “list_stream”. Must be one of [“list_stream”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.list_stream_widget_request module

class ListStreamWidgetRequest(arg: None)

class ListStreamWidgetRequest(arg: ModelComposed)

class ListStreamWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated list stream widget.

Parameters:

• columns ([ListStreamColumn]) – Widget columns.

• query (ListStreamQuery) – Updated list stream widget.

• response_format (ListStreamResponseFormat) – Widget response format.

datadog_api_client.v1.model.log module

class Log(arg: None)

class Log(arg: ModelComposed)

class Log(*args, **kwargs)

Bases: ModelNormal

Object describing a log after being processed and stored by Datadog.

Parameters:

• content (LogContent, optional) – JSON object containing all log attributes and their associated values.

• id (str, optional) – ID of the Log.

datadog_api_client.v1.model.log_content module

class LogContent(arg: None)

class LogContent(arg: ModelComposed)

class LogContent(*args, **kwargs)

Bases: ModelNormal

JSON object containing all log attributes and their associated values.

Parameters:

• attributes ({str: (bool, date, datetime, dict, float, int, list, str, UUID, none_type,)}, optional) – JSON object of attributes from your log.

• host (str, optional) – Name of the machine from where the logs are being sent.

• message (str, optional) –

  The message reserved attribute of your log. By default, Datadog ingests the value of the message attribute as the body of the log entry. That value is then highlighted and displayed in the Logstream, where it is indexed for full text search.

• service (str, optional) – The name of the application or service generating the log events. It is used to switch from Logs to APM, so make sure you define the same value when you use both products.

• tags ([str], optional) – Array of tags associated with your log.

• timestamp (datetime, optional) – Timestamp of your log.

datadog_api_client.v1.model.log_query_definition module

class LogQueryDefinition(arg: None)

class LogQueryDefinition(arg: ModelComposed)

class LogQueryDefinition(*args, **kwargs)

Bases: ModelNormal

The log query.

Parameters:

• compute (LogsQueryCompute, optional) – Define computation for a log query.

• group_by ([LogQueryDefinitionGroupBy], optional) – List of tag prefixes to group by in the case of a cluster check.

• index (str, optional) – A coma separated-list of index names. Use “*” query all indexes at once. Multiple Indexes

• multi_compute ([LogsQueryCompute], optional) – This field is mutually exclusive with compute.

• search (LogQueryDefinitionSearch, optional) – The query being made on the logs.

datadog_api_client.v1.model.log_query_definition_group_by module

class LogQueryDefinitionGroupBy(arg: None)

class LogQueryDefinitionGroupBy(arg: ModelComposed)

class LogQueryDefinitionGroupBy(*args, **kwargs)

Bases: ModelNormal

Defined items in the group.

Parameters:

• facet (str) – Facet name.

• limit (int, optional) – Maximum number of items in the group.

• sort (LogQueryDefinitionGroupBySort, optional) – Define a sorting method.

datadog_api_client.v1.model.log_query_definition_group_by_sort module

class LogQueryDefinitionGroupBySort(arg: None)

class LogQueryDefinitionGroupBySort(arg: ModelComposed)

class LogQueryDefinitionGroupBySort(*args, **kwargs)

Bases: ModelNormal

Define a sorting method.

Parameters:

• aggregation (str) – The aggregation method.

• facet (str, optional) – Facet name.

• order (WidgetSort) – Widget sorting methods.

datadog_api_client.v1.model.log_query_definition_search module

class LogQueryDefinitionSearch(arg: None)

class LogQueryDefinitionSearch(arg: ModelComposed)

class LogQueryDefinitionSearch(*args, **kwargs)

Bases: ModelNormal

The query being made on the logs.

Parameters:

query (str) – Search value to apply.

datadog_api_client.v1.model.log_stream_widget_definition module

class LogStreamWidgetDefinition(arg: None)

class LogStreamWidgetDefinition(arg: ModelComposed)

class LogStreamWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The Log Stream displays a log flow matching the defined query. Only available on FREE layout dashboards.

Parameters:

• columns ([str], optional) – Which columns to display on the widget.

• indexes ([str], optional) – An array of index names to query in the stream. Use [] to query all indexes at once.

• logset (str, optional) – ID of the log set to use. Deprecated.

• message_display (WidgetMessageDisplay, optional) – Amount of log lines to display

• query (str, optional) – Query to filter the log stream with.

• show_date_column (bool, optional) – Whether to show the date column or not

• show_message_column (bool, optional) – Whether to show the message column or not

• sort (WidgetFieldSort, optional) – Which column and order to sort by

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (LogStreamWidgetDefinitionType) – Type of the log stream widget.

datadog_api_client.v1.model.log_stream_widget_definition_type module

class LogStreamWidgetDefinitionType(arg: None)

class LogStreamWidgetDefinitionType(arg: ModelComposed)

class LogStreamWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the log stream widget.

Parameters:

• value (str) – If omitted defaults to “log_stream”. Must be one of [“log_stream”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_api_error module

class LogsAPIError(arg: None)

class LogsAPIError(arg: ModelComposed)

class LogsAPIError(*args, **kwargs)

Bases: ModelNormal

Error returned by the Logs API

Parameters:

• code (str, optional) – Code identifying the error

• details ([LogsAPIError], optional) – Additional error details

• message (str, optional) – Error message

datadog_api_client.v1.model.logs_api_error_response module

class LogsAPIErrorResponse(arg: None)

class LogsAPIErrorResponse(arg: ModelComposed)

class LogsAPIErrorResponse(*args, **kwargs)

Bases: ModelNormal

Response returned by the Logs API when errors occur.

Parameters:

error (LogsAPIError, optional) – Error returned by the Logs API

datadog_api_client.v1.model.logs_api_limit_reached_response module

class LogsAPILimitReachedResponse(arg: None)

class LogsAPILimitReachedResponse(arg: ModelComposed)

class LogsAPILimitReachedResponse(*args, **kwargs)

Bases: ModelNormal

Response returned by the Logs API when the max limit has been reached.

Parameters:

error (LogsAPIError, optional) – Error returned by the Logs API

datadog_api_client.v1.model.logs_arithmetic_processor module

class LogsArithmeticProcessor(arg: None)

class LogsArithmeticProcessor(arg: ModelComposed)

class LogsArithmeticProcessor(*args, **kwargs)

Bases: ModelNormal

Use the Arithmetic Processor to add a new attribute (without spaces or special characters in the new attribute name) to a log with the result of the provided formula. This enables you to remap different time attributes with different units into a single attribute, or to compute operations on attributes within the same log.

The formula can use parentheses and the basic arithmetic operators - , + , * , /.

By default, the calculation is skipped if an attribute is missing. Select “Replace missing attribute by 0” to automatically populate missing attribute values with 0 to ensure that the calculation is done. An attribute is missing if it is not found in the log attributes, or if it cannot be converted to a number.

Notes :

• The operator - needs to be space split in the formula as it can also be contained in attribute names.

• If the target attribute already exists, it is overwritten by the result of the formula.

• Results are rounded up to the 9th decimal. For example, if the result of the formula is 0.1234567891 , the actual value stored for the attribute is 0.123456789.

• If you need to scale a unit of measure, see Scale Filter.

Parameters:

• expression (str) – Arithmetic operation between one or more log attributes.

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• is_replace_missing (bool, optional) – If true , it replaces all missing attributes of expression by 0 , false skip the operation if an attribute is missing.

• name (str, optional) – Name of the processor.

• target (str) – Name of the attribute that contains the result of the arithmetic operation.

• type (LogsArithmeticProcessorType) – Type of logs arithmetic processor.

datadog_api_client.v1.model.logs_arithmetic_processor_type module

class LogsArithmeticProcessorType(arg: None)

class LogsArithmeticProcessorType(arg: ModelComposed)

class LogsArithmeticProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs arithmetic processor.

Parameters:

• value (str) – If omitted defaults to “arithmetic-processor”. Must be one of [“arithmetic-processor”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_array_processor module

class LogsArrayProcessor(arg: None)

class LogsArrayProcessor(arg: ModelComposed)

class LogsArrayProcessor(*args, **kwargs)

Bases: ModelNormal

A processor for extracting, aggregating, or transforming values from JSON arrays within your logs. Supported operations are:

• Select value from matching element

• Compute array length

• Append a value to an array

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• operation (LogsArrayProcessorOperation) – Configuration of the array processor operation to perform.

• type (LogsArrayProcessorType) – Type of logs array processor.

datadog_api_client.v1.model.logs_array_processor_operation module

class LogsArrayProcessorOperation(arg: None)

class LogsArrayProcessorOperation(arg: ModelComposed)

class LogsArrayProcessorOperation(*args, **kwargs)

Bases: ModelComposed

Configuration of the array processor operation to perform.

Parameters:

• preserve_source (bool, optional) – Remove or preserve the remapped source element.

• source (str) – Attribute path containing the value to append.

• target (str) – Attribute path of the array to append to.

• type (LogsArrayProcessorOperationAppendType) – Operation type.

• filter (str) – Filter condition expressed as key:value used to find the matching element.

• value_to_extract (str) – Key of the value to extract from the matching element.

datadog_api_client.v1.model.logs_array_processor_operation_append module

class LogsArrayProcessorOperationAppend(arg: None)

class LogsArrayProcessorOperationAppend(arg: ModelComposed)

class LogsArrayProcessorOperationAppend(*args, **kwargs)

Bases: ModelNormal

Operation that appends a value to a target array attribute.

Parameters:

• preserve_source (bool, optional) – Remove or preserve the remapped source element.

• source (str) – Attribute path containing the value to append.

• target (str) – Attribute path of the array to append to.

• type (LogsArrayProcessorOperationAppendType) – Operation type.

datadog_api_client.v1.model.logs_array_processor_operation_append_type module

class LogsArrayProcessorOperationAppendType(arg: None)

class LogsArrayProcessorOperationAppendType(arg: ModelComposed)

class LogsArrayProcessorOperationAppendType(*args, **kwargs)

Bases: ModelSimple

Operation type.

Parameters:

• value (str) – If omitted defaults to “append”. Must be one of [“append”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_array_processor_operation_length module

class LogsArrayProcessorOperationLength(arg: None)

class LogsArrayProcessorOperationLength(arg: ModelComposed)

class LogsArrayProcessorOperationLength(*args, **kwargs)

Bases: ModelNormal

Operation that computes the length of a source array and stores the result in the target attribute.

Parameters:

• source (str) – Attribute path of the array to measure.

• target (str) – Attribute that receives the computed length.

• type (LogsArrayProcessorOperationLengthType) – Operation type.

datadog_api_client.v1.model.logs_array_processor_operation_length_type module

class LogsArrayProcessorOperationLengthType(arg: None)

class LogsArrayProcessorOperationLengthType(arg: ModelComposed)

class LogsArrayProcessorOperationLengthType(*args, **kwargs)

Bases: ModelSimple

Operation type.

Parameters:

• value (str) – If omitted defaults to “length”. Must be one of [“length”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_array_processor_operation_select module

class LogsArrayProcessorOperationSelect(arg: None)

class LogsArrayProcessorOperationSelect(arg: ModelComposed)

class LogsArrayProcessorOperationSelect(*args, **kwargs)

Bases: ModelNormal

Operation that finds an object in a source array using a filter , and then extracts a specific value into the target attribute.

Parameters:

• filter (str) – Filter condition expressed as key:value used to find the matching element.

• source (str) – Attribute path of the array to search into.

• target (str) – Attribute that receives the extracted value.

• type (LogsArrayProcessorOperationSelectType) – Operation type.

• value_to_extract (str) – Key of the value to extract from the matching element.

datadog_api_client.v1.model.logs_array_processor_operation_select_type module

class LogsArrayProcessorOperationSelectType(arg: None)

class LogsArrayProcessorOperationSelectType(arg: ModelComposed)

class LogsArrayProcessorOperationSelectType(*args, **kwargs)

Bases: ModelSimple

Operation type.

Parameters:

• value (str) – If omitted defaults to “select”. Must be one of [“select”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_array_processor_type module

class LogsArrayProcessorType(arg: None)

class LogsArrayProcessorType(arg: ModelComposed)

class LogsArrayProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs array processor.

Parameters:

• value (str) – If omitted defaults to “array-processor”. Must be one of [“array-processor”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_attribute_remapper module

class LogsAttributeRemapper(arg: None)

class LogsAttributeRemapper(arg: ModelComposed)

class LogsAttributeRemapper(*args, **kwargs)

Bases: ModelNormal

The remapper processor remaps any source attribute(s) or tag to another target attribute or tag. Constraints on the tag/attribute name are explained in the Tag Best Practice documentation. Some additional constraints are applied as : or , are not allowed in the target tag/attribute name.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• override_on_conflict (bool, optional) – Override or not the target element if already set,

• preserve_source (bool, optional) – Remove or preserve the remapped source element.

• source_type (str, optional) – Defines if the sources are from log attribute or tag.

• sources ([str]) – Array of source attributes.

• target (str) – Final attribute or tag name to remap the sources to.

• target_format (TargetFormatType, optional) – If the target_type of the remapper is attribute , try to cast the value to a new specific type. If the cast is not possible, the original type is kept. string , integer , or double are the possible types. If the target_type is tag , this parameter may not be specified.

• target_type (str, optional) – Defines if the final attribute or tag name is from log attribute or tag.

• type (LogsAttributeRemapperType) – Type of logs attribute remapper.

datadog_api_client.v1.model.logs_attribute_remapper_type module

class LogsAttributeRemapperType(arg: None)

class LogsAttributeRemapperType(arg: ModelComposed)

class LogsAttributeRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs attribute remapper.

Parameters:

• value (str) – If omitted defaults to “attribute-remapper”. Must be one of [“attribute-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_by_retention module

class LogsByRetention(arg: None)

class LogsByRetention(arg: ModelComposed)

class LogsByRetention(*args, **kwargs)

Bases: ModelNormal

Object containing logs usage data broken down by retention period.

Parameters:

• orgs (LogsByRetentionOrgs, optional) – Indexed logs usage summary for each organization for each retention period with usage.

• usage ([LogsRetentionAggSumUsage], optional) – Aggregated index logs usage for each retention period with usage.

• usage_by_month (LogsByRetentionMonthlyUsage, optional) – Object containing a summary of indexed logs usage by retention period for a single month.

datadog_api_client.v1.model.logs_by_retention_monthly_usage module

class LogsByRetentionMonthlyUsage(arg: None)

class LogsByRetentionMonthlyUsage(arg: ModelComposed)

class LogsByRetentionMonthlyUsage(*args, **kwargs)

Bases: ModelNormal

Object containing a summary of indexed logs usage by retention period for a single month.

Parameters:

• date (datetime, optional) – The month for the usage.

• usage ([LogsRetentionSumUsage], optional) – Indexed logs usage for each active retention for the month.

datadog_api_client.v1.model.logs_by_retention_org_usage module

class LogsByRetentionOrgUsage(arg: None)

class LogsByRetentionOrgUsage(arg: ModelComposed)

class LogsByRetentionOrgUsage(*args, **kwargs)

Bases: ModelNormal

Indexed logs usage by retention for a single organization.

Parameters:

usage ([LogsRetentionSumUsage], optional) – Indexed logs usage for each active retention for the organization.

datadog_api_client.v1.model.logs_by_retention_orgs module

class LogsByRetentionOrgs(arg: None)

class LogsByRetentionOrgs(arg: ModelComposed)

class LogsByRetentionOrgs(*args, **kwargs)

Bases: ModelNormal

Indexed logs usage summary for each organization for each retention period with usage.

Parameters:

usage ([LogsByRetentionOrgUsage], optional) – Indexed logs usage summary for each organization.

datadog_api_client.v1.model.logs_category_processor module

class LogsCategoryProcessor(arg: None)

class LogsCategoryProcessor(arg: ModelComposed)

class LogsCategoryProcessor(*args, **kwargs)

Bases: ModelNormal

Use the Category Processor to add a new attribute (without spaces or special characters in the new attribute name) to a log matching a provided search query. Use categories to create groups for an analytical view. For example, URL groups, machine groups, environments, and response time buckets.

Notes :

• The syntax of the query is the one of Logs Explorer search bar. The query can be done on any log attribute or tag, whether it is a facet or not. Wildcards can also be used inside your query.

• Once the log has matched one of the Processor queries, it stops. Make sure they are properly ordered in case a log could match several queries.

• The names of the categories must be unique.

• Once defined in the Category Processor, you can map categories to log status using the Log Status Remapper.

Parameters:

• categories ([LogsCategoryProcessorCategory]) – Array of filters to match or not a log and their corresponding name to assign a custom value to the log.

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• target (str) – Name of the target attribute which value is defined by the matching category.

• type (LogsCategoryProcessorType) – Type of logs category processor.

datadog_api_client.v1.model.logs_category_processor_category module

class LogsCategoryProcessorCategory(arg: None)

class LogsCategoryProcessorCategory(arg: ModelComposed)

class LogsCategoryProcessorCategory(*args, **kwargs)

Bases: ModelNormal

Object describing the logs filter.

Parameters:

• filter (LogsFilter, optional) – Filter for logs.

• name (str, optional) – Value to assign to the target attribute.

datadog_api_client.v1.model.logs_category_processor_type module

class LogsCategoryProcessorType(arg: None)

class LogsCategoryProcessorType(arg: ModelComposed)

class LogsCategoryProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs category processor.

Parameters:

• value (str) – If omitted defaults to “category-processor”. Must be one of [“category-processor”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_daily_limit_reset module

class LogsDailyLimitReset(arg: None)

class LogsDailyLimitReset(arg: ModelComposed)

class LogsDailyLimitReset(*args, **kwargs)

Bases: ModelNormal

Object containing options to override the default daily limit reset time.

Parameters:

• reset_time (str, optional) – String in HH:00 format representing the time of day the daily limit should be reset. The hours must be between 00 and 23 (inclusive).

• reset_utc_offset (str, optional) – String in (-|+)HH:00 format representing the UTC offset to apply to the given reset time. The hours must be between -12 and +14 (inclusive).

datadog_api_client.v1.model.logs_date_remapper module

class LogsDateRemapper(arg: None)

class LogsDateRemapper(arg: ModelComposed)

class LogsDateRemapper(*args, **kwargs)

Bases: ModelNormal

As Datadog receives logs, it timestamps them using the value(s) from any of these default attributes.

• timestamp

• date

• _timestamp

• Timestamp

• eventTime

• published_date

  If your logs put their dates in an attribute not in this list, use the log date Remapper Processor to define their date attribute as the official log timestamp. The recognized date formats are ISO8601, UNIX (the milliseconds EPOCH format), and RFC3164.

  Note: If your logs don’t contain any of the default attributes and you haven’t defined your own date attribute, Datadog timestamps the logs with the date it received them.

  If multiple log date remapper processors can be applied to a given log, only the first one (according to the pipelines order) is taken into account.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• sources ([str]) – Array of source attributes.

• type (LogsDateRemapperType) – Type of logs date remapper.

datadog_api_client.v1.model.logs_date_remapper_type module

class LogsDateRemapperType(arg: None)

class LogsDateRemapperType(arg: ModelComposed)

class LogsDateRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs date remapper.

Parameters:

• value (str) – If omitted defaults to “date-remapper”. Must be one of [“date-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_decoder_processor module

class LogsDecoderProcessor(arg: None)

class LogsDecoderProcessor(arg: ModelComposed)

class LogsDecoderProcessor(*args, **kwargs)

Bases: ModelNormal

The decoder processor decodes any source attribute containing a base64/base16-encoded UTF-8/ASCII string back to its original value, storing the result in a target attribute.

Parameters:

• binary_to_text_encoding (LogsDecoderProcessorBinaryToTextEncoding) – The encoding used to represent the binary data.

• input_representation (LogsDecoderProcessorInputRepresentation) – The original representation of input string.

• is_enabled (bool, optional) – Whether the processor is enabled.

• name (str, optional) – Name of the processor.

• source (str) – Name of the log attribute with the encoded data.

• target (str) – Name of the log attribute that contains the decoded data.

• type (LogsDecoderProcessorType) – Type of logs decoder processor.

datadog_api_client.v1.model.logs_decoder_processor_binary_to_text_encoding module

class LogsDecoderProcessorBinaryToTextEncoding(arg: None)

class LogsDecoderProcessorBinaryToTextEncoding(arg: ModelComposed)

class LogsDecoderProcessorBinaryToTextEncoding(*args, **kwargs)

Bases: ModelSimple

The encoding used to represent the binary data.

Parameters:

• value (str) – Must be one of [“base64”, “base16”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_decoder_processor_input_representation module

class LogsDecoderProcessorInputRepresentation(arg: None)

class LogsDecoderProcessorInputRepresentation(arg: ModelComposed)

class LogsDecoderProcessorInputRepresentation(*args, **kwargs)

Bases: ModelSimple

The original representation of input string.

Parameters:

• value (str) – Must be one of [“utf_8”, “integer”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_decoder_processor_type module

class LogsDecoderProcessorType(arg: None)

class LogsDecoderProcessorType(arg: ModelComposed)

class LogsDecoderProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs decoder processor.

Parameters:

• value (str) – If omitted defaults to “decoder-processor”. Must be one of [“decoder-processor”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_exclusion module

class LogsExclusion(arg: None)

class LogsExclusion(arg: ModelComposed)

class LogsExclusion(*args, **kwargs)

Bases: ModelNormal

Represents the index exclusion filter object from configuration API.

Parameters:

• filter (LogsExclusionFilter, optional) – Exclusion filter is defined by a query, a sampling rule, and a active/inactive toggle.

• is_enabled (bool, optional) – Whether or not the exclusion filter is active.

• name (str) – Name of the index exclusion filter.

datadog_api_client.v1.model.logs_exclusion_filter module

class LogsExclusionFilter(arg: None)

class LogsExclusionFilter(arg: ModelComposed)

class LogsExclusionFilter(*args, **kwargs)

Bases: ModelNormal

Exclusion filter is defined by a query, a sampling rule, and a active/inactive toggle.

Parameters:

• query (str, optional) – Default query is * , meaning all logs flowing in the index would be excluded. Scope down exclusion filter to only a subset of logs with a log query.

• sample_rate (float) – Sample rate to apply to logs going through this exclusion filter, a value of 1.0 excludes all logs matching the query.

datadog_api_client.v1.model.logs_filter module

class LogsFilter(arg: None)

class LogsFilter(arg: ModelComposed)

class LogsFilter(*args, **kwargs)

Bases: ModelNormal

Filter for logs.

Parameters:

query (str, optional) – The filter query.

datadog_api_client.v1.model.logs_geo_ip_parser module

class LogsGeoIPParser(arg: None)

class LogsGeoIPParser(arg: ModelComposed)

class LogsGeoIPParser(*args, **kwargs)

Bases: ModelNormal

The GeoIP parser takes an IP address attribute and extracts if available the Continent, Country, Subdivision, and City information in the target attribute path.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• sources ([str]) – Array of source attributes.

• target (str) – Name of the parent attribute that contains all the extracted details from the sources.

• type (LogsGeoIPParserType) – Type of GeoIP parser.

datadog_api_client.v1.model.logs_geo_ip_parser_type module

class LogsGeoIPParserType(arg: None)

class LogsGeoIPParserType(arg: ModelComposed)

class LogsGeoIPParserType(*args, **kwargs)

Bases: ModelSimple

Type of GeoIP parser.

Parameters:

• value (str) – If omitted defaults to “geo-ip-parser”. Must be one of [“geo-ip-parser”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_grok_parser module

class LogsGrokParser(arg: None)

class LogsGrokParser(arg: ModelComposed)

class LogsGrokParser(*args, **kwargs)

Bases: ModelNormal

Create custom grok rules to parse the full message or a specific attribute of your raw event. For more information, see the parsing section.

Parameters:

• grok (LogsGrokParserRules) – Set of rules for the grok parser.

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• samples ([str], optional) – List of sample logs to test this grok parser.

• source (str) – Name of the log attribute to parse.

• type (LogsGrokParserType) – Type of logs grok parser.

datadog_api_client.v1.model.logs_grok_parser_rules module

class LogsGrokParserRules(arg: None)

class LogsGrokParserRules(arg: ModelComposed)

class LogsGrokParserRules(*args, **kwargs)

Bases: ModelNormal

Set of rules for the grok parser.

Parameters:

• match_rules (str) – List of match rules for the grok parser, separated by a new line.

• support_rules (str, optional) – List of support rules for the grok parser, separated by a new line.

datadog_api_client.v1.model.logs_grok_parser_type module

class LogsGrokParserType(arg: None)

class LogsGrokParserType(arg: ModelComposed)

class LogsGrokParserType(*args, **kwargs)

Bases: ModelSimple

Type of logs grok parser.

Parameters:

• value (str) – If omitted defaults to “grok-parser”. Must be one of [“grok-parser”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_index module

class LogsIndex(arg: None)

class LogsIndex(arg: ModelComposed)

class LogsIndex(*args, **kwargs)

Bases: ModelNormal

Object describing a Datadog Log index.

Parameters:

• daily_limit (int, optional) – The number of log events you can send in this index per day before you are rate-limited.

• daily_limit_reset (LogsDailyLimitReset, optional) – Object containing options to override the default daily limit reset time.

• daily_limit_warning_threshold_percentage (float, optional) – A percentage threshold of the daily quota at which a Datadog warning event is generated.

• exclusion_filters ([LogsExclusion], optional) – An array of exclusion objects. The logs are tested against the query of each filter, following the order of the array. Only the first matching active exclusion matters, others (if any) are ignored.

• filter (LogsFilter) – Filter for logs.

• is_rate_limited (bool, optional) – A boolean stating if the index is rate limited, meaning more logs than the daily limit have been sent. Rate limit is reset every-day at 2pm UTC.

• name (str) – The name of the index.

• num_flex_logs_retention_days (int, optional) – The total number of days logs are stored in Standard and Flex Tier before being deleted from the index. If Standard Tier is enabled on this index, logs are first retained in Standard Tier for the number of days specified through num_retention_days , and then stored in Flex Tier until the number of days specified in num_flex_logs_retention_days is reached. The available values depend on retention plans specified in your organization’s contract/subscriptions.

• num_retention_days (int, optional) – The number of days logs are stored in Standard Tier before aging into the Flex Tier or being deleted from the index. The available values depend on retention plans specified in your organization’s contract/subscriptions.

datadog_api_client.v1.model.logs_index_list_response module

class LogsIndexListResponse(arg: None)

class LogsIndexListResponse(arg: ModelComposed)

class LogsIndexListResponse(*args, **kwargs)

Bases: ModelNormal

Object with all Index configurations for a given organization.

Parameters:

indexes ([LogsIndex], optional) – Array of Log index configurations.

datadog_api_client.v1.model.logs_index_update_request module

class LogsIndexUpdateRequest(arg: None)

class LogsIndexUpdateRequest(arg: ModelComposed)

class LogsIndexUpdateRequest(*args, **kwargs)

Bases: ModelNormal

Object for updating a Datadog Log index.

Parameters:

• daily_limit (int, optional) – The number of log events you can send in this index per day before you are rate-limited.

• daily_limit_reset (LogsDailyLimitReset, optional) – Object containing options to override the default daily limit reset time.

• daily_limit_warning_threshold_percentage (float, optional) – A percentage threshold of the daily quota at which a Datadog warning event is generated.

• disable_daily_limit (bool, optional) – If true, sets the daily_limit value to null and the index is not limited on a daily basis (any specified daily_limit value in the request is ignored). If false or omitted, the index’s current daily_limit is maintained.

• exclusion_filters ([LogsExclusion], optional) – An array of exclusion objects. The logs are tested against the query of each filter, following the order of the array. Only the first matching active exclusion matters, others (if any) are ignored.

• filter (LogsFilter) – Filter for logs.

• num_flex_logs_retention_days (int, optional) –

  The total number of days logs are stored in Standard and Flex Tier before being deleted from the index. If Standard Tier is enabled on this index, logs are first retained in Standard Tier for the number of days specified through num_retention_days , and then stored in Flex Tier until the number of days specified in num_flex_logs_retention_days is reached. The available values depend on retention plans specified in your organization’s contract/subscriptions.

  Note : Changing this value affects all logs already in this index. It may also affect billing.

• num_retention_days (int, optional) –

  The number of days logs are stored in Standard Tier before aging into the Flex Tier or being deleted from the index. The available values depend on retention plans specified in your organization’s contract/subscriptions.

  Note : Changing this value affects all logs already in this index. It may also affect billing.

datadog_api_client.v1.model.logs_indexes_order module

class LogsIndexesOrder(arg: None)

class LogsIndexesOrder(arg: ModelComposed)

class LogsIndexesOrder(*args, **kwargs)

Bases: ModelNormal

Object containing the ordered list of log index names.

Parameters:

index_names ([str]) – Array of strings identifying by their name(s) the index(es) of your organization. Logs are tested against the query filter of each index one by one, following the order of the array. Logs are eventually stored in the first matching index.

datadog_api_client.v1.model.logs_list_request module

class LogsListRequest(arg: None)

class LogsListRequest(arg: ModelComposed)

class LogsListRequest(*args, **kwargs)

Bases: ModelNormal

Object to send with the request to retrieve a list of logs from your Organization.

Parameters:

• index (str, optional) – The log index on which the request is performed. For multi-index organizations, the default is all live indexes. Historical indexes of rehydrated logs must be specified.

• limit (int, optional) – Number of logs return in the response.

• query (str, optional) – The search query - following the log search syntax.

• sort (LogsSort, optional) – Time-ascending asc or time-descending desc results.

• start_at (str, optional) –

  Hash identifier of the first log to return in the list, available in a log id attribute. This parameter is used for the pagination feature.

  Note : This parameter is ignored if the corresponding log is out of the scope of the specified time window.

• time (LogsListRequestTime) – Timeframe to retrieve the log from.

datadog_api_client.v1.model.logs_list_request_time module

class LogsListRequestTime(arg: None)

class LogsListRequestTime(arg: ModelComposed)

class LogsListRequestTime(*args, **kwargs)

Bases: ModelNormal

Timeframe to retrieve the log from.

Parameters:

• _from (datetime) – Minimum timestamp for requested logs.

• timezone (str, optional) – Timezone can be specified both as an offset (for example “UTC+03:00”) or a regional zone (for example “Europe/Paris”).

• to (datetime) – Maximum timestamp for requested logs.

datadog_api_client.v1.model.logs_list_response module

class LogsListResponse(arg: None)

class LogsListResponse(arg: ModelComposed)

class LogsListResponse(*args, **kwargs)

Bases: ModelNormal

Response object with all logs matching the request and pagination information.

Parameters:

• logs ([Log], optional) – Array of logs matching the request and the nextLogId if sent.

• next_log_id (str, none_type, optional) – Hash identifier of the next log to return in the list. This parameter is used for the pagination feature.

• status (str, optional) – Status of the response.

datadog_api_client.v1.model.logs_lookup_processor module

class LogsLookupProcessor(arg: None)

class LogsLookupProcessor(arg: ModelComposed)

class LogsLookupProcessor(*args, **kwargs)

Bases: ModelNormal

Use the Lookup Processor to define a mapping between a log attribute and a human readable value saved in the processors mapping table. For example, you can use the Lookup Processor to map an internal service ID into a human readable service name. Alternatively, you could also use it to check if the MAC address that just attempted to connect to the production environment belongs to your list of stolen machines.

Parameters:

• default_lookup (str, optional) – Value to set the target attribute if the source value is not found in the list.

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• lookup_table ([str]) – Mapping table of values for the source attribute and their associated target attribute values, formatted as ["source_key1,target_value1", "source_key2,target_value2"]

• name (str, optional) – Name of the processor.

• source (str) – Source attribute used to perform the lookup.

• target (str) – Name of the attribute that contains the corresponding value in the mapping list or the default_lookup if not found in the mapping list.

• type (LogsLookupProcessorType) – Type of logs lookup processor.

datadog_api_client.v1.model.logs_lookup_processor_type module

class LogsLookupProcessorType(arg: None)

class LogsLookupProcessorType(arg: ModelComposed)

class LogsLookupProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs lookup processor.

Parameters:

• value (str) – If omitted defaults to “lookup-processor”. Must be one of [“lookup-processor”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_message_remapper module

class LogsMessageRemapper(arg: None)

class LogsMessageRemapper(arg: ModelComposed)

class LogsMessageRemapper(*args, **kwargs)

Bases: ModelNormal

The message is a key attribute in Datadog. It is displayed in the message column of the Log Explorer and you can do full string search on it. Use this Processor to define one or more attributes as the official log message.

Note: If multiple log message remapper processors can be applied to a given log, only the first one (according to the pipeline order) is taken into account.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• sources ([str]) – Array of source attributes.

• type (LogsMessageRemapperType) – Type of logs message remapper.

datadog_api_client.v1.model.logs_message_remapper_type module

class LogsMessageRemapperType(arg: None)

class LogsMessageRemapperType(arg: ModelComposed)

class LogsMessageRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs message remapper.

Parameters:

• value (str) – If omitted defaults to “message-remapper”. Must be one of [“message-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_pipeline module

class LogsPipeline(arg: None)

class LogsPipeline(arg: ModelComposed)

class LogsPipeline(*args, **kwargs)

Bases: ModelNormal

Pipelines and processors operate on incoming logs, parsing and transforming them into structured attributes for easier querying.

Note : These endpoints are only available for admin users. Make sure to use an application key created by an admin.

Parameters:

• description (str, optional) – A description of the pipeline.

• filter (LogsFilter, optional) – Filter for logs.

• id (str, optional) – ID of the pipeline.

• is_enabled (bool, optional) – Whether or not the pipeline is enabled.

• is_read_only (bool, optional) – Whether or not the pipeline can be edited.

• name (str) – Name of the pipeline.

• processors ([LogsProcessor], optional) – Ordered list of processors in this pipeline.

• tags ([str], optional) – A list of tags associated with the pipeline.

• type (str, optional) – Type of pipeline.

datadog_api_client.v1.model.logs_pipeline_list module

class LogsPipelineList(arg: None)

class LogsPipelineList(arg: ModelComposed)

class LogsPipelineList(*args, **kwargs)

Bases: ModelSimple

Array of all log pipeline objects configured for the organization.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_pipeline_processor module

class LogsPipelineProcessor(arg: None)

class LogsPipelineProcessor(arg: ModelComposed)

class LogsPipelineProcessor(*args, **kwargs)

Bases: ModelNormal

Nested Pipelines are pipelines within a pipeline. Use Nested Pipelines to split the processing into two steps. For example, first use a high-level filtering such as team and then a second level of filtering based on the integration, service, or any other tag or attribute.

A pipeline can contain Nested Pipelines and Processors whereas a Nested Pipeline can only contain Processors.

Parameters:

• filter (LogsFilter, optional) – Filter for logs.

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• processors ([LogsProcessor], optional) – Ordered list of processors in this pipeline.

• type (LogsPipelineProcessorType) – Type of logs pipeline processor.

datadog_api_client.v1.model.logs_pipeline_processor_type module

class LogsPipelineProcessorType(arg: None)

class LogsPipelineProcessorType(arg: ModelComposed)

class LogsPipelineProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs pipeline processor.

Parameters:

• value (str) – If omitted defaults to “pipeline”. Must be one of [“pipeline”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_pipelines_order module

class LogsPipelinesOrder(arg: None)

class LogsPipelinesOrder(arg: ModelComposed)

class LogsPipelinesOrder(*args, **kwargs)

Bases: ModelNormal

Object containing the ordered list of pipeline IDs.

Parameters:

pipeline_ids ([str]) – Ordered Array of <PIPELINE_ID> strings, the order of pipeline IDs in the array define the overall Pipelines order for Datadog.

datadog_api_client.v1.model.logs_processor module

class LogsProcessor(arg: None)

class LogsProcessor(arg: ModelComposed)

class LogsProcessor(*args, **kwargs)

Bases: ModelComposed

Definition of a logs processor.

Parameters:

• grok (LogsGrokParserRules) – Set of rules for the grok parser.

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• samples ([str], optional) – List of sample logs to test this grok parser.

• source (str) – Name of the log attribute to parse.

• type (LogsGrokParserType) – Type of logs grok parser.

• sources ([str]) – Array of source attributes.

• override_on_conflict (bool, optional) – Override or not the target element if already set,

• preserve_source (bool, optional) – Remove or preserve the remapped source element.

• source_type (str, optional) – Defines if the sources are from log attribute or tag.

• target (str) – Final attribute or tag name to remap the sources to.

• target_format (TargetFormatType, optional) – If the target_type of the remapper is attribute, try to cast the value to a new specific type. If the cast is not possible, the original type is kept. string, integer, or double are the possible types. If the target_type is tag, this parameter may not be specified.

• target_type (str, optional) – Defines if the final attribute or tag name is from log attribute or tag.

• normalize_ending_slashes (bool, none_type, optional) – Normalize the ending slashes or not.

• is_encoded (bool, optional) – Define if the source attribute is URL encoded or not.

• categories ([LogsCategoryProcessorCategory]) – Array of filters to match or not a log and their corresponding name to assign a custom value to the log.

• expression (str) – Arithmetic operation between one or more log attributes.

• is_replace_missing (bool, optional) – If true, it replaces all missing attributes of expression by 0, false skip the operation if an attribute is missing.

• template (str) – A formula with one or more attributes and raw text.

• filter (LogsFilter, optional) – Filter for logs.

• processors ([LogsProcessor], optional) – Ordered list of processors in this pipeline.

• default_lookup (str, optional) – Value to set the target attribute if the source value is not found in the list.

• lookup_table ([str]) – Mapping table of values for the source attribute and their associated target attribute values, formatted as [“source_key1,target_value1”, “source_key2,target_value2”]

• lookup_enrichment_table (str) – Name of the Reference Table for the source attribute and their associated target attribute values.

• operation (LogsArrayProcessorOperation) – Configuration of the array processor operation to perform.

• binary_to_text_encoding (LogsDecoderProcessorBinaryToTextEncoding) – The encoding used to represent the binary data.

• input_representation (LogsDecoderProcessorInputRepresentation) – The original representation of input string.

• mappers ([LogsSchemaMapper]) – The LogsSchemaProcessor mappers.

• schema (LogsSchemaData) – Configuration of the schema data to use.

datadog_api_client.v1.model.logs_query_compute module

class LogsQueryCompute(arg: None)

class LogsQueryCompute(arg: ModelComposed)

class LogsQueryCompute(*args, **kwargs)

Bases: ModelNormal

Define computation for a log query.

Parameters:

• aggregation (str) – The aggregation method.

• facet (str, optional) – Facet name.

• interval (int, optional) – Define a time interval in seconds.

datadog_api_client.v1.model.logs_retention_agg_sum_usage module

class LogsRetentionAggSumUsage(arg: None)

class LogsRetentionAggSumUsage(arg: ModelComposed)

class LogsRetentionAggSumUsage(*args, **kwargs)

Bases: ModelNormal

Object containing indexed logs usage aggregated across organizations and months for a retention period.

Parameters:

• logs_indexed_logs_usage_agg_sum (int, optional) – Total indexed logs for this retention period.

• logs_live_indexed_logs_usage_agg_sum (int, optional) – Live indexed logs for this retention period.

• logs_rehydrated_indexed_logs_usage_agg_sum (int, optional) – Rehydrated indexed logs for this retention period.

• retention (str, optional) – The retention period in days or “custom” for all custom retention periods.

datadog_api_client.v1.model.logs_retention_sum_usage module

class LogsRetentionSumUsage(arg: None)

class LogsRetentionSumUsage(arg: ModelComposed)

class LogsRetentionSumUsage(*args, **kwargs)

Bases: ModelNormal

Object containing indexed logs usage grouped by retention period and summed.

Parameters:

• logs_indexed_logs_usage_sum (int, optional) – Total indexed logs for this retention period.

• logs_live_indexed_logs_usage_sum (int, optional) – Live indexed logs for this retention period.

• logs_rehydrated_indexed_logs_usage_sum (int, optional) – Rehydrated indexed logs for this retention period.

• retention (str, optional) – The retention period in days or “custom” for all custom retention periods.

datadog_api_client.v1.model.logs_schema_category_mapper module

class LogsSchemaCategoryMapper(arg: None)

class LogsSchemaCategoryMapper(arg: ModelComposed)

class LogsSchemaCategoryMapper(*args, **kwargs)

Bases: ModelNormal

Use the Schema Category Mapper to categorize log event into enum fields. In the case of OCSF, they can be used to map sibling fields which are composed of an ID and a name.

Notes :

• The syntax of the query is the one of Logs Explorer search bar. The query can be done on any log attribute or tag, whether it is a facet or not. Wildcards can also be used inside your query.

• Categories are executed in order and processing stops at the first match. Make sure categories are properly ordered in case a log could match multiple queries.

• Sibling fields always have a numerical ID field and a human-readable string name.

• A fallback section handles cases where the name or ID value matches a specific value. If the name matches “Other” or the ID matches 99, the value of the sibling name field will be pulled from a source field from the original log.

Parameters:

• categories ([LogsSchemaCategoryMapperCategory]) – Array of filters to match or not a log and their corresponding name to assign a custom value to the log.

• fallback (LogsSchemaCategoryMapperFallback, optional) – Used to override hardcoded category values with a value pulled from a source attribute on the log.

• name (str) – Name of the logs schema category mapper.

• targets (LogsSchemaCategoryMapperTargets) – Name of the target attributes which value is defined by the matching category.

• type (LogsSchemaCategoryMapperType) – Type of logs schema category mapper.

datadog_api_client.v1.model.logs_schema_category_mapper_category module

class LogsSchemaCategoryMapperCategory(arg: None)

class LogsSchemaCategoryMapperCategory(arg: ModelComposed)

class LogsSchemaCategoryMapperCategory(*args, **kwargs)

Bases: ModelNormal

Object describing the logs filter with corresponding category ID and name assignment.

Parameters:

• filter (LogsFilter) – Filter for logs.

• id (int) – ID to inject into the category.

• name (str) – Value to assign to target schema field.

datadog_api_client.v1.model.logs_schema_category_mapper_fallback module

class LogsSchemaCategoryMapperFallback(arg: None)

class LogsSchemaCategoryMapperFallback(arg: ModelComposed)

class LogsSchemaCategoryMapperFallback(*args, **kwargs)

Bases: ModelNormal

Used to override hardcoded category values with a value pulled from a source attribute on the log.

Parameters:

• sources ({str: ([str],)}, optional) – Fallback sources used to populate value of field.

• values ({str: (str,)}, optional) – Values that define when the fallback is used.

datadog_api_client.v1.model.logs_schema_category_mapper_targets module

class LogsSchemaCategoryMapperTargets(arg: None)

class LogsSchemaCategoryMapperTargets(arg: ModelComposed)

class LogsSchemaCategoryMapperTargets(*args, **kwargs)

Bases: ModelNormal

Name of the target attributes which value is defined by the matching category.

Parameters:

• id (str, optional) – ID of the field to map log attributes to.

• name (str, optional) – Name of the field to map log attributes to.

datadog_api_client.v1.model.logs_schema_category_mapper_type module

class LogsSchemaCategoryMapperType(arg: None)

class LogsSchemaCategoryMapperType(arg: ModelComposed)

class LogsSchemaCategoryMapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs schema category mapper.

Parameters:

• value (str) – If omitted defaults to “schema-category-mapper”. Must be one of [“schema-category-mapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_schema_data module

class LogsSchemaData(arg: None)

class LogsSchemaData(arg: ModelComposed)

class LogsSchemaData(*args, **kwargs)

Bases: ModelNormal

Configuration of the schema data to use.

Parameters:

• class_name (str) – Class name of the schema to use.

• class_uid (int) – Class UID of the schema to use.

• profiles ([str], optional) – Optional list of profiles to modify the schema.

• schema_type (str) – Type of schema to use.

• version (str) – Version of the schema to use.

datadog_api_client.v1.model.logs_schema_mapper module

class LogsSchemaMapper(arg: None)

class LogsSchemaMapper(arg: ModelComposed)

class LogsSchemaMapper(*args, **kwargs)

Bases: ModelComposed

Configuration of the schema processor mapper to use.

Parameters:

• name (str) – Name of the logs schema remapper.

• override_on_conflict (bool, optional) – Override or not the target element if already set.

• preserve_source (bool, optional) – Remove or preserve the remapped source element.

• sources ([str]) – Array of source attributes.

• target (str) – Target field to map log source field to.

• target_format (TargetFormatType, optional) – If the target_type of the remapper is attribute, try to cast the value to a new specific type. If the cast is not possible, the original type is kept. string, integer, or double are the possible types. If the target_type is tag, this parameter may not be specified.

• type (LogsSchemaRemapperType) – Type of logs schema remapper.

• categories ([LogsSchemaCategoryMapperCategory]) – Array of filters to match or not a log and their corresponding name to assign a custom value to the log.

• fallback (LogsSchemaCategoryMapperFallback, optional) – Used to override hardcoded category values with a value pulled from a source attribute on the log.

• targets (LogsSchemaCategoryMapperTargets) – Name of the target attributes which value is defined by the matching category.

datadog_api_client.v1.model.logs_schema_processor module

class LogsSchemaProcessor(arg: None)

class LogsSchemaProcessor(arg: ModelComposed)

class LogsSchemaProcessor(*args, **kwargs)

Bases: ModelNormal

A processor that has additional validations and checks for a given schema. Currently supported schema types include OCSF.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• mappers ([LogsSchemaMapper]) – The LogsSchemaProcessor mappers.

• name (str) – Name of the processor.

• schema (LogsSchemaData) – Configuration of the schema data to use.

• type (LogsSchemaProcessorType) – Type of logs schema processor.

datadog_api_client.v1.model.logs_schema_processor_type module

class LogsSchemaProcessorType(arg: None)

class LogsSchemaProcessorType(arg: ModelComposed)

class LogsSchemaProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs schema processor.

Parameters:

• value (str) – If omitted defaults to “schema-processor”. Must be one of [“schema-processor”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_schema_remapper module

class LogsSchemaRemapper(arg: None)

class LogsSchemaRemapper(arg: ModelComposed)

class LogsSchemaRemapper(*args, **kwargs)

Bases: ModelNormal

The schema remapper maps source log fields to their correct fields.

Parameters:

• name (str) – Name of the logs schema remapper.

• override_on_conflict (bool, optional) – Override or not the target element if already set.

• preserve_source (bool, optional) – Remove or preserve the remapped source element.

• sources ([str]) – Array of source attributes.

• target (str) – Target field to map log source field to.

• target_format (TargetFormatType, optional) – If the target_type of the remapper is attribute , try to cast the value to a new specific type. If the cast is not possible, the original type is kept. string , integer , or double are the possible types. If the target_type is tag , this parameter may not be specified.

• type (LogsSchemaRemapperType) – Type of logs schema remapper.

datadog_api_client.v1.model.logs_schema_remapper_type module

class LogsSchemaRemapperType(arg: None)

class LogsSchemaRemapperType(arg: ModelComposed)

class LogsSchemaRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs schema remapper.

Parameters:

• value (str) – If omitted defaults to “schema-remapper”. Must be one of [“schema-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_service_remapper module

class LogsServiceRemapper(arg: None)

class LogsServiceRemapper(arg: ModelComposed)

class LogsServiceRemapper(*args, **kwargs)

Bases: ModelNormal

Use this processor if you want to assign one or more attributes as the official service.

Note: If multiple service remapper processors can be applied to a given log, only the first one (according to the pipeline order) is taken into account.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• sources ([str]) – Array of source attributes.

• type (LogsServiceRemapperType) – Type of logs service remapper.

datadog_api_client.v1.model.logs_service_remapper_type module

class LogsServiceRemapperType(arg: None)

class LogsServiceRemapperType(arg: ModelComposed)

class LogsServiceRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs service remapper.

Parameters:

• value (str) – If omitted defaults to “service-remapper”. Must be one of [“service-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_sort module

class LogsSort(arg: None)

class LogsSort(arg: ModelComposed)

class LogsSort(*args, **kwargs)

Bases: ModelSimple

Time-ascending asc or time-descending desc results.

Parameters:

• value (str) – Must be one of [“asc”, “desc”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_span_remapper module

class LogsSpanRemapper(arg: None)

class LogsSpanRemapper(arg: ModelComposed)

class LogsSpanRemapper(*args, **kwargs)

Bases: ModelNormal

There are two ways to define correlation between application spans and logs:

1. Follow the documentation on how to inject a span ID in the application logs. Log integrations automatically handle all remaining setup steps by default.

2. Use the span remapper processor to define a log attribute as its associated span ID.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• sources ([str], optional) – Array of source attributes.

• type (LogsSpanRemapperType) – Type of logs span remapper.

datadog_api_client.v1.model.logs_span_remapper_type module

class LogsSpanRemapperType(arg: None)

class LogsSpanRemapperType(arg: ModelComposed)

class LogsSpanRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs span remapper.

Parameters:

• value (str) – If omitted defaults to “span-id-remapper”. Must be one of [“span-id-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_status_remapper module

class LogsStatusRemapper(arg: None)

class LogsStatusRemapper(arg: ModelComposed)

class LogsStatusRemapper(*args, **kwargs)

Bases: ModelNormal

Use this Processor if you want to assign some attributes as the official status.

Each incoming status value is mapped as follows.

• Integers from 0 to 7 map to the Syslog severity standards

• Strings beginning with emerg or f (case-insensitive) map to emerg (0)

• Strings beginning with a (case-insensitive) map to alert (1)

• Strings beginning with c (case-insensitive) map to critical (2)

• Strings beginning with err (case-insensitive) map to error (3)

• Strings beginning with w (case-insensitive) map to warning (4)

• Strings beginning with n (case-insensitive) map to notice (5)

• Strings beginning with i (case-insensitive) map to info (6)

• Strings beginning with d , trace or verbose (case-insensitive) map to debug (7)

• Strings beginning with o or matching OK or Success (case-insensitive) map to OK

• All others map to info (6)

  Note: If multiple log status remapper processors can be applied to a given log, only the first one (according to the pipelines order) is taken into account.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• sources ([str]) – Array of source attributes.

• type (LogsStatusRemapperType) – Type of logs status remapper.

datadog_api_client.v1.model.logs_status_remapper_type module

class LogsStatusRemapperType(arg: None)

class LogsStatusRemapperType(arg: ModelComposed)

class LogsStatusRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs status remapper.

Parameters:

• value (str) – If omitted defaults to “status-remapper”. Must be one of [“status-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_string_builder_processor module

class LogsStringBuilderProcessor(arg: None)

class LogsStringBuilderProcessor(arg: ModelComposed)

class LogsStringBuilderProcessor(*args, **kwargs)

Bases: ModelNormal

Use the string builder processor to add a new attribute (without spaces or special characters) to a log with the result of the provided template. This enables aggregation of different attributes or raw strings into a single attribute.

The template is defined by both raw text and blocks with the syntax %{attribute_path}.

Notes :

• The processor only accepts attributes with values or an array of values in the blocks.

• If an attribute cannot be used (object or array of object), it is replaced by an empty string or the entire operation is skipped depending on your selection.

• If the target attribute already exists, it is overwritten by the result of the template.

• Results of the template cannot exceed 256 characters.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• is_replace_missing (bool, optional) – If true, it replaces all missing attributes of template by an empty string. If false (default), skips the operation for missing attributes.

• name (str, optional) – Name of the processor.

• target (str) – The name of the attribute that contains the result of the template.

• template (str) – A formula with one or more attributes and raw text.

• type (LogsStringBuilderProcessorType) – Type of logs string builder processor.

datadog_api_client.v1.model.logs_string_builder_processor_type module

class LogsStringBuilderProcessorType(arg: None)

class LogsStringBuilderProcessorType(arg: ModelComposed)

class LogsStringBuilderProcessorType(*args, **kwargs)

Bases: ModelSimple

Type of logs string builder processor.

Parameters:

• value (str) – If omitted defaults to “string-builder-processor”. Must be one of [“string-builder-processor”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_trace_remapper module

class LogsTraceRemapper(arg: None)

class LogsTraceRemapper(arg: ModelComposed)

class LogsTraceRemapper(*args, **kwargs)

Bases: ModelNormal

There are two ways to improve correlation between application traces and logs.

1. Follow the documentation on how to inject a trace ID in the application logs and by default log integrations take care of all the rest of the setup.

2. Use the Trace remapper processor to define a log attribute as its associated trace ID.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• sources ([str], optional) – Array of source attributes.

• type (LogsTraceRemapperType) – Type of logs trace remapper.

datadog_api_client.v1.model.logs_trace_remapper_type module

class LogsTraceRemapperType(arg: None)

class LogsTraceRemapperType(arg: ModelComposed)

class LogsTraceRemapperType(*args, **kwargs)

Bases: ModelSimple

Type of logs trace remapper.

Parameters:

• value (str) – If omitted defaults to “trace-id-remapper”. Must be one of [“trace-id-remapper”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_url_parser module

class LogsURLParser(arg: None)

class LogsURLParser(arg: ModelComposed)

class LogsURLParser(*args, **kwargs)

Bases: ModelNormal

This processor extracts query parameters and other important parameters from a URL.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• name (str, optional) – Name of the processor.

• normalize_ending_slashes (bool, none_type, optional) – Normalize the ending slashes or not.

• sources ([str]) – Array of source attributes.

• target (str) – Name of the parent attribute that contains all the extracted details from the sources.

• type (LogsURLParserType) – Type of logs URL parser.

datadog_api_client.v1.model.logs_url_parser_type module

class LogsURLParserType(arg: None)

class LogsURLParserType(arg: ModelComposed)

class LogsURLParserType(*args, **kwargs)

Bases: ModelSimple

Type of logs URL parser.

Parameters:

• value (str) – If omitted defaults to “url-parser”. Must be one of [“url-parser”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.logs_user_agent_parser module

class LogsUserAgentParser(arg: None)

class LogsUserAgentParser(arg: ModelComposed)

class LogsUserAgentParser(*args, **kwargs)

Bases: ModelNormal

The User-Agent parser takes a User-Agent attribute and extracts the OS, browser, device, and other user data. It recognizes major bots like the Google Bot, Yahoo Slurp, and Bing.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• is_encoded (bool, optional) – Define if the source attribute is URL encoded or not.

• name (str, optional) – Name of the processor.

• sources ([str]) – Array of source attributes.

• target (str) – Name of the parent attribute that contains all the extracted details from the sources.

• type (LogsUserAgentParserType) – Type of logs User-Agent parser.

datadog_api_client.v1.model.logs_user_agent_parser_type module

class LogsUserAgentParserType(arg: None)

class LogsUserAgentParserType(arg: ModelComposed)

class LogsUserAgentParserType(*args, **kwargs)

Bases: ModelSimple

Type of logs User-Agent parser.

Parameters:

• value (str) – If omitted defaults to “user-agent-parser”. Must be one of [“user-agent-parser”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.matching_downtime module

class MatchingDowntime(arg: None)

class MatchingDowntime(arg: ModelComposed)

class MatchingDowntime(*args, **kwargs)

Bases: ModelNormal

Object describing a downtime that matches this monitor.

Parameters:

• end (int, none_type, optional) – POSIX timestamp to end the downtime.

• id (int) – The downtime ID.

• scope ([str], optional) – The scope(s) to which the downtime applies. Must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).

• start (int, optional) – POSIX timestamp to start the downtime.

datadog_api_client.v1.model.metric_content_encoding module

class MetricContentEncoding(arg: None)

class MetricContentEncoding(arg: ModelComposed)

class MetricContentEncoding(*args, **kwargs)

Bases: ModelSimple

HTTP header used to compress the media-type.

Parameters:

• value (str) – If omitted defaults to “deflate”. Must be one of [“deflate”, “gzip”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.metric_metadata module

class MetricMetadata(arg: None)

class MetricMetadata(arg: ModelComposed)

class MetricMetadata(*args, **kwargs)

Bases: ModelNormal

Object with all metric related metadata.

Parameters:

• description (str, optional) – Metric description.

• integration (str, optional) – Name of the integration that sent the metric if applicable.

• per_unit (str, optional) – Per unit of the metric such as second in bytes per second.

• short_name (str, optional) – A more human-readable and abbreviated version of the metric name.

• statsd_interval (int, optional) – StatsD flush interval of the metric in seconds if applicable.

• type (str, optional) – Metric type such as gauge or rate.

• unit (str, optional) – Primary unit of the metric such as byte or operation.

datadog_api_client.v1.model.metric_search_response module

class MetricSearchResponse(arg: None)

class MetricSearchResponse(arg: ModelComposed)

class MetricSearchResponse(*args, **kwargs)

Bases: ModelNormal

Object containing the list of metrics matching the search query.

Parameters:

results (MetricSearchResponseResults, optional) – Search result.

datadog_api_client.v1.model.metric_search_response_results module

class MetricSearchResponseResults(arg: None)

class MetricSearchResponseResults(arg: ModelComposed)

class MetricSearchResponseResults(*args, **kwargs)

Bases: ModelNormal

Search result.

Parameters:

metrics ([str], optional) – List of metrics that match the search query.

datadog_api_client.v1.model.metrics_list_response module

class MetricsListResponse(arg: None)

class MetricsListResponse(arg: ModelComposed)

class MetricsListResponse(*args, **kwargs)

Bases: ModelNormal

Object listing all metric names stored by Datadog since a given time.

Parameters:

• _from (str, optional) – Time when the metrics were active, seconds since the Unix epoch.

• metrics ([str], optional) – List of metric names.

datadog_api_client.v1.model.metrics_payload module

class MetricsPayload(arg: None)

class MetricsPayload(arg: ModelComposed)

class MetricsPayload(*args, **kwargs)

Bases: ModelNormal

The metrics’ payload.

Parameters:

series ([Series]) – A list of timeseries to submit to Datadog.

datadog_api_client.v1.model.metrics_query_metadata module

class MetricsQueryMetadata(arg: None)

class MetricsQueryMetadata(arg: ModelComposed)

class MetricsQueryMetadata(*args, **kwargs)

Bases: ModelNormal

Object containing all metric names returned and their associated metadata.

Parameters:

• aggr (str, none_type, optional) – Aggregation type.

• display_name (str, optional) – Display name of the metric.

• end (int, optional) – End of the time window, milliseconds since Unix epoch.

• expression (str, optional) – Metric expression.

• interval (int, optional) – Number of milliseconds between data samples.

• length (int, optional) – Number of data samples.

• metric (str, optional) – Metric name.

• pointlist ([Point], optional) – List of points of the timeseries in milliseconds.

• query_index (int, optional) – The index of the series’ query within the request.

• scope (str, optional) – Metric scope, comma separated list of tags.

• start (int, optional) – Start of the time window, milliseconds since Unix epoch.

• tag_set ([str], optional) – Unique tags identifying this series.

• unit ([MetricsQueryUnit, none_type], optional) – Detailed information about the metric unit. The first element describes the “primary unit” (for example, bytes in bytes per second ). The second element describes the “per unit” (for example, second in bytes per second ). If the second element is not present, the API returns null.

datadog_api_client.v1.model.metrics_query_response module

class MetricsQueryResponse(arg: None)

class MetricsQueryResponse(arg: ModelComposed)

class MetricsQueryResponse(*args, **kwargs)

Bases: ModelNormal

Response Object that includes your query and the list of metrics retrieved.

Parameters:

• error (str, optional) – Message indicating the errors if status is not ok.

• from_date (int, optional) – Start of requested time window, milliseconds since Unix epoch.

• group_by ([str], optional) – List of tag keys on which to group.

• message (str, optional) – Message indicating success if status is ok.

• query (str, optional) – Query string

• res_type (str, optional) – Type of response.

• series ([MetricsQueryMetadata], optional) – List of timeseries queried.

• status (str, optional) – Status of the query.

• to_date (int, optional) – End of requested time window, milliseconds since Unix epoch.

datadog_api_client.v1.model.metrics_query_unit module

class MetricsQueryUnit(arg: None)

class MetricsQueryUnit(arg: ModelComposed)

class MetricsQueryUnit(*args, **kwargs)

Bases: ModelNormal

Object containing the metric unit family, scale factor, name, and short name.

Parameters:

• family (str, optional) – Unit family, allows for conversion between units of the same family, for scaling.

• name (str, optional) – Unit name

• plural (str, optional) – Plural form of the unit name.

• scale_factor (float, optional) – Factor for scaling between units of the same family.

• short_name (str, optional) – Abbreviation of the unit.

datadog_api_client.v1.model.monitor module

class Monitor(arg: None)

class Monitor(arg: ModelComposed)

class Monitor(*args, **kwargs)

Bases: ModelNormal

Object describing a monitor.

Parameters:

• created (datetime, optional) – Timestamp of the monitor creation.

• creator (Creator, optional) – Object describing the creator of the shared element.

• deleted (datetime, none_type, optional) – Whether or not the monitor is deleted. (Always null )

• draft_status (MonitorDraftStatus, optional) –

  Indicates whether the monitor is in a draft or published state.

  draft : The monitor appears as Draft and does not send notifications. published : The monitor is active and evaluates conditions and notify as configured.

  This field is in preview. The draft value is only available to customers with the feature enabled.

• id (int, optional) – ID of this monitor.

• matching_downtimes ([MatchingDowntime], optional) – A list of active v1 downtimes that match this monitor.

• message (str, optional) – A message to include with notifications for this monitor.

• modified (datetime, optional) – Last timestamp when the monitor was edited.

• multi (bool, optional) – Whether or not the monitor is broken down on different groups.

• name (str, optional) – The monitor name.

• options (MonitorOptions, optional) – List of options associated with your monitor.

• overall_state (MonitorOverallStates, optional) – The different states your monitor can be in.

• priority (int, none_type, optional) – Integer from 1 (high) to 5 (low) indicating alert severity.

• query (str) – The monitor query.

• restricted_roles ([str], none_type, optional) –

  A list of unique role identifiers to define which roles are allowed to edit the monitor. The unique identifiers for all roles can be pulled from the Roles API and are located in the data.id field. Editing a monitor includes any updates to the monitor configuration, monitor deletion, and muting of the monitor for any amount of time. You can use the Restriction Policies API to manage write authorization for individual monitors by teams and users, in addition to roles.

• state (MonitorState, optional) – Wrapper object with the different monitor states.

• tags ([str], optional) – Tags associated to your monitor.

• type (MonitorType) – The type of the monitor. For more information about type , see the monitor options docs.

datadog_api_client.v1.model.monitor_device_id module

class MonitorDeviceID(arg: None)

class MonitorDeviceID(arg: ModelComposed)

class MonitorDeviceID(*args, **kwargs)

Bases: ModelSimple

ID of the device the Synthetics monitor is running on. Same as SyntheticsDeviceID.

Parameters:

• value (str) – Must be one of [“laptop_large”, “tablet”, “mobile_small”, “chrome.laptop_large”, “chrome.tablet”, “chrome.mobile_small”, “firefox.laptop_large”, “firefox.tablet”, “firefox.mobile_small”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_draft_status module

class MonitorDraftStatus(arg: None)

class MonitorDraftStatus(arg: ModelComposed)

class MonitorDraftStatus(*args, **kwargs)

Bases: ModelSimple

Indicates whether the monitor is in a draft or published state.

draft: The monitor appears as Draft and does not send notifications. published: The monitor is active and evaluates conditions and notify as configured.

This field is in preview. The draft value is only available to customers with the feature enabled.

Parameters:

• value (str) – If omitted defaults to “published”. Must be one of [“draft”, “published”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_formula_and_function_cost_aggregator module

class MonitorFormulaAndFunctionCostAggregator(arg: None)

class MonitorFormulaAndFunctionCostAggregator(arg: ModelComposed)

class MonitorFormulaAndFunctionCostAggregator(*args, **kwargs)

Bases: ModelSimple

Aggregation methods for metric queries.

Parameters:

• value (str) – Must be one of [“avg”, “sum”, “max”, “min”, “last”, “area”, “l2norm”, “percentile”, “stddev”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_formula_and_function_cost_data_source module

class MonitorFormulaAndFunctionCostDataSource(arg: None)

class MonitorFormulaAndFunctionCostDataSource(arg: ModelComposed)

class MonitorFormulaAndFunctionCostDataSource(*args, **kwargs)

Bases: ModelSimple

Data source for cost queries.

Parameters:

• value (str) – Must be one of [“metrics”, “cloud_cost”, “datadog_usage”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_formula_and_function_cost_query_definition module

class MonitorFormulaAndFunctionCostQueryDefinition(arg: None)

class MonitorFormulaAndFunctionCostQueryDefinition(arg: ModelComposed)

class MonitorFormulaAndFunctionCostQueryDefinition(*args, **kwargs)

Bases: ModelNormal

A formula and functions cost query.

Parameters:

• aggregator (MonitorFormulaAndFunctionCostAggregator, optional) – Aggregation methods for metric queries.

• data_source (MonitorFormulaAndFunctionCostDataSource) – Data source for cost queries.

• name (str) – Name of the query for use in formulas.

• query (str) – The monitor query.

datadog_api_client.v1.model.monitor_formula_and_function_event_aggregation module

class MonitorFormulaAndFunctionEventAggregation(arg: None)

class MonitorFormulaAndFunctionEventAggregation(arg: ModelComposed)

class MonitorFormulaAndFunctionEventAggregation(*args, **kwargs)

Bases: ModelSimple

Aggregation methods for event platform queries.

Parameters:

• value (str) – Must be one of [“count”, “cardinality”, “median”, “pc75”, “pc90”, “pc95”, “pc98”, “pc99”, “sum”, “min”, “max”, “avg”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_formula_and_function_event_query_definition module

class MonitorFormulaAndFunctionEventQueryDefinition(arg: None)

class MonitorFormulaAndFunctionEventQueryDefinition(arg: ModelComposed)

class MonitorFormulaAndFunctionEventQueryDefinition(*args, **kwargs)

Bases: ModelNormal

A formula and functions events query.

Parameters:

• compute (MonitorFormulaAndFunctionEventQueryDefinitionCompute) – Compute options.

• data_source (MonitorFormulaAndFunctionEventsDataSource) – Data source for event platform-based queries.

• group_by ([MonitorFormulaAndFunctionEventQueryGroupBy], optional) – Group by options.

• indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.

• name (str) – Name of the query for use in formulas.

• search (MonitorFormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.

datadog_api_client.v1.model.monitor_formula_and_function_event_query_definition_compute module

class MonitorFormulaAndFunctionEventQueryDefinitionCompute(arg: None)

class MonitorFormulaAndFunctionEventQueryDefinitionCompute(arg: ModelComposed)

class MonitorFormulaAndFunctionEventQueryDefinitionCompute(*args, **kwargs)

Bases: ModelNormal

Compute options.

Parameters:

• aggregation (MonitorFormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.

• interval (int, optional) – A time interval in milliseconds.

• metric (str, optional) – Measurable attribute to compute.

datadog_api_client.v1.model.monitor_formula_and_function_event_query_definition_search module

class MonitorFormulaAndFunctionEventQueryDefinitionSearch(arg: None)

class MonitorFormulaAndFunctionEventQueryDefinitionSearch(arg: ModelComposed)

class MonitorFormulaAndFunctionEventQueryDefinitionSearch(*args, **kwargs)

Bases: ModelNormal

Search options.

Parameters:

query (str) – Events search string.

datadog_api_client.v1.model.monitor_formula_and_function_event_query_group_by module

class MonitorFormulaAndFunctionEventQueryGroupBy(arg: None)

class MonitorFormulaAndFunctionEventQueryGroupBy(arg: ModelComposed)

class MonitorFormulaAndFunctionEventQueryGroupBy(*args, **kwargs)

Bases: ModelNormal

List of objects used to group by.

Parameters:

• facet (str) – Event facet.

• limit (int, optional) – Number of groups to return.

• sort (MonitorFormulaAndFunctionEventQueryGroupBySort, optional) – Options for sorting group by results.

datadog_api_client.v1.model.monitor_formula_and_function_event_query_group_by_sort module

class MonitorFormulaAndFunctionEventQueryGroupBySort(arg: None)

class MonitorFormulaAndFunctionEventQueryGroupBySort(arg: ModelComposed)

class MonitorFormulaAndFunctionEventQueryGroupBySort(*args, **kwargs)

Bases: ModelNormal

Options for sorting group by results.

Parameters:

• aggregation (MonitorFormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.

• metric (str, optional) – Metric used for sorting group by results.

• order (QuerySortOrder, optional) – Direction of sort.

datadog_api_client.v1.model.monitor_formula_and_function_events_data_source module

class MonitorFormulaAndFunctionEventsDataSource(arg: None)

class MonitorFormulaAndFunctionEventsDataSource(arg: ModelComposed)

class MonitorFormulaAndFunctionEventsDataSource(*args, **kwargs)

Bases: ModelSimple

Data source for event platform-based queries.

Parameters:

• value (str) – Must be one of [“rum”, “ci_pipelines”, “ci_tests”, “audit”, “events”, “logs”, “spans”, “database_queries”, “network”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_formula_and_function_query_definition module

class MonitorFormulaAndFunctionQueryDefinition(arg: None)

class MonitorFormulaAndFunctionQueryDefinition(arg: ModelComposed)

class MonitorFormulaAndFunctionQueryDefinition(*args, **kwargs)

Bases: ModelComposed

A formula and function query.

Parameters:

• compute (MonitorFormulaAndFunctionEventQueryDefinitionCompute) – Compute options.

• data_source (MonitorFormulaAndFunctionEventsDataSource) – Data source for event platform-based queries.

• group_by ([MonitorFormulaAndFunctionEventQueryGroupBy], optional) – Group by options.

• indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.

• name (str) – Name of the query for use in formulas.

• search (MonitorFormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.

• aggregator (MonitorFormulaAndFunctionCostAggregator, optional) – Aggregation methods for metric queries.

• query (str) – The monitor query.

datadog_api_client.v1.model.monitor_group_search_response module

class MonitorGroupSearchResponse(arg: None)

class MonitorGroupSearchResponse(arg: ModelComposed)

class MonitorGroupSearchResponse(*args, **kwargs)

Bases: ModelNormal

The response of a monitor group search.

Parameters:

• counts (MonitorGroupSearchResponseCounts, optional) – The counts of monitor groups per different criteria.

• groups ([MonitorGroupSearchResult], optional) – The list of found monitor groups.

• metadata (MonitorSearchResponseMetadata, optional) – Metadata about the response.

datadog_api_client.v1.model.monitor_group_search_response_counts module

class MonitorGroupSearchResponseCounts(arg: None)

class MonitorGroupSearchResponseCounts(arg: ModelComposed)

class MonitorGroupSearchResponseCounts(*args, **kwargs)

Bases: ModelNormal

The counts of monitor groups per different criteria.

Parameters:

• status (MonitorSearchCount, optional) – Search facets.

• type (MonitorSearchCount, optional) – Search facets.

datadog_api_client.v1.model.monitor_group_search_result module

class MonitorGroupSearchResult(arg: None)

class MonitorGroupSearchResult(arg: ModelComposed)

class MonitorGroupSearchResult(*args, **kwargs)

Bases: ModelNormal

A single monitor group search result.

Parameters:

• group (str, optional) – The name of the group.

• group_tags ([str], optional) – The list of tags of the monitor group.

• last_nodata_ts (int, optional) – Latest timestamp the monitor group was in NO_DATA state.

• last_triggered_ts (int, none_type, optional) – Latest timestamp the monitor group triggered.

• monitor_id (int, optional) – The ID of the monitor.

• monitor_name (str, optional) – The name of the monitor.

• status (MonitorOverallStates, optional) – The different states your monitor can be in.

datadog_api_client.v1.model.monitor_options module

class MonitorOptions(arg: None)

class MonitorOptions(arg: ModelComposed)

class MonitorOptions(*args, **kwargs)

Bases: ModelNormal

List of options associated with your monitor.

Parameters:

• aggregation (MonitorOptionsAggregation, optional) – Type of aggregation performed in the monitor query.

• device_ids ([MonitorDeviceID], optional) – IDs of the device the Synthetics monitor is running on. Deprecated.

• enable_logs_sample (bool, optional) – Whether or not to send a log sample when the log monitor triggers.

• enable_samples (bool, optional) – Whether or not to send a list of samples when the monitor triggers. This is only used by CI Test and Pipeline monitors.

• escalation_message (str, optional) – We recommend using the is_renotify , block in the original message instead. A message to include with a re-notification. Supports the @username notification we allow elsewhere. Not applicable if renotify_interval is None.

• evaluation_delay (int, none_type, optional) – Time (in seconds) to delay evaluation, as a non-negative integer. For example, if the value is set to 300 (5min), the timeframe is set to last_5m and the time is 7:00, the monitor evaluates data from 6:50 to 6:55. This is useful for AWS CloudWatch and other backfilled metrics to ensure the monitor always has data during evaluation.

• group_retention_duration (str, optional) – The time span after which groups with missing data are dropped from the monitor state. The minimum value is one hour, and the maximum value is 72 hours. Example values are: “60m”, “1h”, and “2d”. This option is only available for APM Trace Analytics, Audit Trail, CI, Error Tracking, Event, Logs, and RUM monitors.

• groupby_simple_monitor (bool, optional) – Whether the log alert monitor triggers a single alert or multiple alerts when any group breaches a threshold. Use notify_by instead. Deprecated.

• include_tags (bool, optional) –

  A Boolean indicating whether notifications from this monitor automatically inserts its triggering tags into the title.

  Examples

  • If True , [Triggered on {host:h1}] Monitor Title

  • If False , [Triggered] Monitor Title

• locked (bool, optional) – Whether or not the monitor is locked (only editable by creator and admins). Use restricted_roles instead. Deprecated.

• min_failure_duration (int, none_type, optional) – How long the test should be in failure before alerting (integer, number of seconds, max 7200).

• min_location_failed (int, none_type, optional) – The minimum number of locations in failure at the same time during at least one moment in the min_failure_duration period ( min_location_failed and min_failure_duration are part of the advanced alerting rules - integer, >= 1).

• new_group_delay (int, none_type, optional) –

  Time (in seconds) to skip evaluations for new groups.

  For example, this option can be used to skip evaluations for new hosts while they initialize.

  Must be a non negative integer.

• new_host_delay (int, none_type, optional) –

  Time (in seconds) to allow a host to boot and applications to fully start before starting the evaluation of monitor results. Should be a non negative integer.

  Use new_group_delay instead. Deprecated.

• no_data_timeframe (int, none_type, optional) – The number of minutes before a monitor notifies after data stops reporting. Datadog recommends at least 2x the monitor timeframe for query alerts or 2 minutes for service checks. If omitted, 2x the evaluation timeframe is used for query alerts, and 24 hours is used for service checks.

• notification_preset_name (MonitorOptionsNotificationPresets, optional) – Toggles the display of additional content sent in the monitor notification.

• notify_audit (bool, optional) – A Boolean indicating whether tagged users is notified on changes to this monitor.

• notify_by ([str], optional) – Controls what granularity a monitor alerts on. Only available for monitors with groupings. For instance, a monitor grouped by cluster , namespace , and pod can be configured to only notify on each new cluster violating the alert conditions by setting notify_by to ["cluster"]. Tags mentioned in notify_by must be a subset of the grouping tags in the query. For example, a query grouped by cluster and namespace cannot notify on region. Setting notify_by to ["*"] configures the monitor to notify as a simple-alert.

• notify_no_data (bool, optional) – A Boolean indicating whether this monitor notifies when data stops reporting. Defaults to false.

• on_missing_data (OnMissingDataOption, optional) – Controls how groups or monitors are treated if an evaluation does not return any data points. The default option results in different behavior depending on the monitor query type. For monitors using Count queries, an empty monitor evaluation is treated as 0 and is compared to the threshold conditions. For monitors using any query type other than Count, for example Gauge, Measure, or Rate, the monitor shows the last known status. This option is only available for APM Trace Analytics, Audit Trail, CI, Error Tracking, Event, Logs, and RUM monitors.

• renotify_interval (int, none_type, optional) – The number of minutes after the last notification before a monitor re-notifies on the current status. It only re-notifies if it’s not resolved.

• renotify_occurrences (int, none_type, optional) – The number of times re-notification messages should be sent on the current status at the provided re-notification interval.

• renotify_statuses ([MonitorRenotifyStatusType], none_type, optional) – The types of monitor statuses for which re-notification messages are sent. Default: null if renotify_interval is null. If renotify_interval is set, defaults to renotify on Alert and No Data.

• require_full_window (bool, optional) – A Boolean indicating whether this monitor needs a full window of data before it’s evaluated. We highly recommend you set this to false for sparse metrics, otherwise some evaluations are skipped. Default is false. This setting only applies to metric monitors.

• scheduling_options (MonitorOptionsSchedulingOptions, optional) – Configuration options for scheduling.

• silenced ({str: (int, none_type,)}, optional) – Information about the downtime applied to the monitor. Only shows v1 downtimes. Deprecated.

• synthetics_check_id (str, none_type, optional) – ID of the corresponding Synthetic check. Deprecated.

• threshold_windows (MonitorThresholdWindowOptions, optional) – Alerting time window options.

• thresholds (MonitorThresholds, optional) – List of the different monitor threshold available.

• timeout_h (int, none_type, optional) – The number of hours of the monitor not reporting data before it automatically resolves from a triggered state. The minimum allowed value is 0 hours. The maximum allowed value is 24 hours.

• variables ([MonitorFormulaAndFunctionQueryDefinition], optional) – List of requests that can be used in the monitor query. This feature is currently in beta.

datadog_api_client.v1.model.monitor_options_aggregation module

class MonitorOptionsAggregation(arg: None)

class MonitorOptionsAggregation(arg: ModelComposed)

class MonitorOptionsAggregation(*args, **kwargs)

Bases: ModelNormal

Type of aggregation performed in the monitor query.

Parameters:

• group_by (str, optional) – Group to break down the monitor on.

• metric (str, optional) – Metric name used in the monitor.

• type (str, optional) – Metric type used in the monitor.

datadog_api_client.v1.model.monitor_options_custom_schedule module

class MonitorOptionsCustomSchedule(arg: None)

class MonitorOptionsCustomSchedule(arg: ModelComposed)

class MonitorOptionsCustomSchedule(*args, **kwargs)

Bases: ModelNormal

Configuration options for the custom schedule. This feature is in private beta.

Parameters:

recurrences ([MonitorOptionsCustomScheduleRecurrence], optional) – Array of custom schedule recurrences.

datadog_api_client.v1.model.monitor_options_custom_schedule_recurrence module

class MonitorOptionsCustomScheduleRecurrence(arg: None)

class MonitorOptionsCustomScheduleRecurrence(arg: ModelComposed)

class MonitorOptionsCustomScheduleRecurrence(*args, **kwargs)

Bases: ModelNormal

Configuration for a recurrence set on the monitor options for custom schedule.

Parameters:

• rrule (str, optional) – Defines the recurrence rule (RRULE) for a given schedule.

• start (str, optional) – Defines the start date and time of the recurring schedule.

• timezone (str, optional) – Defines the timezone the schedule runs on.

datadog_api_client.v1.model.monitor_options_notification_presets module

class MonitorOptionsNotificationPresets(arg: None)

class MonitorOptionsNotificationPresets(arg: ModelComposed)

class MonitorOptionsNotificationPresets(*args, **kwargs)

Bases: ModelSimple

Toggles the display of additional content sent in the monitor notification.

Parameters:

• value (str) – If omitted defaults to “show_all”. Must be one of [“show_all”, “hide_query”, “hide_handles”, “hide_all”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_options_scheduling_options module

class MonitorOptionsSchedulingOptions(arg: None)

class MonitorOptionsSchedulingOptions(arg: ModelComposed)

class MonitorOptionsSchedulingOptions(*args, **kwargs)

Bases: ModelNormal

Configuration options for scheduling.

Parameters:

• custom_schedule (MonitorOptionsCustomSchedule, optional) – Configuration options for the custom schedule. This feature is in private beta.

• evaluation_window (MonitorOptionsSchedulingOptionsEvaluationWindow, optional) – Configuration options for the evaluation window. If hour_starts is set, no other fields may be set. Otherwise, day_starts and month_starts must be set together.

datadog_api_client.v1.model.monitor_options_scheduling_options_evaluation_window module

class MonitorOptionsSchedulingOptionsEvaluationWindow(arg: None)

class MonitorOptionsSchedulingOptionsEvaluationWindow(arg: ModelComposed)

class MonitorOptionsSchedulingOptionsEvaluationWindow(*args, **kwargs)

Bases: ModelNormal

Configuration options for the evaluation window. If hour_starts is set, no other fields may be set. Otherwise, day_starts and month_starts must be set together.

Parameters:

• day_starts (str, optional) – The time of the day at which a one day cumulative evaluation window starts.

• hour_starts (int, optional) – The minute of the hour at which a one hour cumulative evaluation window starts.

• month_starts (int, optional) – The day of the month at which a one month cumulative evaluation window starts.

• timezone (str, optional) – The timezone of the time of the day of the cumulative evaluation window start.

datadog_api_client.v1.model.monitor_overall_states module

class MonitorOverallStates(arg: None)

class MonitorOverallStates(arg: ModelComposed)

class MonitorOverallStates(*args, **kwargs)

Bases: ModelSimple

The different states your monitor can be in.

Parameters:

• value (str) – Must be one of [“Alert”, “Ignored”, “No Data”, “OK”, “Skipped”, “Unknown”, “Warn”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_renotify_status_type module

class MonitorRenotifyStatusType(arg: None)

class MonitorRenotifyStatusType(arg: ModelComposed)

class MonitorRenotifyStatusType(*args, **kwargs)

Bases: ModelSimple

The different statuses for which renotification is supported.

Parameters:

• value (str) – Must be one of [“alert”, “warn”, “no data”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_search_count module

class MonitorSearchCount(arg: None)

class MonitorSearchCount(arg: ModelComposed)

class MonitorSearchCount(*args, **kwargs)

Bases: ModelSimple

Search facets.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_search_count_item module

class MonitorSearchCountItem(arg: None)

class MonitorSearchCountItem(arg: ModelComposed)

class MonitorSearchCountItem(*args, **kwargs)

Bases: ModelNormal

A facet item.

Parameters:

• count (int, optional) – The number of found monitors with the listed value.

• name (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) – The facet value.

datadog_api_client.v1.model.monitor_search_response module

class MonitorSearchResponse(arg: None)

class MonitorSearchResponse(arg: ModelComposed)

class MonitorSearchResponse(*args, **kwargs)

Bases: ModelNormal

The response form a monitor search.

Parameters:

• counts (MonitorSearchResponseCounts, optional) – The counts of monitors per different criteria.

• metadata (MonitorSearchResponseMetadata, optional) – Metadata about the response.

• monitors ([MonitorSearchResult], optional) – The list of found monitors.

datadog_api_client.v1.model.monitor_search_response_counts module

class MonitorSearchResponseCounts(arg: None)

class MonitorSearchResponseCounts(arg: ModelComposed)

class MonitorSearchResponseCounts(*args, **kwargs)

Bases: ModelNormal

The counts of monitors per different criteria.

Parameters:

• muted (MonitorSearchCount, optional) – Search facets.

• status (MonitorSearchCount, optional) – Search facets.

• tag (MonitorSearchCount, optional) – Search facets.

• type (MonitorSearchCount, optional) – Search facets.

datadog_api_client.v1.model.monitor_search_response_metadata module

class MonitorSearchResponseMetadata(arg: None)

class MonitorSearchResponseMetadata(arg: ModelComposed)

class MonitorSearchResponseMetadata(*args, **kwargs)

Bases: ModelNormal

Metadata about the response.

Parameters:

• page (int, optional) – The page to start paginating from.

• page_count (int, optional) – The number of pages.

• per_page (int, optional) – The number of monitors to return per page.

• total_count (int, optional) – The total number of monitors.

datadog_api_client.v1.model.monitor_search_result module

class MonitorSearchResult(arg: None)

class MonitorSearchResult(arg: ModelComposed)

class MonitorSearchResult(*args, **kwargs)

Bases: ModelNormal

Holds search results.

Parameters:

• classification (str, optional) – Classification of the monitor.

• creator (Creator, optional) – Object describing the creator of the shared element.

• id (int, optional) – ID of the monitor.

• last_triggered_ts (int, none_type, optional) – Latest timestamp the monitor triggered.

• metrics ([str], optional) – Metrics used by the monitor.

• name (str, optional) – The monitor name.

• notifications ([MonitorSearchResultNotification], optional) – The notification triggered by the monitor.

• org_id (int, optional) – The ID of the organization.

• quality_issues ([str], optional) – Quality issues detected with the monitor.

• query (str, optional) – The monitor query.

• scopes ([str], optional) – The scope(s) to which the downtime applies, for example host:app2. Provide multiple scopes as a comma-separated list, for example env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes (that is env:dev AND env:prod ), NOT any of them.

• status (MonitorOverallStates, optional) – The different states your monitor can be in.

• tags ([str], optional) – Tags associated with the monitor.

• type (MonitorType, optional) –

  The type of the monitor. For more information about type , see the monitor options docs.

datadog_api_client.v1.model.monitor_search_result_notification module

class MonitorSearchResultNotification(arg: None)

class MonitorSearchResultNotification(arg: ModelComposed)

class MonitorSearchResultNotification(*args, **kwargs)

Bases: ModelNormal

A notification triggered by the monitor.

Parameters:

• handle (str, optional) – The email address that received the notification.

• name (str, optional) – The username receiving the notification

datadog_api_client.v1.model.monitor_state module

class MonitorState(arg: None)

class MonitorState(arg: ModelComposed)

class MonitorState(*args, **kwargs)

Bases: ModelNormal

Wrapper object with the different monitor states.

Parameters:

groups ({str: (MonitorStateGroup,)}, optional) – Dictionary where the keys are groups (comma separated lists of tags) and the values are the list of groups your monitor is broken down on.

datadog_api_client.v1.model.monitor_state_group module

class MonitorStateGroup(arg: None)

class MonitorStateGroup(arg: ModelComposed)

class MonitorStateGroup(*args, **kwargs)

Bases: ModelNormal

Monitor state for a single group.

Parameters:

• last_nodata_ts (int, optional) – Latest timestamp the monitor was in NO_DATA state.

• last_notified_ts (int, optional) – Latest timestamp of the notification sent for this monitor group.

• last_resolved_ts (int, optional) – Latest timestamp the monitor group was resolved.

• last_triggered_ts (int, optional) – Latest timestamp the monitor group triggered.

• name (str, optional) – The name of the monitor.

• status (MonitorOverallStates, optional) – The different states your monitor can be in.

datadog_api_client.v1.model.monitor_summary_widget_definition module

class MonitorSummaryWidgetDefinition(arg: None)

class MonitorSummaryWidgetDefinition(arg: ModelComposed)

class MonitorSummaryWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The monitor summary widget displays a summary view of all your Datadog monitors, or a subset based on a query. Only available on FREE layout dashboards.

Parameters:

• color_preference (WidgetColorPreference, optional) – Which color to use on the widget.

• count (int, optional) – The number of monitors to display. Deprecated.

• display_format (WidgetMonitorSummaryDisplayFormat, optional) – What to display on the widget.

• hide_zero_counts (bool, optional) – Whether to show counts of 0 or not.

• query (str) – Query to filter the monitors with.

• show_last_triggered (bool, optional) – Whether to show the time that has elapsed since the monitor/group triggered.

• show_priority (bool, optional) – Whether to show the priorities column.

• sort (WidgetMonitorSummarySort, optional) – Widget sorting methods.

• start (int, optional) – The start of the list. Typically 0. Deprecated.

• summary_type (WidgetSummaryType, optional) – Which summary type should be used.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (MonitorSummaryWidgetDefinitionType) – Type of the monitor summary widget.

datadog_api_client.v1.model.monitor_summary_widget_definition_type module

class MonitorSummaryWidgetDefinitionType(arg: None)

class MonitorSummaryWidgetDefinitionType(arg: ModelComposed)

class MonitorSummaryWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the monitor summary widget.

Parameters:

• value (str) – If omitted defaults to “manage_status”. Must be one of [“manage_status”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_threshold_window_options module

class MonitorThresholdWindowOptions(arg: None)

class MonitorThresholdWindowOptions(arg: ModelComposed)

class MonitorThresholdWindowOptions(*args, **kwargs)

Bases: ModelNormal

Alerting time window options.

Parameters:

• recovery_window (str, none_type, optional) – Describes how long an anomalous metric must be normal before the alert recovers.

• trigger_window (str, none_type, optional) – Describes how long a metric must be anomalous before an alert triggers.

datadog_api_client.v1.model.monitor_thresholds module

class MonitorThresholds(arg: None)

class MonitorThresholds(arg: ModelComposed)

class MonitorThresholds(*args, **kwargs)

Bases: ModelNormal

List of the different monitor threshold available.

Parameters:

• critical (float, optional) – The monitor CRITICAL threshold.

• critical_recovery (float, none_type, optional) – The monitor CRITICAL recovery threshold.

• ok (float, none_type, optional) – The monitor OK threshold.

• unknown (float, none_type, optional) – The monitor UNKNOWN threshold.

• warning (float, none_type, optional) – The monitor WARNING threshold.

• warning_recovery (float, none_type, optional) – The monitor WARNING recovery threshold.

datadog_api_client.v1.model.monitor_type module

class MonitorType(arg: None)

class MonitorType(arg: ModelComposed)

class MonitorType(*args, **kwargs)

Bases: ModelSimple

The type of the monitor. For more information about type, see the [monitor options](https://docs.datadoghq.com/monitors/guide/monitor_api_options/) docs.

Parameters:

• value (str) – Must be one of [“composite”, “event alert”, “log alert”, “metric alert”, “process alert”, “query alert”, “rum alert”, “service check”, “synthetics alert”, “trace-analytics alert”, “slo alert”, “event-v2 alert”, “audit alert”, “ci-pipelines alert”, “ci-tests alert”, “error-tracking alert”, “database-monitoring alert”, “network-performance alert”, “cost alert”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monitor_update_request module

class MonitorUpdateRequest(arg: None)

class MonitorUpdateRequest(arg: ModelComposed)

class MonitorUpdateRequest(*args, **kwargs)

Bases: ModelNormal

Object describing a monitor update request.

Parameters:

• created (datetime, optional) – Timestamp of the monitor creation.

• creator (Creator, optional) – Object describing the creator of the shared element.

• deleted (datetime, none_type, optional) – Whether or not the monitor is deleted. (Always null )

• draft_status (MonitorDraftStatus, optional) –

  Indicates whether the monitor is in a draft or published state.

  draft : The monitor appears as Draft and does not send notifications. published : The monitor is active and evaluates conditions and notify as configured.

  This field is in preview. The draft value is only available to customers with the feature enabled.

• id (int, optional) – ID of this monitor.

• message (str, optional) – A message to include with notifications for this monitor.

• modified (datetime, optional) – Last timestamp when the monitor was edited.

• multi (bool, optional) – Whether or not the monitor is broken down on different groups.

• name (str, optional) – The monitor name.

• options (MonitorOptions, optional) – List of options associated with your monitor.

• overall_state (MonitorOverallStates, optional) – The different states your monitor can be in.

• priority (int, none_type, optional) – Integer from 1 (high) to 5 (low) indicating alert severity.

• query (str, optional) – The monitor query.

• restricted_roles ([str], none_type, optional) –

  A list of unique role identifiers to define which roles are allowed to edit the monitor. The unique identifiers for all roles can be pulled from the Roles API and are located in the data.id field. Editing a monitor includes any updates to the monitor configuration, monitor deletion, and muting of the monitor for any amount of time. You can use the Restriction Policies API to manage write authorization for individual monitors by teams and users, in addition to roles.

• state (MonitorState, optional) – Wrapper object with the different monitor states.

• tags ([str], optional) – Tags associated to your monitor.

• type (MonitorType, optional) –

  The type of the monitor. For more information about type , see the monitor options docs.

datadog_api_client.v1.model.monthly_usage_attribution_body module

class MonthlyUsageAttributionBody(arg: None)

class MonthlyUsageAttributionBody(arg: ModelComposed)

class MonthlyUsageAttributionBody(*args, **kwargs)

Bases: ModelNormal

Usage Summary by tag for a given organization.

Parameters:

• month (datetime, optional) – Datetime in ISO-8601 format, UTC, precise to month: [YYYY-MM].

• org_name (str, optional) – The name of the organization.

• public_id (str, optional) – The organization public ID.

• region (str, optional) – The region of the Datadog instance that the organization belongs to.

• tag_config_source (str, optional) – The source of the usage attribution tag configuration and the selected tags in the format <source_org_name>:::<selected tag 1>///<selected tag 2>///<selected tag 3>.

• tags (UsageAttributionTagNames, none_type, optional) –

  Tag keys and values.

  A null value here means that the requested tag breakdown cannot be applied because it does not match the tags configured for usage attribution. In this scenario the API returns the total usage, not broken down by tags.

• updated_at (datetime, optional) – Datetime of the most recent update to the usage values.

• values (MonthlyUsageAttributionValues, optional) – Fields in Usage Summary by tag(s). The following values have been deprecated : estimated_indexed_spans_usage , estimated_indexed_spans_percentage , estimated_ingested_spans_usage , estimated_ingested_spans_percentage.

datadog_api_client.v1.model.monthly_usage_attribution_metadata module

class MonthlyUsageAttributionMetadata(arg: None)

class MonthlyUsageAttributionMetadata(arg: ModelComposed)

class MonthlyUsageAttributionMetadata(*args, **kwargs)

Bases: ModelNormal

The object containing document metadata.

Parameters:

• aggregates (UsageAttributionAggregates, optional) – An array of available aggregates.

• pagination (MonthlyUsageAttributionPagination, optional) – The metadata for the current pagination.

datadog_api_client.v1.model.monthly_usage_attribution_pagination module

class MonthlyUsageAttributionPagination(arg: None)

class MonthlyUsageAttributionPagination(arg: ModelComposed)

class MonthlyUsageAttributionPagination(*args, **kwargs)

Bases: ModelNormal

The metadata for the current pagination.

Parameters:

next_record_id (str, none_type, optional) – The cursor to use to get the next results, if any. To make the next request, use the same parameters with the addition of the next_record_id.

datadog_api_client.v1.model.monthly_usage_attribution_response module

class MonthlyUsageAttributionResponse(arg: None)

class MonthlyUsageAttributionResponse(arg: ModelComposed)

class MonthlyUsageAttributionResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the monthly Usage Summary by tag(s).

Parameters:

• metadata (MonthlyUsageAttributionMetadata, optional) – The object containing document metadata.

• usage ([MonthlyUsageAttributionBody], optional) – Get usage summary by tag(s).

datadog_api_client.v1.model.monthly_usage_attribution_supported_metrics module

class MonthlyUsageAttributionSupportedMetrics(arg: None)

class MonthlyUsageAttributionSupportedMetrics(arg: ModelComposed)

class MonthlyUsageAttributionSupportedMetrics(*args, **kwargs)

Bases: ModelSimple

Supported metrics for monthly usage attribution requests.

Parameters:

• value (str) – Must be one of [“api_usage”, “api_percentage”, “apm_fargate_usage”, “apm_fargate_percentage”, “appsec_fargate_usage”, “appsec_fargate_percentage”, “apm_host_usage”, “apm_host_percentage”, “apm_usm_usage”, “apm_usm_percentage”, “appsec_usage”, “appsec_percentage”, “asm_serverless_traced_invocations_usage”, “asm_serverless_traced_invocations_percentage”, “browser_usage”, “browser_percentage”, “ci_visibility_itr_usage”, “ci_visibility_itr_percentage”, “cloud_siem_usage”, “cloud_siem_percentage”, “code_security_host_usage”, “code_security_host_percentage”, “container_excl_agent_usage”, “container_excl_agent_percentage”, “container_usage”, “container_percentage”, “cspm_containers_percentage”, “cspm_containers_usage”, “cspm_hosts_percentage”, “cspm_hosts_usage”, “custom_timeseries_usage”, “custom_timeseries_percentage”, “custom_ingested_timeseries_usage”, “custom_ingested_timeseries_percentage”, “cws_containers_percentage”, “cws_containers_usage”, “cws_fargate_task_percentage”, “cws_fargate_task_usage”, “cws_hosts_percentage”, “cws_hosts_usage”, “data_jobs_monitoring_usage”, “data_jobs_monitoring_percentage”, “data_stream_monitoring_usage”, “data_stream_monitoring_percentage”, “dbm_hosts_percentage”, “dbm_hosts_usage”, “dbm_queries_percentage”, “dbm_queries_usage”, “error_tracking_usage”, “error_tracking_percentage”, “estimated_indexed_spans_usage”, “estimated_indexed_spans_percentage”, “estimated_ingested_spans_usage”, “estimated_ingested_spans_percentage”, “fargate_usage”, “fargate_percentage”, “functions_usage”, “functions_percentage”, “incident_management_monthly_active_users_usage”, “incident_management_monthly_active_users_percentage”, “infra_host_usage”, “infra_host_percentage”, “invocations_usage”, “invocations_percentage”, “lambda_traced_invocations_usage”, “lambda_traced_invocations_percentage”, “llm_observability_usage”, “llm_observability_percentage”, “mobile_app_testing_percentage”, “mobile_app_testing_usage”, “ndm_netflow_usage”, “ndm_netflow_percentage”, “network_device_wireless_usage”, “network_device_wireless_percentage”, “npm_host_usage”, “npm_host_percentage”, “obs_pipeline_bytes_usage”, “obs_pipeline_bytes_percentage”, “obs_pipelines_vcpu_usage”, “obs_pipelines_vcpu_percentage”, “online_archive_usage”, “online_archive_percentage”, “product_analytics_session_usage”, “product_analytics_session_percentage”, “profiled_container_usage”, “profiled_container_percentage”, “profiled_fargate_usage”, “profiled_fargate_percentage”, “profiled_host_usage”, “profiled_host_percentage”, “published_app_usage”, “published_app_percentage”, “serverless_apps_usage”, “serverless_apps_percentage”, “snmp_usage”, “snmp_percentage”, “universal_service_monitoring_usage”, “universal_service_monitoring_percentage”, “vuln_management_hosts_usage”, “vuln_management_hosts_percentage”, “sds_scanned_bytes_usage”, “sds_scanned_bytes_percentage”, “ci_test_indexed_spans_usage”, “ci_test_indexed_spans_percentage”, “ingested_logs_bytes_usage”, “ingested_logs_bytes_percentage”, “ci_pipeline_indexed_spans_usage”, “ci_pipeline_indexed_spans_percentage”, “indexed_spans_usage”, “indexed_spans_percentage”, “custom_event_usage”, “custom_event_percentage”, “logs_indexed_custom_retention_usage”, “logs_indexed_custom_retention_percentage”, “logs_indexed_360day_usage”, “logs_indexed_360day_percentage”, “logs_indexed_180day_usage”, “logs_indexed_180day_percentage”, “logs_indexed_90day_usage”, “logs_indexed_90day_percentage”, “logs_indexed_60day_usage”, “logs_indexed_60day_percentage”, “logs_indexed_45day_usage”, “logs_indexed_45day_percentage”, “logs_indexed_30day_usage”, “logs_indexed_30day_percentage”, “logs_indexed_15day_usage”, “logs_indexed_15day_percentage”, “logs_indexed_7day_usage”, “logs_indexed_7day_percentage”, “logs_indexed_3day_usage”, “logs_indexed_3day_percentage”, “logs_indexed_1day_usage”, “logs_indexed_1day_percentage”, “rum_ingested_usage”, “rum_ingested_percentage”, “rum_investigate_usage”, “rum_investigate_percentage”, “rum_replay_sessions_usage”, “rum_replay_sessions_percentage”, “rum_session_replay_add_on_usage”, “rum_session_replay_add_on_percentage”, “rum_browser_mobile_sessions_usage”, “rum_browser_mobile_sessions_percentage”, “ingested_spans_bytes_usage”, “ingested_spans_bytes_percentage”, “siem_analyzed_logs_add_on_usage”, “siem_analyzed_logs_add_on_percentage”, “siem_ingested_bytes_usage”, “siem_ingested_bytes_percentage”, “workflow_executions_usage”, “workflow_executions_percentage”, “sca_fargate_usage”, “sca_fargate_percentage”, “*”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.monthly_usage_attribution_values module

class MonthlyUsageAttributionValues(arg: None)

class MonthlyUsageAttributionValues(arg: ModelComposed)

class MonthlyUsageAttributionValues(*args, **kwargs)

Bases: ModelNormal

Fields in Usage Summary by tag(s). The following values have been deprecated : estimated_indexed_spans_usage , estimated_indexed_spans_percentage , estimated_ingested_spans_usage , estimated_ingested_spans_percentage.

Parameters:

• api_percentage (float, optional) – The percentage of synthetic API test usage by tag(s).

• api_usage (float, optional) – The synthetic API test usage by tag(s).

• apm_fargate_percentage (float, optional) – The percentage of APM ECS Fargate task usage by tag(s).

• apm_fargate_usage (float, optional) – The APM ECS Fargate task usage by tag(s).

• apm_host_percentage (float, optional) – The percentage of APM host usage by tag(s).

• apm_host_usage (float, optional) – The APM host usage by tag(s).

• apm_usm_percentage (float, optional) – The percentage of APM and Universal Service Monitoring host usage by tag(s).

• apm_usm_usage (float, optional) – The APM and Universal Service Monitoring host usage by tag(s).

• appsec_fargate_percentage (float, optional) – The percentage of Application Security Monitoring ECS Fargate task usage by tag(s).

• appsec_fargate_usage (float, optional) – The Application Security Monitoring ECS Fargate task usage by tag(s).

• appsec_percentage (float, optional) – The percentage of Application Security Monitoring host usage by tag(s).

• appsec_usage (float, optional) – The Application Security Monitoring host usage by tag(s).

• asm_serverless_traced_invocations_percentage (float, optional) – The percentage of Application Security Monitoring Serverless traced invocations usage by tag(s).

• asm_serverless_traced_invocations_usage (float, optional) – The Application Security Monitoring Serverless traced invocations usage by tag(s).

• browser_percentage (float, optional) – The percentage of synthetic browser test usage by tag(s).

• browser_usage (float, optional) – The synthetic browser test usage by tag(s).

• ci_pipeline_indexed_spans_percentage (float, optional) – The percentage of CI Pipeline Indexed Spans usage by tag(s).

• ci_pipeline_indexed_spans_usage (float, optional) – The total CI Pipeline Indexed Spans usage by tag(s).

• ci_test_indexed_spans_percentage (float, optional) – The percentage of CI Test Indexed Spans usage by tag(s).

• ci_test_indexed_spans_usage (float, optional) – The total CI Test Indexed Spans usage by tag(s).

• ci_visibility_itr_percentage (float, optional) – The percentage of Git committers for Intelligent Test Runner usage by tag(s).

• ci_visibility_itr_usage (float, optional) – The Git committers for Intelligent Test Runner usage by tag(s).

• cloud_siem_percentage (float, optional) – The percentage of Cloud Security Information and Event Management usage by tag(s).

• cloud_siem_usage (float, optional) – The Cloud Security Information and Event Management usage by tag(s).

• code_security_host_percentage (float, optional) – The percentage of Code Security host usage by tags.

• code_security_host_usage (float, optional) – The Code Security host usage by tags.

• container_excl_agent_percentage (float, optional) – The percentage of container usage without the Datadog Agent by tag(s).

• container_excl_agent_usage (float, optional) – The container usage without the Datadog Agent by tag(s).

• container_percentage (float, optional) – The percentage of container usage by tag(s).

• container_usage (float, optional) – The container usage by tag(s).

• cspm_containers_percentage (float, optional) – The percentage of Cloud Security Management Pro container usage by tag(s).

• cspm_containers_usage (float, optional) – The Cloud Security Management Pro container usage by tag(s).

• cspm_hosts_percentage (float, optional) – The percentage of Cloud Security Management Pro host usage by tag(s).

• cspm_hosts_usage (float, optional) – The Cloud Security Management Pro host usage by tag(s).

• custom_event_percentage (float, optional) – The percentage of Custom Events usage by tag(s).

• custom_event_usage (float, optional) – The total Custom Events usage by tag(s).

• custom_ingested_timeseries_percentage (float, optional) – The percentage of ingested custom metrics usage by tag(s).

• custom_ingested_timeseries_usage (float, optional) – The ingested custom metrics usage by tag(s).

• custom_timeseries_percentage (float, optional) – The percentage of indexed custom metrics usage by tag(s).

• custom_timeseries_usage (float, optional) – The indexed custom metrics usage by tag(s).

• cws_containers_percentage (float, optional) – The percentage of Cloud Workload Security container usage by tag(s).

• cws_containers_usage (float, optional) – The Cloud Workload Security container usage by tag(s).

• cws_fargate_task_percentage (float, optional) – The percentage of Cloud Workload Security Fargate task usage by tag(s).

• cws_fargate_task_usage (float, optional) – The Cloud Workload Security Fargate task usage by tag(s).

• cws_hosts_percentage (float, optional) – The percentage of Cloud Workload Security host usage by tag(s).

• cws_hosts_usage (float, optional) – The Cloud Workload Security host usage by tag(s).

• data_jobs_monitoring_usage (float, optional) – The Data Jobs Monitoring usage by tag(s).

• data_stream_monitoring_usage (float, optional) – The Data Stream Monitoring usage by tag(s).

• dbm_hosts_percentage (float, optional) – The percentage of Database Monitoring host usage by tag(s).

• dbm_hosts_usage (float, optional) – The Database Monitoring host usage by tag(s).

• dbm_queries_percentage (float, optional) – The percentage of Database Monitoring queries usage by tag(s).

• dbm_queries_usage (float, optional) – The Database Monitoring queries usage by tag(s).

• error_tracking_percentage (float, optional) – The percentage of error tracking events usage by tag(s).

• error_tracking_usage (float, optional) – The error tracking events usage by tag(s).

• estimated_indexed_spans_percentage (float, optional) – The percentage of estimated indexed spans usage by tag(s).

• estimated_indexed_spans_usage (float, optional) – The estimated indexed spans usage by tag(s).

• estimated_ingested_spans_percentage (float, optional) – The percentage of estimated ingested spans usage by tag(s).

• estimated_ingested_spans_usage (float, optional) – The estimated ingested spans usage by tag(s).

• fargate_percentage (float, optional) – The percentage of Fargate usage by tags.

• fargate_usage (float, optional) – The Fargate usage by tags.

• functions_percentage (float, optional) – The percentage of Lambda function usage by tag(s).

• functions_usage (float, optional) – The Lambda function usage by tag(s).

• incident_management_monthly_active_users_percentage (float, optional) – The percentage of Incident Management monthly active users usage by tag(s).

• incident_management_monthly_active_users_usage (float, optional) – The Incident Management monthly active users usage by tag(s).

• indexed_spans_percentage (float, optional) – The percentage of APM Indexed Spans usage by tag(s).

• indexed_spans_usage (float, optional) – The total APM Indexed Spans usage by tag(s).

• infra_host_percentage (float, optional) – The percentage of infrastructure host usage by tag(s).

• infra_host_usage (float, optional) – The infrastructure host usage by tag(s).

• ingested_logs_bytes_percentage (float, optional) – The percentage of Ingested Logs usage by tag(s).

• ingested_logs_bytes_usage (float, optional) – The total Ingested Logs usage by tag(s).

• ingested_spans_bytes_percentage (float, optional) – The percentage of APM Ingested Spans usage by tag(s).

• ingested_spans_bytes_usage (float, optional) – The total APM Ingested Spans usage by tag(s).

• invocations_percentage (float, optional) – The percentage of Lambda invocation usage by tag(s).

• invocations_usage (float, optional) – The Lambda invocation usage by tag(s).

• lambda_traced_invocations_percentage (float, optional) – The percentage of Serverless APM usage by tag(s).

• lambda_traced_invocations_usage (float, optional) – The Serverless APM usage by tag(s).

• llm_observability_percentage (float, optional) – The percentage of LLM Observability usage by tag(s).

• llm_observability_usage (float, optional) – The LLM Observability usage by tag(s).

• logs_indexed_15day_percentage (float, optional) – The percentage of Indexed Logs (15-day Retention) usage by tag(s).

• logs_indexed_15day_usage (float, optional) – The total Indexed Logs (15-day Retention) usage by tag(s).

• logs_indexed_180day_percentage (float, optional) – The percentage of Indexed Logs (180-day Retention) usage by tag(s).

• logs_indexed_180day_usage (float, optional) – The total Indexed Logs (180-day Retention) usage by tag(s).

• logs_indexed_1day_percentage (float, optional) – The percentage of Indexed Logs (1-day Retention) usage by tag(s).

• logs_indexed_1day_usage (float, optional) – The total Indexed Logs (1-day Retention) usage by tag(s).

• logs_indexed_30day_percentage (float, optional) – The percentage of Indexed Logs (30-day Retention) usage by tag(s).

• logs_indexed_30day_usage (float, optional) – The total Indexed Logs (30-day Retention) usage by tag(s).

• logs_indexed_360day_percentage (float, optional) – The percentage of Indexed Logs (360-day Retention) usage by tag(s).

• logs_indexed_360day_usage (float, optional) – The total Indexed Logs (360-day Retention) usage by tag(s).

• logs_indexed_3day_percentage (float, optional) – The percentage of Indexed Logs (3-day Retention) usage by tag(s).

• logs_indexed_3day_usage (float, optional) – The total Indexed Logs (3-day Retention) usage by tag(s).

• logs_indexed_45day_percentage (float, optional) – The percentage of Indexed Logs (45-day Retention) usage by tag(s).

• logs_indexed_45day_usage (float, optional) – The total Indexed Logs (45-day Retention) usage by tag(s).

• logs_indexed_60day_percentage (float, optional) – The percentage of Indexed Logs (60-day Retention) usage by tag(s).

• logs_indexed_60day_usage (float, optional) – The total Indexed Logs (60-day Retention) usage by tag(s).

• logs_indexed_7day_percentage (float, optional) – The percentage of Indexed Logs (7-day Retention) usage by tag(s).

• logs_indexed_7day_usage (float, optional) – The total Indexed Logs (7-day Retention) usage by tag(s).

• logs_indexed_90day_percentage (float, optional) – The percentage of Indexed Logs (90-day Retention) usage by tag(s).

• logs_indexed_90day_usage (float, optional) – The total Indexed Logs (90-day Retention) usage by tag(s).

• logs_indexed_custom_retention_percentage (float, optional) – The percentage of Indexed Logs (Custom Retention) usage by tag(s).

• logs_indexed_custom_retention_usage (float, optional) – The total Indexed Logs (Custom Retention) usage by tag(s).

• mobile_app_testing_percentage (float, optional) – The percentage of Synthetic mobile application test usage by tag(s).

• mobile_app_testing_usage (float, optional) – The Synthetic mobile application test usage by tag(s).

• ndm_netflow_percentage (float, optional) – The percentage of Network Device Monitoring NetFlow usage by tag(s).

• ndm_netflow_usage (float, optional) – The Network Device Monitoring NetFlow usage by tag(s).

• network_device_wireless_percentage (float, optional) – The percentage of network device wireless usage by tag(s).

• network_device_wireless_usage (float, optional) – The network device wireless usage by tag(s).

• npm_host_percentage (float, optional) – The percentage of network host usage by tag(s).

• npm_host_usage (float, optional) – The network host usage by tag(s).

• obs_pipeline_bytes_percentage (float, optional) – The percentage of observability pipeline bytes usage by tag(s).

• obs_pipeline_bytes_usage (float, optional) – The observability pipeline bytes usage by tag(s).

• obs_pipelines_vcpu_percentage (float, optional) – The percentage of observability pipeline per core usage by tag(s).

• obs_pipelines_vcpu_usage (float, optional) – The observability pipeline per core usage by tag(s).

• online_archive_percentage (float, optional) – The percentage of online archive usage by tag(s).

• online_archive_usage (float, optional) – The online archive usage by tag(s).

• product_analytics_session_percentage (float, optional) – The percentage of Product Analytics session usage by tag(s).

• product_analytics_session_usage (float, optional) – The Product Analytics session usage by tag(s).

• profiled_container_percentage (float, optional) – The percentage of profiled container usage by tag(s).

• profiled_container_usage (float, optional) – The profiled container usage by tag(s).

• profiled_fargate_percentage (float, optional) – The percentage of profiled Fargate task usage by tag(s).

• profiled_fargate_usage (float, optional) – The profiled Fargate task usage by tag(s).

• profiled_host_percentage (float, optional) – The percentage of profiled hosts usage by tag(s).

• profiled_host_usage (float, optional) – The profiled hosts usage by tag(s).

• published_app_percentage (float, optional) – The percentage of published application usage by tag(s).

• published_app_usage (float, optional) – The published application usage by tag(s).

• rum_browser_mobile_sessions_percentage (float, optional) – The percentage of RUM Browser and Mobile usage by tag(s).

• rum_browser_mobile_sessions_usage (float, optional) – The total RUM Browser and Mobile usage by tag(s).

• rum_ingested_percentage (float, optional) – The percentage of RUM Ingested usage by tag(s).

• rum_ingested_usage (float, optional) – The total RUM Ingested usage by tag(s).

• rum_investigate_percentage (float, optional) – The percentage of RUM Investigate usage by tag(s).

• rum_investigate_usage (float, optional) – The total RUM Investigate usage by tag(s).

• rum_replay_sessions_percentage (float, optional) – The percentage of RUM Session Replay usage by tag(s).

• rum_replay_sessions_usage (float, optional) – The total RUM Session Replay usage by tag(s).

• rum_session_replay_add_on_percentage (float, optional) – The percentage of RUM Session Replay Add-On usage by tag(s).

• rum_session_replay_add_on_usage (float, optional) – The total RUM Session Replay Add-On usage by tag(s).

• sca_fargate_percentage (float, optional) – The percentage of Software Composition Analysis Fargate task usage by tag(s).

• sca_fargate_usage (float, optional) – The total Software Composition Analysis Fargate task usage by tag(s).

• sds_scanned_bytes_percentage (float, optional) – The percentage of Sensitive Data Scanner usage by tag(s).

• sds_scanned_bytes_usage (float, optional) – The total Sensitive Data Scanner usage by tag(s).

• serverless_apps_percentage (float, optional) – The percentage of Serverless Apps usage by tag(s).

• serverless_apps_usage (float, optional) – The total Serverless Apps usage by tag(s).

• siem_analyzed_logs_add_on_percentage (float, optional) – The percentage of log events analyzed by Cloud SIEM usage by tag(s).

• siem_analyzed_logs_add_on_usage (float, optional) – The log events analyzed by Cloud SIEM usage by tag(s).

• siem_ingested_bytes_percentage (float, optional) – The percentage of SIEM usage by tag(s).

• siem_ingested_bytes_usage (float, optional) – The total SIEM usage by tag(s).

• snmp_percentage (float, optional) – The percentage of network device usage by tag(s).

• snmp_usage (float, optional) – The network device usage by tag(s).

• universal_service_monitoring_percentage (float, optional) – The percentage of universal service monitoring usage by tag(s).

• universal_service_monitoring_usage (float, optional) – The universal service monitoring usage by tag(s).

• vuln_management_hosts_percentage (float, optional) – The percentage of Application Vulnerability Management usage by tag(s).

• vuln_management_hosts_usage (float, optional) – The Application Vulnerability Management usage by tag(s).

• workflow_executions_percentage (float, optional) – The percentage of workflow executions usage by tag(s).

• workflow_executions_usage (float, optional) – The total workflow executions usage by tag(s).

datadog_api_client.v1.model.note_widget_definition module

class NoteWidgetDefinition(arg: None)

class NoteWidgetDefinition(arg: ModelComposed)

class NoteWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The notes and links widget is similar to free text widget, but allows for more formatting options.

Parameters:

• background_color (str, optional) – Background color of the note.

• content (str) – Content of the note.

• font_size (str, optional) – Size of the text.

• has_padding (bool, optional) – Whether to add padding or not.

• show_tick (bool, optional) – Whether to show a tick or not.

• text_align (WidgetTextAlign, optional) – How to align the text on the widget.

• tick_edge (WidgetTickEdge, optional) – Define how you want to align the text on the widget.

• tick_pos (str, optional) – Where to position the tick on an edge.

• type (NoteWidgetDefinitionType) – Type of the note widget.

• vertical_align (WidgetVerticalAlign, optional) – Vertical alignment.

datadog_api_client.v1.model.note_widget_definition_type module

class NoteWidgetDefinitionType(arg: None)

class NoteWidgetDefinitionType(arg: ModelComposed)

class NoteWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the note widget.

Parameters:

• value (str) – If omitted defaults to “note”. Must be one of [“note”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notebook_absolute_time module

class NotebookAbsoluteTime(arg: None)

class NotebookAbsoluteTime(arg: ModelComposed)

class NotebookAbsoluteTime(*args, **kwargs)

Bases: ModelNormal

Absolute timeframe.

Parameters:

• end (datetime) – The end time.

• live (bool, optional) – Indicates whether the timeframe should be shifted to end at the current time.

• start (datetime) – The start time.

datadog_api_client.v1.model.notebook_author module

class NotebookAuthor(arg: None)

class NotebookAuthor(arg: ModelComposed)

class NotebookAuthor(*args, **kwargs)

Bases: ModelNormal

Attributes of user object returned by the API.

Parameters:

• created_at (datetime, optional) – Creation time of the user.

• disabled (bool, optional) – Whether the user is disabled.

• email (str, optional) – Email of the user.

• handle (str, optional) – Handle of the user.

• icon (str, optional) – URL of the user’s icon.

• name (str, none_type, optional) – Name of the user.

• status (str, optional) – Status of the user.

• title (str, none_type, optional) – Title of the user.

• verified (bool, optional) – Whether the user is verified.

datadog_api_client.v1.model.notebook_cell_create_request module

class NotebookCellCreateRequest(arg: None)

class NotebookCellCreateRequest(arg: ModelComposed)

class NotebookCellCreateRequest(*args, **kwargs)

Bases: ModelNormal

The description of a notebook cell create request.

Parameters:

• attributes (NotebookCellCreateRequestAttributes) – The attributes of a notebook cell in create cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

• type (NotebookCellResourceType) – Type of the Notebook Cell resource.

additional_properties_type = None

datadog_api_client.v1.model.notebook_cell_create_request_attributes module

class NotebookCellCreateRequestAttributes(arg: None)

class NotebookCellCreateRequestAttributes(arg: ModelComposed)

class NotebookCellCreateRequestAttributes(*args, **kwargs)

Bases: ModelComposed

The attributes of a notebook cell in create cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

Parameters:

• definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_cell_resource_type module

class NotebookCellResourceType(arg: None)

class NotebookCellResourceType(arg: ModelComposed)

class NotebookCellResourceType(*args, **kwargs)

Bases: ModelSimple

Type of the Notebook Cell resource.

Parameters:

• value (str) – If omitted defaults to “notebook_cells”. Must be one of [“notebook_cells”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notebook_cell_response module

class NotebookCellResponse(arg: None)

class NotebookCellResponse(arg: ModelComposed)

class NotebookCellResponse(*args, **kwargs)

Bases: ModelNormal

The description of a notebook cell response.

Parameters:

• attributes (NotebookCellResponseAttributes) –

  The attributes of a notebook cell response. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

• id (str) – Notebook cell ID.

• type (NotebookCellResourceType) – Type of the Notebook Cell resource.

datadog_api_client.v1.model.notebook_cell_response_attributes module

class NotebookCellResponseAttributes(arg: None)

class NotebookCellResponseAttributes(arg: ModelComposed)

class NotebookCellResponseAttributes(*args, **kwargs)

Bases: ModelComposed

The attributes of a notebook cell response. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

Parameters:

• definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_cell_time module

class NotebookCellTime(arg: None)

class NotebookCellTime(arg: ModelComposed)

class NotebookCellTime(*args, **kwargs)

Bases: ModelComposed

Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

Parameters:

• live_span (WidgetLiveSpan) – The available timeframes depend on the widget you are using.

• end (datetime) – The end time.

• live (bool, optional) – Indicates whether the timeframe should be shifted to end at the current time.

• start (datetime) – The start time.

datadog_api_client.v1.model.notebook_cell_update_request module

class NotebookCellUpdateRequest(arg: None)

class NotebookCellUpdateRequest(arg: ModelComposed)

class NotebookCellUpdateRequest(*args, **kwargs)

Bases: ModelNormal

The description of a notebook cell update request.

Parameters:

• attributes (NotebookCellUpdateRequestAttributes) –

  The attributes of a notebook cell in update cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

• id (str) – Notebook cell ID.

• type (NotebookCellResourceType) – Type of the Notebook Cell resource.

datadog_api_client.v1.model.notebook_cell_update_request_attributes module

class NotebookCellUpdateRequestAttributes(arg: None)

class NotebookCellUpdateRequestAttributes(arg: ModelComposed)

class NotebookCellUpdateRequestAttributes(*args, **kwargs)

Bases: ModelComposed

The attributes of a notebook cell in update cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

Parameters:

• definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_create_data module

class NotebookCreateData(arg: None)

class NotebookCreateData(arg: ModelComposed)

class NotebookCreateData(*args, **kwargs)

Bases: ModelNormal

The data for a notebook create request.

Parameters:

• attributes (NotebookCreateDataAttributes) – The data attributes of a notebook.

• type (NotebookResourceType) – Type of the Notebook resource.

datadog_api_client.v1.model.notebook_create_data_attributes module

class NotebookCreateDataAttributes(arg: None)

class NotebookCreateDataAttributes(arg: ModelComposed)

class NotebookCreateDataAttributes(*args, **kwargs)

Bases: ModelNormal

The data attributes of a notebook.

Parameters:

• cells ([NotebookCellCreateRequest]) – List of cells to display in the notebook.

• metadata (NotebookMetadata, optional) – Metadata associated with the notebook.

• name (str) – The name of the notebook.

• status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.

• time (NotebookGlobalTime) – Notebook global timeframe.

datadog_api_client.v1.model.notebook_create_request module

class NotebookCreateRequest(arg: None)

class NotebookCreateRequest(arg: ModelComposed)

class NotebookCreateRequest(*args, **kwargs)

Bases: ModelNormal

The description of a notebook create request.

Parameters:

data (NotebookCreateData) – The data for a notebook create request.

datadog_api_client.v1.model.notebook_distribution_cell_attributes module

class NotebookDistributionCellAttributes(arg: None)

class NotebookDistributionCellAttributes(arg: ModelComposed)

class NotebookDistributionCellAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook distribution cell.

Parameters:

• definition (DistributionWidgetDefinition) – The Distribution visualization is another way of showing metrics aggregated across one or several tags, such as hosts. Unlike the heat map, a distribution graph’s x-axis is quantity rather than time.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_global_time module

class NotebookGlobalTime(arg: None)

class NotebookGlobalTime(arg: ModelComposed)

class NotebookGlobalTime(*args, **kwargs)

Bases: ModelComposed

Notebook global timeframe.

Parameters:

• live_span (WidgetLiveSpan) – The available timeframes depend on the widget you are using.

• end (datetime) – The end time.

• live (bool, optional) – Indicates whether the timeframe should be shifted to end at the current time.

• start (datetime) – The start time.

datadog_api_client.v1.model.notebook_graph_size module

class NotebookGraphSize(arg: None)

class NotebookGraphSize(arg: ModelComposed)

class NotebookGraphSize(*args, **kwargs)

Bases: ModelSimple

The size of the graph.

Parameters:

• value (str) – Must be one of [“xs”, “s”, “m”, “l”, “xl”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notebook_heat_map_cell_attributes module

class NotebookHeatMapCellAttributes(arg: None)

class NotebookHeatMapCellAttributes(arg: ModelComposed)

class NotebookHeatMapCellAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook heatmap cell.

Parameters:

• definition (HeatMapWidgetDefinition) – The heat map visualization shows metrics aggregated across many tags, such as hosts. The more hosts that have a particular value, the darker that square is.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_log_stream_cell_attributes module

class NotebookLogStreamCellAttributes(arg: None)

class NotebookLogStreamCellAttributes(arg: ModelComposed)

class NotebookLogStreamCellAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook log_stream cell.

Parameters:

• definition (LogStreamWidgetDefinition) – The Log Stream displays a log flow matching the defined query. Only available on FREE layout dashboards.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_markdown_cell_attributes module

class NotebookMarkdownCellAttributes(arg: None)

class NotebookMarkdownCellAttributes(arg: ModelComposed)

class NotebookMarkdownCellAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook markdown cell.

Parameters:

definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with Markdown , which enables the use of headings, subheadings, links, images, lists, and code blocks.

datadog_api_client.v1.model.notebook_markdown_cell_definition module

class NotebookMarkdownCellDefinition(arg: None)

class NotebookMarkdownCellDefinition(arg: ModelComposed)

class NotebookMarkdownCellDefinition(*args, **kwargs)

Bases: ModelNormal

Text in a notebook is formatted with Markdown , which enables the use of headings, subheadings, links, images, lists, and code blocks.

Parameters:

• text (str) – The markdown content.

• type (NotebookMarkdownCellDefinitionType) – Type of the markdown cell.

datadog_api_client.v1.model.notebook_markdown_cell_definition_type module

class NotebookMarkdownCellDefinitionType(arg: None)

class NotebookMarkdownCellDefinitionType(arg: ModelComposed)

class NotebookMarkdownCellDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the markdown cell.

Parameters:

• value (str) – If omitted defaults to “markdown”. Must be one of [“markdown”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notebook_metadata module

class NotebookMetadata(arg: None)

class NotebookMetadata(arg: ModelComposed)

class NotebookMetadata(*args, **kwargs)

Bases: ModelNormal

Metadata associated with the notebook.

Parameters:

• is_template (bool, optional) – Whether or not the notebook is a template.

• take_snapshots (bool, optional) – Whether or not the notebook takes snapshot image backups of the notebook’s fixed-time graphs.

• type (NotebookMetadataType, none_type, optional) – Metadata type of the notebook.

datadog_api_client.v1.model.notebook_metadata_type module

class NotebookMetadataType(arg: None)

class NotebookMetadataType(arg: ModelComposed)

class NotebookMetadataType(*args, **kwargs)

Bases: ModelSimple

Metadata type of the notebook.

Parameters:

• value (str) – Must be one of [“postmortem”, “runbook”, “investigation”, “documentation”, “report”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notebook_relative_time module

class NotebookRelativeTime(arg: None)

class NotebookRelativeTime(arg: ModelComposed)

class NotebookRelativeTime(*args, **kwargs)

Bases: ModelNormal

Relative timeframe.

Parameters:

live_span (WidgetLiveSpan) – The available timeframes depend on the widget you are using.

datadog_api_client.v1.model.notebook_resource_type module

class NotebookResourceType(arg: None)

class NotebookResourceType(arg: ModelComposed)

class NotebookResourceType(*args, **kwargs)

Bases: ModelSimple

Type of the Notebook resource.

Parameters:

• value (str) – If omitted defaults to “notebooks”. Must be one of [“notebooks”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notebook_response module

class NotebookResponse(arg: None)

class NotebookResponse(arg: ModelComposed)

class NotebookResponse(*args, **kwargs)

Bases: ModelNormal

The description of a notebook response.

Parameters:

data (NotebookResponseData, optional) – The data for a notebook.

datadog_api_client.v1.model.notebook_response_data module

class NotebookResponseData(arg: None)

class NotebookResponseData(arg: ModelComposed)

class NotebookResponseData(*args, **kwargs)

Bases: ModelNormal

The data for a notebook.

Parameters:

• attributes (NotebookResponseDataAttributes) – The attributes of a notebook.

• id (int) – Unique notebook ID, assigned when you create the notebook.

• type (NotebookResourceType) – Type of the Notebook resource.

datadog_api_client.v1.model.notebook_response_data_attributes module

class NotebookResponseDataAttributes(arg: None)

class NotebookResponseDataAttributes(arg: ModelComposed)

class NotebookResponseDataAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook.

Parameters:

• author (NotebookAuthor, optional) – Attributes of user object returned by the API.

• cells ([NotebookCellResponse]) – List of cells to display in the notebook.

• created (datetime, optional) – UTC time stamp for when the notebook was created.

• metadata (NotebookMetadata, optional) – Metadata associated with the notebook.

• modified (datetime, optional) – UTC time stamp for when the notebook was last modified.

• name (str) – The name of the notebook.

• status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.

• time (NotebookGlobalTime) – Notebook global timeframe.

datadog_api_client.v1.model.notebook_split_by module

class NotebookSplitBy(arg: None)

class NotebookSplitBy(arg: ModelComposed)

class NotebookSplitBy(*args, **kwargs)

Bases: ModelNormal

Object describing how to split the graph to display multiple visualizations per request.

Parameters:

• keys ([str]) – Keys to split on.

• tags ([str]) – Tags to split on.

datadog_api_client.v1.model.notebook_status module

class NotebookStatus(arg: None)

class NotebookStatus(arg: ModelComposed)

class NotebookStatus(*args, **kwargs)

Bases: ModelSimple

Publication status of the notebook. For now, always “published”.

Parameters:

• value (str) – If omitted defaults to “published”. Must be one of [“published”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notebook_timeseries_cell_attributes module

class NotebookTimeseriesCellAttributes(arg: None)

class NotebookTimeseriesCellAttributes(arg: ModelComposed)

class NotebookTimeseriesCellAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook timeseries cell.

Parameters:

• definition (TimeseriesWidgetDefinition) – The timeseries visualization allows you to display the evolution of one or more metrics, log events, or Indexed Spans over time.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_toplist_cell_attributes module

class NotebookToplistCellAttributes(arg: None)

class NotebookToplistCellAttributes(arg: ModelComposed)

class NotebookToplistCellAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook toplist cell.

Parameters:

• definition (ToplistWidgetDefinition) – The top list visualization enables you to display a list of Tag value like hostname or service with the most or least of any metric value, such as highest consumers of CPU, hosts with the least disk space, etc.

• graph_size (NotebookGraphSize, optional) – The size of the graph.

• split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.

• time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

datadog_api_client.v1.model.notebook_update_cell module

class NotebookUpdateCell(arg: None)

class NotebookUpdateCell(arg: ModelComposed)

class NotebookUpdateCell(*args, **kwargs)

Bases: ModelComposed

Updating a notebook can either insert new cell(s) or update existing cell(s) by including the cell id. To delete existing cell(s), simply omit it from the list of cells.

Parameters:

• attributes (NotebookCellCreateRequestAttributes) – The attributes of a notebook cell in create cell request. Valid cell types are markdown, timeseries, toplist, heatmap, distribution, log_stream. [More information on each graph visualization type.](https://docs.datadoghq.com/dashboards/widgets/)

• type (NotebookCellResourceType) – Type of the Notebook Cell resource.

• id (str) – Notebook cell ID.

datadog_api_client.v1.model.notebook_update_data module

class NotebookUpdateData(arg: None)

class NotebookUpdateData(arg: ModelComposed)

class NotebookUpdateData(*args, **kwargs)

Bases: ModelNormal

The data for a notebook update request.

Parameters:

• attributes (NotebookUpdateDataAttributes) – The data attributes of a notebook.

• type (NotebookResourceType) – Type of the Notebook resource.

datadog_api_client.v1.model.notebook_update_data_attributes module

class NotebookUpdateDataAttributes(arg: None)

class NotebookUpdateDataAttributes(arg: ModelComposed)

class NotebookUpdateDataAttributes(*args, **kwargs)

Bases: ModelNormal

The data attributes of a notebook.

Parameters:

• cells ([NotebookUpdateCell]) – List of cells to display in the notebook.

• metadata (NotebookMetadata, optional) – Metadata associated with the notebook.

• name (str) – The name of the notebook.

• status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.

• time (NotebookGlobalTime) – Notebook global timeframe.

datadog_api_client.v1.model.notebook_update_request module

class NotebookUpdateRequest(arg: None)

class NotebookUpdateRequest(arg: ModelComposed)

class NotebookUpdateRequest(*args, **kwargs)

Bases: ModelNormal

The description of a notebook update request.

Parameters:

data (NotebookUpdateData) – The data for a notebook update request.

datadog_api_client.v1.model.notebooks_response module

class NotebooksResponse(arg: None)

class NotebooksResponse(arg: ModelComposed)

class NotebooksResponse(*args, **kwargs)

Bases: ModelNormal

Notebooks get all response.

Parameters:

• data ([NotebooksResponseData], optional) – List of notebook definitions.

• meta (NotebooksResponseMeta, optional) – Searches metadata returned by the API.

datadog_api_client.v1.model.notebooks_response_data module

class NotebooksResponseData(arg: None)

class NotebooksResponseData(arg: ModelComposed)

class NotebooksResponseData(*args, **kwargs)

Bases: ModelNormal

The data for a notebook in get all response.

Parameters:

• attributes (NotebooksResponseDataAttributes) – The attributes of a notebook in get all response.

• id (int) – Unique notebook ID, assigned when you create the notebook.

• type (NotebookResourceType) – Type of the Notebook resource.

datadog_api_client.v1.model.notebooks_response_data_attributes module

class NotebooksResponseDataAttributes(arg: None)

class NotebooksResponseDataAttributes(arg: ModelComposed)

class NotebooksResponseDataAttributes(*args, **kwargs)

Bases: ModelNormal

The attributes of a notebook in get all response.

Parameters:

• author (NotebookAuthor, optional) – Attributes of user object returned by the API.

• cells ([NotebookCellResponse], optional) – List of cells to display in the notebook.

• created (datetime, optional) – UTC time stamp for when the notebook was created.

• metadata (NotebookMetadata, optional) – Metadata associated with the notebook.

• modified (datetime, optional) – UTC time stamp for when the notebook was last modified.

• name (str) – The name of the notebook.

• status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.

• time (NotebookGlobalTime, optional) – Notebook global timeframe.

datadog_api_client.v1.model.notebooks_response_meta module

class NotebooksResponseMeta(arg: None)

class NotebooksResponseMeta(arg: ModelComposed)

class NotebooksResponseMeta(*args, **kwargs)

Bases: ModelNormal

Searches metadata returned by the API.

Parameters:

page (NotebooksResponsePage, optional) – Pagination metadata returned by the API.

datadog_api_client.v1.model.notebooks_response_page module

class NotebooksResponsePage(arg: None)

class NotebooksResponsePage(arg: ModelComposed)

class NotebooksResponsePage(*args, **kwargs)

Bases: ModelNormal

Pagination metadata returned by the API.

Parameters:

• total_count (int, optional) – The total number of notebooks that would be returned if the request was not filtered by start and count parameters.

• total_filtered_count (int, optional) – The total number of notebooks returned.

datadog_api_client.v1.model.notify_end_state module

class NotifyEndState(arg: None)

class NotifyEndState(arg: ModelComposed)

class NotifyEndState(*args, **kwargs)

Bases: ModelSimple

A notification end state.

Parameters:

• value (str) – Must be one of [“alert”, “no data”, “warn”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.notify_end_type module

class NotifyEndType(arg: None)

class NotifyEndType(arg: ModelComposed)

class NotifyEndType(*args, **kwargs)

Bases: ModelSimple

A notification end type.

Parameters:

• value (str) – Must be one of [“canceled”, “expired”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.number_format_unit module

class NumberFormatUnit(arg: None)

class NumberFormatUnit(arg: ModelComposed)

class NumberFormatUnit(*args, **kwargs)

Bases: ModelComposed

Number format unit.

Parameters:

• per_unit_name (str, optional) – The name of the unit per item.

• type (NumberFormatUnitScaleType, optional) – The type of unit scale.

• unit_name (str, optional) – The name of the unit.

• label (str, optional) – The label for the custom unit.

datadog_api_client.v1.model.number_format_unit_canonical module

class NumberFormatUnitCanonical(arg: None)

class NumberFormatUnitCanonical(arg: ModelComposed)

class NumberFormatUnitCanonical(*args, **kwargs)

Bases: ModelNormal

Canonical unit.

Parameters:

• per_unit_name (str, optional) – The name of the unit per item.

• type (NumberFormatUnitScaleType, optional) – The type of unit scale.

• unit_name (str, optional) – The name of the unit.

datadog_api_client.v1.model.number_format_unit_custom module

class NumberFormatUnitCustom(arg: None)

class NumberFormatUnitCustom(arg: ModelComposed)

class NumberFormatUnitCustom(*args, **kwargs)

Bases: ModelNormal

Custom unit.

Parameters:

• label (str, optional) – The label for the custom unit.

• type (NumberFormatUnitCustomType, optional) – The type of custom unit.

datadog_api_client.v1.model.number_format_unit_custom_type module

class NumberFormatUnitCustomType(arg: None)

class NumberFormatUnitCustomType(arg: ModelComposed)

class NumberFormatUnitCustomType(*args, **kwargs)

Bases: ModelSimple

The type of custom unit.

Parameters:

• value (str) – If omitted defaults to “custom_unit_label”. Must be one of [“custom_unit_label”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.number_format_unit_scale module

class NumberFormatUnitScale(arg: None)

class NumberFormatUnitScale(arg: ModelComposed)

class NumberFormatUnitScale(*args, **kwargs)

Bases: ModelNormal

The definition of NumberFormatUnitScale object.

Parameters:

• type (NumberFormatUnitScaleType, optional) – The type of unit scale.

• unit_name (str, optional) – The name of the unit.

datadog_api_client.v1.model.number_format_unit_scale_type module

class NumberFormatUnitScaleType(arg: None)

class NumberFormatUnitScaleType(arg: ModelComposed)

class NumberFormatUnitScaleType(*args, **kwargs)

Bases: ModelSimple

The type of unit scale.

Parameters:

• value (str) – If omitted defaults to “canonical_unit”. Must be one of [“canonical_unit”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.on_missing_data_option module

class OnMissingDataOption(arg: None)

class OnMissingDataOption(arg: ModelComposed)

class OnMissingDataOption(*args, **kwargs)

Bases: ModelSimple

Controls how groups or monitors are treated if an evaluation does not return any data points.

The default option results in different behavior depending on the monitor query type. For monitors using Count queries, an empty monitor evaluation is treated as 0 and is compared to the threshold conditions. For monitors using any query type other than Count, for example Gauge, Measure, or Rate, the monitor shows the last known status. This option is only available for APM Trace Analytics, Audit Trail, CI, Error Tracking, Event, Logs, and RUM monitors.

Parameters:

• value (str) – Must be one of [“default”, “show_no_data”, “show_and_notify_no_data”, “resolve”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.org_downgraded_response module

class OrgDowngradedResponse(arg: None)

class OrgDowngradedResponse(arg: ModelComposed)

class OrgDowngradedResponse(*args, **kwargs)

Bases: ModelNormal

Status of downgrade

Parameters:

message (str, optional) – Information pertaining to the downgraded child organization.

datadog_api_client.v1.model.organization module

class Organization(arg: None)

class Organization(arg: ModelComposed)

class Organization(*args, **kwargs)

Bases: ModelNormal

Create, edit, and manage organizations.

Parameters:

• billing (OrganizationBilling, optional) – A JSON array of billing type. Deprecated.

• created (str, optional) – Date of the organization creation.

• description (str, optional) – Description of the organization.

• name (str, optional) – The name of the child organization, limited to 32 characters.

• public_id (str, optional) – The public_id of the organization you are operating within.

• settings (OrganizationSettings, optional) – A JSON array of settings.

• subscription (OrganizationSubscription, optional) – Subscription definition. Deprecated.

• trial (bool, optional) – Only available for MSP customers. Allows child organizations to be created on a trial plan.

datadog_api_client.v1.model.organization_billing module

class OrganizationBilling(arg: None)

class OrganizationBilling(arg: ModelComposed)

class OrganizationBilling(*args, **kwargs)

Bases: ModelNormal

A JSON array of billing type.

Parameters:

type (str, optional) – The type of billing. Only parent_billing is supported.

datadog_api_client.v1.model.organization_create_body module

class OrganizationCreateBody(arg: None)

class OrganizationCreateBody(arg: ModelComposed)

class OrganizationCreateBody(*args, **kwargs)

Bases: ModelNormal

Object describing an organization to create.

Parameters:

• billing (OrganizationBilling, optional) – A JSON array of billing type. Deprecated.

• name (str) – The name of the new child-organization, limited to 32 characters.

• subscription (OrganizationSubscription, optional) – Subscription definition. Deprecated.

datadog_api_client.v1.model.organization_create_response module

class OrganizationCreateResponse(arg: None)

class OrganizationCreateResponse(arg: ModelComposed)

class OrganizationCreateResponse(*args, **kwargs)

Bases: ModelNormal

Response object for an organization creation.

Parameters:

• api_key (ApiKey, optional) – Datadog API key.

• application_key (ApplicationKey, optional) – An application key with its associated metadata.

• org (Organization, optional) – Create, edit, and manage organizations.

• user (User, optional) – Create, edit, and disable users.

datadog_api_client.v1.model.organization_list_response module

class OrganizationListResponse(arg: None)

class OrganizationListResponse(arg: ModelComposed)

class OrganizationListResponse(*args, **kwargs)

Bases: ModelNormal

Response with the list of organizations.

Parameters:

orgs ([Organization], optional) – Array of organization objects.

datadog_api_client.v1.model.organization_response module

class OrganizationResponse(arg: None)

class OrganizationResponse(arg: ModelComposed)

class OrganizationResponse(*args, **kwargs)

Bases: ModelNormal

Response with an organization.

Parameters:

org (Organization, optional) – Create, edit, and manage organizations.

datadog_api_client.v1.model.organization_settings module

class OrganizationSettings(arg: None)

class OrganizationSettings(arg: ModelComposed)

class OrganizationSettings(*args, **kwargs)

Bases: ModelNormal

A JSON array of settings.

Parameters:

• private_widget_share (bool, optional) – Whether or not the organization users can share widgets outside of Datadog.

• saml (OrganizationSettingsSaml, optional) – Set the boolean property enabled to enable or disable single sign on with SAML. See the SAML documentation for more information about all SAML settings.

• saml_autocreate_access_role (AccessRole, none_type, optional) – The access role of the user. Options are st (standard user), adm (admin user), or ro (read-only user).

• saml_autocreate_users_domains (OrganizationSettingsSamlAutocreateUsersDomains, optional) – Has two properties, enabled (boolean) and domains , which is a list of domains without the @ symbol.

• saml_can_be_enabled (bool, optional) – Whether or not SAML can be enabled for this organization.

• saml_idp_endpoint (str, optional) – Identity provider endpoint for SAML authentication.

• saml_idp_initiated_login (OrganizationSettingsSamlIdpInitiatedLogin, optional) – Has one property enabled (boolean).

• saml_idp_metadata_uploaded (bool, optional) – Whether or not a SAML identity provider metadata file was provided to the Datadog organization.

• saml_login_url (str, optional) – URL for SAML logging.

• saml_strict_mode (OrganizationSettingsSamlStrictMode, optional) – Has one property enabled (boolean).

datadog_api_client.v1.model.organization_settings_saml module

class OrganizationSettingsSaml(arg: None)

class OrganizationSettingsSaml(arg: ModelComposed)

class OrganizationSettingsSaml(*args, **kwargs)

Bases: ModelNormal

Set the boolean property enabled to enable or disable single sign on with SAML. See the SAML documentation for more information about all SAML settings.

Parameters:

enabled (bool, optional) – Whether or not SAML is enabled for this organization.

datadog_api_client.v1.model.organization_settings_saml_autocreate_users_domains module

class OrganizationSettingsSamlAutocreateUsersDomains(arg: None)

class OrganizationSettingsSamlAutocreateUsersDomains(arg: ModelComposed)

class OrganizationSettingsSamlAutocreateUsersDomains(*args, **kwargs)

Bases: ModelNormal

Has two properties, enabled (boolean) and domains , which is a list of domains without the @ symbol.

Parameters:

• domains ([str], optional) – List of domains where the SAML automated user creation is enabled.

• enabled (bool, optional) – Whether or not the automated user creation based on SAML domain is enabled.

datadog_api_client.v1.model.organization_settings_saml_idp_initiated_login module

class OrganizationSettingsSamlIdpInitiatedLogin(arg: None)

class OrganizationSettingsSamlIdpInitiatedLogin(arg: ModelComposed)

class OrganizationSettingsSamlIdpInitiatedLogin(*args, **kwargs)

Bases: ModelNormal

Has one property enabled (boolean).

Parameters:

enabled (bool, optional) – Whether SAML IdP initiated login is enabled, learn more in the SAML documentation.

datadog_api_client.v1.model.organization_settings_saml_strict_mode module

class OrganizationSettingsSamlStrictMode(arg: None)

class OrganizationSettingsSamlStrictMode(arg: ModelComposed)

class OrganizationSettingsSamlStrictMode(*args, **kwargs)

Bases: ModelNormal

Has one property enabled (boolean).

Parameters:

enabled (bool, optional) – Whether or not the SAML strict mode is enabled. If true, all users must log in with SAML. Learn more on the SAML Strict documentation.

datadog_api_client.v1.model.organization_subscription module

class OrganizationSubscription(arg: None)

class OrganizationSubscription(arg: ModelComposed)

class OrganizationSubscription(*args, **kwargs)

Bases: ModelNormal

Subscription definition.

Parameters:

type (str, optional) – The subscription type. Types available are trial , free , and pro.

datadog_api_client.v1.model.pager_duty_service module

class PagerDutyService(arg: None)

class PagerDutyService(arg: ModelComposed)

class PagerDutyService(*args, **kwargs)

Bases: ModelNormal

The PagerDuty service that is available for integration with Datadog.

Parameters:

• service_key (str) – Your service key in PagerDuty.

• service_name (str) – Your service name associated with a service key in PagerDuty.

datadog_api_client.v1.model.pager_duty_service_key module

class PagerDutyServiceKey(arg: None)

class PagerDutyServiceKey(arg: ModelComposed)

class PagerDutyServiceKey(*args, **kwargs)

Bases: ModelNormal

PagerDuty service object key.

Parameters:

service_key (str) – Your service key in PagerDuty.

datadog_api_client.v1.model.pager_duty_service_name module

class PagerDutyServiceName(arg: None)

class PagerDutyServiceName(arg: ModelComposed)

class PagerDutyServiceName(*args, **kwargs)

Bases: ModelNormal

PagerDuty service object name.

Parameters:

service_name (str) – Your service name associated service key in PagerDuty.

datadog_api_client.v1.model.pagination module

class Pagination(arg: None)

class Pagination(arg: ModelComposed)

class Pagination(*args, **kwargs)

Bases: ModelNormal

Pagination object.

Parameters:

• total_count (int, optional) – Total count.

• total_filtered_count (int, optional) – Total count of elements matched by the filter.

datadog_api_client.v1.model.point module

class Point(arg: None)

class Point(arg: ModelComposed)

class Point(*args, **kwargs)

Bases: ModelSimple

Array of timeseries points.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.powerpack_template_variable_contents module

class PowerpackTemplateVariableContents(arg: None)

class PowerpackTemplateVariableContents(arg: ModelComposed)

class PowerpackTemplateVariableContents(*args, **kwargs)

Bases: ModelNormal

Powerpack template variable contents.

Parameters:

• name (str) – The name of the variable.

• prefix (str, optional) – The tag prefix associated with the variable.

• values ([str]) – One or many template variable values within the saved view, which will be unioned together using OR if more than one is specified.

datadog_api_client.v1.model.powerpack_template_variables module

class PowerpackTemplateVariables(arg: None)

class PowerpackTemplateVariables(arg: ModelComposed)

class PowerpackTemplateVariables(*args, **kwargs)

Bases: ModelNormal

Powerpack template variables.

Parameters:

• controlled_by_powerpack ([PowerpackTemplateVariableContents], optional) – Template variables controlled at the powerpack level.

• controlled_externally ([PowerpackTemplateVariableContents], optional) – Template variables controlled by the external resource, such as the dashboard this powerpack is on.

datadog_api_client.v1.model.powerpack_widget_definition module

class PowerpackWidgetDefinition(arg: None)

class PowerpackWidgetDefinition(arg: ModelComposed)

class PowerpackWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The powerpack widget allows you to keep similar graphs together on your timeboard. Each group has a custom header, can hold one to many graphs, and is collapsible.

Parameters:

• background_color (str, optional) – Background color of the powerpack title.

• banner_img (str, optional) – URL of image to display as a banner for the powerpack.

• powerpack_id (str) – UUID of the associated powerpack.

• show_title (bool, optional) – Whether to show the title or not.

• template_variables (PowerpackTemplateVariables, optional) – Powerpack template variables.

• title (str, optional) – Title of the widget.

• type (PowerpackWidgetDefinitionType) – Type of the powerpack widget.

datadog_api_client.v1.model.powerpack_widget_definition_type module

class PowerpackWidgetDefinitionType(arg: None)

class PowerpackWidgetDefinitionType(arg: ModelComposed)

class PowerpackWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the powerpack widget.

Parameters:

• value (str) – If omitted defaults to “powerpack”. Must be one of [“powerpack”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.process_query_definition module

class ProcessQueryDefinition(arg: None)

class ProcessQueryDefinition(arg: ModelComposed)

class ProcessQueryDefinition(*args, **kwargs)

Bases: ModelNormal

The process query to use in the widget.

Parameters:

• filter_by ([str], optional) – List of processes.

• limit (int, optional) – Max number of items in the filter list.

• metric (str) – Your chosen metric.

• search_by (str, optional) – Your chosen search term.

datadog_api_client.v1.model.query_sort_order module

class QuerySortOrder(arg: None)

class QuerySortOrder(arg: ModelComposed)

class QuerySortOrder(*args, **kwargs)

Bases: ModelSimple

Direction of sort.

Parameters:

• value (str) – If omitted defaults to “desc”. Must be one of [“asc”, “desc”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.query_value_widget_definition module

class QueryValueWidgetDefinition(arg: None)

class QueryValueWidgetDefinition(arg: ModelComposed)

class QueryValueWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Query values display the current value of a given metric, APM, or log query.

Parameters:

• autoscale (bool, optional) – Whether to use auto-scaling or not.

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• custom_unit (str, optional) – Display a unit of your choice on the widget.

• precision (int, optional) – Number of decimals to show. If not defined, the widget uses the raw value.

• requests ([QueryValueWidgetRequest]) – Widget definition.

• text_align (WidgetTextAlign, optional) – How to align the text on the widget.

• time (WidgetTime, optional) – Time setting for the widget.

• timeseries_background (TimeseriesBackground, optional) – Set a timeseries on the widget background.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (QueryValueWidgetDefinitionType) – Type of the query value widget.

datadog_api_client.v1.model.query_value_widget_definition_type module

class QueryValueWidgetDefinitionType(arg: None)

class QueryValueWidgetDefinitionType(arg: ModelComposed)

class QueryValueWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the query value widget.

Parameters:

• value (str) – If omitted defaults to “query_value”. Must be one of [“query_value”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.query_value_widget_request module

class QueryValueWidgetRequest(arg: None)

class QueryValueWidgetRequest(arg: ModelComposed)

class QueryValueWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated query value widget.

Parameters:

• aggregator (WidgetAggregator, optional) – Aggregator used for the request.

• apm_query (LogQueryDefinition, optional) – The log query.

• audit_query (LogQueryDefinition, optional) – The log query.

• conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.

• event_query (LogQueryDefinition, optional) – The log query.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – TODO.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

datadog_api_client.v1.model.reference_table_logs_lookup_processor module

class ReferenceTableLogsLookupProcessor(arg: None)

class ReferenceTableLogsLookupProcessor(arg: ModelComposed)

class ReferenceTableLogsLookupProcessor(*args, **kwargs)

Bases: ModelNormal

Note : Reference Tables are in public beta. Use the Lookup Processor to define a mapping between a log attribute and a human readable value saved in a Reference Table. For example, you can use the Lookup Processor to map an internal service ID into a human readable service name. Alternatively, you could also use it to check if the MAC address that just attempted to connect to the production environment belongs to your list of stolen machines.

Parameters:

• is_enabled (bool, optional) – Whether or not the processor is enabled.

• lookup_enrichment_table (str) – Name of the Reference Table for the source attribute and their associated target attribute values.

• name (str, optional) – Name of the processor.

• source (str) – Source attribute used to perform the lookup.

• target (str) – Name of the attribute that contains the corresponding value in the mapping list.

• type (LogsLookupProcessorType) – Type of logs lookup processor.

datadog_api_client.v1.model.resource_provider_config module

class ResourceProviderConfig(arg: None)

class ResourceProviderConfig(arg: ModelComposed)

class ResourceProviderConfig(*args, **kwargs)

Bases: ModelNormal

Configuration settings applied to resources from the specified Azure resource provider.

Parameters:

• metrics_enabled (bool, optional) – Collect metrics for resources from this provider.

• namespace (str, optional) – The provider namespace to apply this configuration to.

datadog_api_client.v1.model.response_meta_attributes module

class ResponseMetaAttributes(arg: None)

class ResponseMetaAttributes(arg: ModelComposed)

class ResponseMetaAttributes(*args, **kwargs)

Bases: ModelNormal

Object describing meta attributes of response.

Parameters:

page (Pagination, optional) – Pagination object.

datadog_api_client.v1.model.run_workflow_widget_definition module

class RunWorkflowWidgetDefinition(arg: None)

class RunWorkflowWidgetDefinition(arg: ModelComposed)

class RunWorkflowWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Run workflow is widget that allows you to run a workflow from a dashboard.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• inputs ([RunWorkflowWidgetInput], optional) – Array of workflow inputs to map to dashboard template variables.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (RunWorkflowWidgetDefinitionType) – Type of the run workflow widget.

• workflow_id (str) – Workflow id.

datadog_api_client.v1.model.run_workflow_widget_definition_type module

class RunWorkflowWidgetDefinitionType(arg: None)

class RunWorkflowWidgetDefinitionType(arg: ModelComposed)

class RunWorkflowWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the run workflow widget.

Parameters:

• value (str) – If omitted defaults to “run_workflow”. Must be one of [“run_workflow”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.run_workflow_widget_input module

class RunWorkflowWidgetInput(arg: None)

class RunWorkflowWidgetInput(arg: ModelComposed)

class RunWorkflowWidgetInput(*args, **kwargs)

Bases: ModelNormal

Object to map a dashboard template variable to a workflow input.

Parameters:

• name (str) – Name of the workflow input.

• value (str) – Dashboard template variable. Can be suffixed with ‘.value’ or ‘.key’.

datadog_api_client.v1.model.scatter_plot_request module

class ScatterPlotRequest(arg: None)

class ScatterPlotRequest(arg: ModelComposed)

class ScatterPlotRequest(*args, **kwargs)

Bases: ModelNormal

Updated scatter plot.

Parameters:

• aggregator (ScatterplotWidgetAggregator, optional) – Aggregator used for the request.

• apm_query (LogQueryDefinition, optional) – The log query.

• event_query (LogQueryDefinition, optional) – The log query.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Query definition.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

datadog_api_client.v1.model.scatter_plot_widget_definition module

class ScatterPlotWidgetDefinition(arg: None)

class ScatterPlotWidgetDefinition(arg: ModelComposed)

class ScatterPlotWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The scatter plot visualization allows you to graph a chosen scope over two different metrics with their respective aggregation.

Parameters:

• color_by_groups ([str], optional) – List of groups used for colors.

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• requests (ScatterPlotWidgetDefinitionRequests) – Widget definition.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (ScatterPlotWidgetDefinitionType) – Type of the scatter plot widget.

• xaxis (WidgetAxis, optional) – Axis controls for the widget.

• yaxis (WidgetAxis, optional) – Axis controls for the widget.

datadog_api_client.v1.model.scatter_plot_widget_definition_requests module

class ScatterPlotWidgetDefinitionRequests(arg: None)

class ScatterPlotWidgetDefinitionRequests(arg: ModelComposed)

class ScatterPlotWidgetDefinitionRequests(*args, **kwargs)

Bases: ModelNormal

Widget definition.

Parameters:

• table (ScatterplotTableRequest, optional) – Scatterplot request containing formulas and functions.

• x (ScatterPlotRequest, optional) – Updated scatter plot.

• y (ScatterPlotRequest, optional) – Updated scatter plot.

datadog_api_client.v1.model.scatter_plot_widget_definition_type module

class ScatterPlotWidgetDefinitionType(arg: None)

class ScatterPlotWidgetDefinitionType(arg: ModelComposed)

class ScatterPlotWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the scatter plot widget.

Parameters:

• value (str) – If omitted defaults to “scatterplot”. Must be one of [“scatterplot”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.scatterplot_dimension module

class ScatterplotDimension(arg: None)

class ScatterplotDimension(arg: ModelComposed)

class ScatterplotDimension(*args, **kwargs)

Bases: ModelSimple

Dimension of the Scatterplot.

Parameters:

• value (str) – Must be one of [“x”, “y”, “radius”, “color”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.scatterplot_table_request module

class ScatterplotTableRequest(arg: None)

class ScatterplotTableRequest(arg: ModelComposed)

class ScatterplotTableRequest(*args, **kwargs)

Bases: ModelNormal

Scatterplot request containing formulas and functions.

Parameters:

• formulas ([ScatterplotWidgetFormula], optional) – List of Scatterplot formulas that operate on queries.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

datadog_api_client.v1.model.scatterplot_widget_aggregator module

class ScatterplotWidgetAggregator(arg: None)

class ScatterplotWidgetAggregator(arg: ModelComposed)

class ScatterplotWidgetAggregator(*args, **kwargs)

Bases: ModelSimple

Aggregator used for the request.

Parameters:

• value (str) – Must be one of [“avg”, “last”, “max”, “min”, “sum”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.scatterplot_widget_formula module

class ScatterplotWidgetFormula(arg: None)

class ScatterplotWidgetFormula(arg: ModelComposed)

class ScatterplotWidgetFormula(*args, **kwargs)

Bases: ModelNormal

Formula to be used in a Scatterplot widget query.

Parameters:

• alias (str, optional) – Expression alias.

• dimension (ScatterplotDimension) – Dimension of the Scatterplot.

• formula (str) – String expression built from queries, formulas, and functions.

datadog_api_client.v1.model.search_service_level_objective module

class SearchServiceLevelObjective(arg: None)

class SearchServiceLevelObjective(arg: ModelComposed)

class SearchServiceLevelObjective(*args, **kwargs)

Bases: ModelNormal

A service level objective data container.

Parameters:

data (SearchServiceLevelObjectiveData, optional) – A service level objective ID and attributes.

datadog_api_client.v1.model.search_service_level_objective_attributes module

class SearchServiceLevelObjectiveAttributes(arg: None)

class SearchServiceLevelObjectiveAttributes(arg: ModelComposed)

class SearchServiceLevelObjectiveAttributes(*args, **kwargs)

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , and tags ).

Parameters:

• all_tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty).

• created_at (int, optional) –

  Creation timestamp (UNIX time in seconds)

  Always included in service level objective responses.

• creator (SLOCreator, none_type, optional) – The creator of the SLO

• description (str, none_type, optional) –

  A user-defined description of the service level objective.

  Always included in service level objective responses (but may be null ). Optional in create/update requests.

• env_tags ([str], optional) – Tags with the env tag key.

• groups ([str], none_type, optional) – A list of (up to 100) monitor groups that narrow the scope of a monitor service level objective. Included in service level objective responses if it is not empty.

• modified_at (int, optional) –

  Modification timestamp (UNIX time in seconds)

  Always included in service level objective responses.

• monitor_ids ([int], none_type, optional) – A list of monitor ids that defines the scope of a monitor service level objective.

• name (str, optional) – The name of the service level objective object.

• overall_status ([SLOOverallStatuses], optional) – calculated status and error budget remaining.

• query (SearchSLOQuery, none_type, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

• service_tags ([str], optional) – Tags with the service tag key.

• slo_type (SLOType, optional) – The type of the service level objective.

• status (SLOStatus, optional) – Status of the SLO’s primary timeframe.

• team_tags ([str], optional) – Tags with the team tag key.

• thresholds ([SearchSLOThreshold], optional) – The thresholds (timeframes and associated targets) for this service level objective object.

datadog_api_client.v1.model.search_service_level_objective_data module

class SearchServiceLevelObjectiveData(arg: None)

class SearchServiceLevelObjectiveData(arg: ModelComposed)

class SearchServiceLevelObjectiveData(*args, **kwargs)

Bases: ModelNormal

A service level objective ID and attributes.

Parameters:

• attributes (SearchServiceLevelObjectiveAttributes, optional) – A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , and tags ).

• id (str, optional) –

  A unique identifier for the service level objective object.

  Always included in service level objective responses.

• type (str, optional) – The type of the object, must be slo.

datadog_api_client.v1.model.search_slo_query module

class SearchSLOQuery(arg: None)

class SearchSLOQuery(arg: ModelComposed)

class SearchSLOQuery(*args, **kwargs)

Bases: ModelNormal

A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

Parameters:

• denominator (str, optional) – A Datadog metric query for total (valid) events.

• metrics ([str], none_type, optional) – Metric names used in the query’s numerator and denominator. This field will return null and will be implemented in the next version of this endpoint.

• numerator (str, optional) – A Datadog metric query for good events.

datadog_api_client.v1.model.search_slo_response module

class SearchSLOResponse(arg: None)

class SearchSLOResponse(arg: ModelComposed)

class SearchSLOResponse(*args, **kwargs)

Bases: ModelNormal

A search SLO response containing results from the search query.

Parameters:

• data (SearchSLOResponseData, optional) – Data from search SLO response.

• links (SearchSLOResponseLinks, optional) – Pagination links.

• meta (SearchSLOResponseMeta, optional) – Searches metadata returned by the API.

datadog_api_client.v1.model.search_slo_response_data module

class SearchSLOResponseData(arg: None)

class SearchSLOResponseData(arg: ModelComposed)

class SearchSLOResponseData(*args, **kwargs)

Bases: ModelNormal

Data from search SLO response.

Parameters:

• attributes (SearchSLOResponseDataAttributes, optional) – Attributes

• type (str, optional) – Type of service level objective result.

datadog_api_client.v1.model.search_slo_response_data_attributes module

class SearchSLOResponseDataAttributes(arg: None)

class SearchSLOResponseDataAttributes(arg: ModelComposed)

class SearchSLOResponseDataAttributes(*args, **kwargs)

Bases: ModelNormal

Attributes

Parameters:

• facets (SearchSLOResponseDataAttributesFacets, optional) – Facets

• slos ([SearchServiceLevelObjective], optional) – SLOs

datadog_api_client.v1.model.search_slo_response_data_attributes_facets module

class SearchSLOResponseDataAttributesFacets(arg: None)

class SearchSLOResponseDataAttributesFacets(arg: ModelComposed)

class SearchSLOResponseDataAttributesFacets(*args, **kwargs)

Bases: ModelNormal

Facets

Parameters:

• all_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – All tags associated with an SLO.

• creator_name ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Creator of an SLO.

• env_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Tags with the env tag key.

• service_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Tags with the service tag key.

• slo_type ([SearchSLOResponseDataAttributesFacetsObjectInt], optional) – Type of SLO.

• target ([SearchSLOResponseDataAttributesFacetsObjectInt], optional) – SLO Target

• team_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Tags with the team tag key.

• timeframe ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Timeframes of SLOs.

datadog_api_client.v1.model.search_slo_response_data_attributes_facets_object_int module

class SearchSLOResponseDataAttributesFacetsObjectInt(arg: None)

class SearchSLOResponseDataAttributesFacetsObjectInt(arg: ModelComposed)

class SearchSLOResponseDataAttributesFacetsObjectInt(*args, **kwargs)

Bases: ModelNormal

Facet

Parameters:

• count (int, optional) – Count

• name (float, optional) – Facet

datadog_api_client.v1.model.search_slo_response_data_attributes_facets_object_string module

class SearchSLOResponseDataAttributesFacetsObjectString(arg: None)

class SearchSLOResponseDataAttributesFacetsObjectString(arg: ModelComposed)

class SearchSLOResponseDataAttributesFacetsObjectString(*args, **kwargs)

Bases: ModelNormal

Facet

Parameters:

• count (int, optional) – Count

• name (str, optional) – Facet

datadog_api_client.v1.model.search_slo_response_links module

class SearchSLOResponseLinks(arg: None)

class SearchSLOResponseLinks(arg: ModelComposed)

class SearchSLOResponseLinks(*args, **kwargs)

Bases: ModelNormal

Pagination links.

Parameters:

• first (str, optional) – Link to last page.

• last (str, none_type, optional) – Link to first page.

• next (str, optional) – Link to the next page.

• prev (str, none_type, optional) – Link to previous page.

• self (str, optional) – Link to current page.

datadog_api_client.v1.model.search_slo_response_meta module

class SearchSLOResponseMeta(arg: None)

class SearchSLOResponseMeta(arg: ModelComposed)

class SearchSLOResponseMeta(*args, **kwargs)

Bases: ModelNormal

Searches metadata returned by the API.

Parameters:

pagination (SearchSLOResponseMetaPage, optional) – Pagination metadata returned by the API.

datadog_api_client.v1.model.search_slo_response_meta_page module

class SearchSLOResponseMetaPage(arg: None)

class SearchSLOResponseMetaPage(arg: ModelComposed)

class SearchSLOResponseMetaPage(*args, **kwargs)

Bases: ModelNormal

Pagination metadata returned by the API.

Parameters:

• first_number (int, optional) – The first number.

• last_number (int, optional) – The last number.

• next_number (int, optional) – The next number.

• number (int, optional) – The page number.

• prev_number (int, optional) – The previous page number.

• size (int, optional) – The size of the response.

• total (int, optional) – The total number of SLOs in the response.

• type (str, optional) – Type of pagination.

datadog_api_client.v1.model.search_slo_threshold module

class SearchSLOThreshold(arg: None)

class SearchSLOThreshold(arg: ModelComposed)

class SearchSLOThreshold(*args, **kwargs)

Bases: ModelNormal

SLO thresholds (target and optionally warning) for a single time window.

Parameters:

• target (float) – The target value for the service level indicator within the corresponding timeframe.

• target_display (str, optional) –

  A string representation of the target that indicates its precision. It uses trailing zeros to show significant decimal places (for example 98.00 ).

  Always included in service level objective responses. Ignored in create/update requests.

• timeframe (SearchSLOTimeframe) – The SLO time window options.

• warning (float, none_type, optional) – The warning value for the service level objective.

• warning_display (str, none_type, optional) –

  A string representation of the warning target (see the description of the target_display field for details).

  Included in service level objective responses if a warning target exists. Ignored in create/update requests.

datadog_api_client.v1.model.search_slo_timeframe module

class SearchSLOTimeframe(arg: None)

class SearchSLOTimeframe(arg: ModelComposed)

class SearchSLOTimeframe(*args, **kwargs)

Bases: ModelSimple

The SLO time window options.

Parameters:

• value (str) – Must be one of [“7d”, “30d”, “90d”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.selectable_template_variable_items module

class SelectableTemplateVariableItems(arg: None)

class SelectableTemplateVariableItems(arg: ModelComposed)

class SelectableTemplateVariableItems(*args, **kwargs)

Bases: ModelNormal

Object containing the template variable’s name, associated tag/attribute, default value and selectable values.

Parameters:

• default_value (str, optional) – The default value of the template variable.

• name (str, optional) – Name of the template variable.

• prefix (str, optional) – The tag/attribute key associated with the template variable.

• type (str, none_type, optional) – The type of variable. This is to differentiate between filter variables (interpolated in query) and group by variables (interpolated into group by).

• visible_tags ([str], none_type, optional) – List of visible tag values on the shared dashboard.

datadog_api_client.v1.model.series module

class Series(arg: None)

class Series(arg: ModelComposed)

class Series(*args, **kwargs)

Bases: ModelNormal

A metric to submit to Datadog. See Datadog metrics.

Parameters:

• host (str, optional) – The name of the host that produced the metric.

• interval (int, none_type, optional) – If the type of the metric is rate or count, define the corresponding interval in seconds.

• metric (str) – The name of the timeseries.

• points ([Point]) – Points relating to a metric. All points must be tuples with timestamp and a scalar value (cannot be a string). Timestamps should be in POSIX time in seconds, and cannot be more than ten minutes in the future or more than one hour in the past.

• tags ([str], optional) – A list of tags associated with the metric.

• type (str, optional) – The type of the metric. Valid types are “”, count , gauge , and rate.

datadog_api_client.v1.model.service_check module

class ServiceCheck(arg: None)

class ServiceCheck(arg: ModelComposed)

class ServiceCheck(*args, **kwargs)

Bases: ModelNormal

An object containing service check and status.

Parameters:

• check (str) – The check.

• host_name (str) – The host name correlated with the check.

• message (str, optional) – Message containing check status.

• status (ServiceCheckStatus) – The status of a service check. Set to 0 for OK, 1 for warning, 2 for critical, and 3 for unknown.

• tags ([str]) – Tags related to a check.

• timestamp (int, optional) – Time of check.

datadog_api_client.v1.model.service_check_status module

class ServiceCheckStatus(arg: None)

class ServiceCheckStatus(arg: ModelComposed)

class ServiceCheckStatus(*args, **kwargs)

Bases: ModelSimple

The status of a service check. Set to 0 for OK, 1 for warning, 2 for critical, and 3 for unknown.

Parameters:

• value (int) – Must be one of [0, 1, 2, 3].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.service_checks module

class ServiceChecks(arg: None)

class ServiceChecks(arg: ModelComposed)

class ServiceChecks(*args, **kwargs)

Bases: ModelSimple

The service checks.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.service_level_objective module

class ServiceLevelObjective(arg: None)

class ServiceLevelObjective(arg: ModelComposed)

class ServiceLevelObjective(*args, **kwargs)

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).

Parameters:

• created_at (int, optional) –

  Creation timestamp (UNIX time in seconds)

  Always included in service level objective responses.

• creator (Creator, optional) – Object describing the creator of the shared element.

• description (str, none_type, optional) –

  A user-defined description of the service level objective.

  Always included in service level objective responses (but may be null ). Optional in create/update requests.

• groups ([str], optional) –

  A list of (up to 100) monitor groups that narrow the scope of a monitor service level objective.

  Included in service level objective responses if it is not empty. Optional in create/update requests for monitor service level objectives, but may only be used when then length of the monitor_ids field is one.

• id (str, optional) –

  A unique identifier for the service level objective object.

  Always included in service level objective responses.

• modified_at (int, optional) –

  Modification timestamp (UNIX time in seconds)

  Always included in service level objective responses.

• monitor_ids ([int], optional) – A list of monitor ids that defines the scope of a monitor service level objective. Required if type is monitor.

• monitor_tags ([str], optional) – The union of monitor tags for all monitors referenced by the monitor_ids field. Always included in service level objective responses for monitor-based service level objectives (but may be empty). Ignored in create/update requests. Does not affect which monitors are included in the service level objective (that is determined entirely by the monitor_ids field).

• name (str) – The name of the service level objective object.

• query (ServiceLevelObjectiveQuery, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

• sli_specification (SLOSliSpec, optional) – A generic SLI specification. This is currently used for time-slice SLOs only.

• tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty). Optional in create/update requests.

• target_threshold (float, optional) – The target threshold such that when the service level indicator is above this threshold over the given timeframe, the objective is being met.

• thresholds ([SLOThreshold]) – The thresholds (timeframes and associated targets) for this service level objective object.

• timeframe (SLOTimeframe, optional) – The SLO time window options. Note that “custom” is not a valid option for creating or updating SLOs. It is only used when querying SLO history over custom timeframes.

• type (SLOType) – The type of the service level objective.

• warning_threshold (float, optional) – The optional warning threshold such that when the service level indicator is below this value for the given threshold, but above the target threshold, the objective appears in a “warning” state. This value must be greater than the target threshold.

datadog_api_client.v1.model.service_level_objective_query module

class ServiceLevelObjectiveQuery(arg: None)

class ServiceLevelObjectiveQuery(arg: ModelComposed)

class ServiceLevelObjectiveQuery(*args, **kwargs)

Bases: ModelNormal

A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

Parameters:

• denominator (str) – A Datadog metric query for total (valid) events.

• numerator (str) – A Datadog metric query for good events.

datadog_api_client.v1.model.service_level_objective_request module

class ServiceLevelObjectiveRequest(arg: None)

class ServiceLevelObjectiveRequest(arg: ModelComposed)

class ServiceLevelObjectiveRequest(*args, **kwargs)

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).

Parameters:

• description (str, none_type, optional) –

  A user-defined description of the service level objective.

  Always included in service level objective responses (but may be null ). Optional in create/update requests.

• groups ([str], optional) –

  A list of (up to 100) monitor groups that narrow the scope of a monitor service level objective.

  Included in service level objective responses if it is not empty. Optional in create/update requests for monitor service level objectives, but may only be used when then length of the monitor_ids field is one.

• monitor_ids ([int], optional) – A list of monitor IDs that defines the scope of a monitor service level objective. Required if type is monitor.

• name (str) – The name of the service level objective object.

• query (ServiceLevelObjectiveQuery, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

• sli_specification (SLOSliSpec, optional) – A generic SLI specification. This is currently used for time-slice SLOs only.

• tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty). Optional in create/update requests.

• target_threshold (float, optional) – The target threshold such that when the service level indicator is above this threshold over the given timeframe, the objective is being met.

• thresholds ([SLOThreshold]) – The thresholds (timeframes and associated targets) for this service level objective object.

• timeframe (SLOTimeframe, optional) – The SLO time window options. Note that “custom” is not a valid option for creating or updating SLOs. It is only used when querying SLO history over custom timeframes.

• type (SLOType) – The type of the service level objective.

• warning_threshold (float, optional) – The optional warning threshold such that when the service level indicator is below this value for the given threshold, but above the target threshold, the objective appears in a “warning” state. This value must be greater than the target threshold.

datadog_api_client.v1.model.service_map_widget_definition module

class ServiceMapWidgetDefinition(arg: None)

class ServiceMapWidgetDefinition(arg: ModelComposed)

class ServiceMapWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

This widget displays a map of a service to all of the services that call it, and all of the services that it calls.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• filters ([str]) – Your environment and primary tag (or * if enabled for your account).

• service (str) – The ID of the service you want to map.

• title (str, optional) – The title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (ServiceMapWidgetDefinitionType) – Type of the service map widget.

datadog_api_client.v1.model.service_map_widget_definition_type module

class ServiceMapWidgetDefinitionType(arg: None)

class ServiceMapWidgetDefinitionType(arg: ModelComposed)

class ServiceMapWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the service map widget.

Parameters:

• value (str) – If omitted defaults to “servicemap”. Must be one of [“servicemap”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.service_summary_widget_definition module

class ServiceSummaryWidgetDefinition(arg: None)

class ServiceSummaryWidgetDefinition(arg: ModelComposed)

class ServiceSummaryWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The service summary displays the graphs of a chosen service in your screenboard. Only available on FREE layout dashboards.

Parameters:

• display_format (WidgetServiceSummaryDisplayFormat, optional) – Number of columns to display.

• env (str) – APM environment.

• service (str) – APM service.

• show_breakdown (bool, optional) – Whether to show the latency breakdown or not.

• show_distribution (bool, optional) – Whether to show the latency distribution or not.

• show_errors (bool, optional) – Whether to show the error metrics or not.

• show_hits (bool, optional) – Whether to show the hits metrics or not.

• show_latency (bool, optional) – Whether to show the latency metrics or not.

• show_resource_list (bool, optional) – Whether to show the resource list or not.

• size_format (WidgetSizeFormat, optional) – Size of the widget.

• span_name (str) – APM span name.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (ServiceSummaryWidgetDefinitionType) – Type of the service summary widget.

datadog_api_client.v1.model.service_summary_widget_definition_type module

class ServiceSummaryWidgetDefinitionType(arg: None)

class ServiceSummaryWidgetDefinitionType(arg: ModelComposed)

class ServiceSummaryWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the service summary widget.

Parameters:

• value (str) – If omitted defaults to “trace_service”. Must be one of [“trace_service”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.shared_dashboard module

class SharedDashboard(arg: None)

class SharedDashboard(arg: ModelComposed)

class SharedDashboard(*args, **kwargs)

Bases: ModelNormal

The metadata object associated with how a dashboard has been/will be shared.

Parameters:

• author (SharedDashboardAuthor, optional) – User who shared the dashboard.

• created (datetime, optional) – Date the dashboard was shared.

• dashboard_id (str) – ID of the dashboard to share.

• dashboard_type (DashboardType) – The type of the associated private dashboard.

• embeddable_domains ([str], optional) – The SharedDashboard embeddable_domains.

• expiration (datetime, none_type, optional) – The time when an OPEN shared dashboard becomes publicly unavailable.

• global_time (DashboardGlobalTime, optional) – Object containing the live span selection for the dashboard.

• global_time_selectable_enabled (bool, none_type, optional) – Whether to allow viewers to select a different global time setting for the shared dashboard.

• invitees ([SharedDashboardInviteesItems], optional) – The SharedDashboard invitees.

• last_accessed (datetime, none_type, optional) – The last time the shared dashboard was accessed. Null if never accessed.

• public_url (str, optional) – URL of the shared dashboard.

• selectable_template_vars ([SelectableTemplateVariableItems], none_type, optional) – List of objects representing template variables on the shared dashboard which can have selectable values.

• share_list ([str], none_type, optional) – List of email addresses that can receive an invitation to access to the shared dashboard. Deprecated.

• share_type (DashboardShareType, none_type, optional) – Type of sharing access (either open to anyone who has the public URL or invite-only).

• status (SharedDashboardStatus, optional) – Active means the dashboard is publicly available. Paused means the dashboard is not publicly available.

• title (str, optional) – Title of the shared dashboard.

• token (str, optional) – A unique token assigned to the shared dashboard.

• viewing_preferences (ViewingPreferences, optional) – The viewing preferences for a shared dashboard.

datadog_api_client.v1.model.shared_dashboard_author module

class SharedDashboardAuthor(arg: None)

class SharedDashboardAuthor(arg: ModelComposed)

class SharedDashboardAuthor(*args, **kwargs)

Bases: ModelNormal

User who shared the dashboard.

Parameters:

• handle (str, optional) – Identifier of the user who shared the dashboard.

• name (str, none_type, optional) – Name of the user who shared the dashboard.

datadog_api_client.v1.model.shared_dashboard_invitees_items module

class SharedDashboardInviteesItems(arg: None)

class SharedDashboardInviteesItems(arg: ModelComposed)

class SharedDashboardInviteesItems(*args, **kwargs)

Bases: ModelNormal

The allowlisted invitees for an INVITE-only shared dashboard.

Parameters:

• access_expiration (datetime, none_type, optional) – Time of the invitee expiration. Null means the invite will not expire.

• created_at (datetime, optional) – Time that the invitee was created.

• email (str) – Email of the invitee.

datadog_api_client.v1.model.shared_dashboard_invites module

class SharedDashboardInvites(arg: None)

class SharedDashboardInvites(arg: ModelComposed)

class SharedDashboardInvites(*args, **kwargs)

Bases: ModelNormal

Invitations data and metadata that exists for a shared dashboard returned by the API.

Parameters:

• data (SharedDashboardInvitesData) – An object or list of objects containing the information for an invitation to a shared dashboard.

• meta (SharedDashboardInvitesMeta, optional) – Pagination metadata returned by the API.

datadog_api_client.v1.model.shared_dashboard_invites_data module

class SharedDashboardInvitesData(arg: None)

class SharedDashboardInvitesData(arg: ModelComposed)

class SharedDashboardInvitesData(*args, **kwargs)

Bases: ModelComposed

An object or list of objects containing the information for an invitation to a shared dashboard.

Parameters:

• attributes (SharedDashboardInvitesDataObjectAttributes) – Attributes of the shared dashboard invitation

• type (DashboardInviteType) – Type for shared dashboard invitation request body.

datadog_api_client.v1.model.shared_dashboard_invites_data_list module

class SharedDashboardInvitesDataList(arg: None)

class SharedDashboardInvitesDataList(arg: ModelComposed)

class SharedDashboardInvitesDataList(*args, **kwargs)

Bases: ModelSimple

A list of objects containing the information for an invitation(s) to a shared dashboard.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.shared_dashboard_invites_data_object module

class SharedDashboardInvitesDataObject(arg: None)

class SharedDashboardInvitesDataObject(arg: ModelComposed)

class SharedDashboardInvitesDataObject(*args, **kwargs)

Bases: ModelNormal

Object containing the information for an invitation to a shared dashboard.

Parameters:

• attributes (SharedDashboardInvitesDataObjectAttributes) – Attributes of the shared dashboard invitation

• type (DashboardInviteType) – Type for shared dashboard invitation request body.

datadog_api_client.v1.model.shared_dashboard_invites_data_object_attributes module

class SharedDashboardInvitesDataObjectAttributes(arg: None)

class SharedDashboardInvitesDataObjectAttributes(arg: ModelComposed)

class SharedDashboardInvitesDataObjectAttributes(*args, **kwargs)

Bases: ModelNormal

Attributes of the shared dashboard invitation

Parameters:

• created_at (datetime, optional) – When the invitation was sent.

• email (str, optional) – An email address that an invitation has been (or if used in invitation request, will be) sent to.

• has_session (bool, optional) – Indicates whether an active session exists for the invitation (produced when a user clicks the link in the email).

• invitation_expiry (datetime, optional) – When the invitation expires.

• session_expiry (datetime, none_type, optional) – When the invited user’s session expires. null if the invitation has no associated session.

• share_token (str, optional) – The unique token of the shared dashboard that was (or is to be) shared.

datadog_api_client.v1.model.shared_dashboard_invites_meta module

class SharedDashboardInvitesMeta(arg: None)

class SharedDashboardInvitesMeta(arg: ModelComposed)

class SharedDashboardInvitesMeta(*args, **kwargs)

Bases: ModelNormal

Pagination metadata returned by the API.

Parameters:

page (SharedDashboardInvitesMetaPage, optional) – Object containing the total count of invitations across all pages

datadog_api_client.v1.model.shared_dashboard_invites_meta_page module

class SharedDashboardInvitesMetaPage(arg: None)

class SharedDashboardInvitesMetaPage(arg: ModelComposed)

class SharedDashboardInvitesMetaPage(*args, **kwargs)

Bases: ModelNormal

Object containing the total count of invitations across all pages

Parameters:

total_count (int, optional) – The total number of invitations on this shared board, across all pages.

datadog_api_client.v1.model.shared_dashboard_status module

class SharedDashboardStatus(arg: None)

class SharedDashboardStatus(arg: ModelComposed)

class SharedDashboardStatus(*args, **kwargs)

Bases: ModelSimple

Active means the dashboard is publicly available. Paused means the dashboard is not publicly available.

Parameters:

• value (str) – Must be one of [“active”, “paused”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.shared_dashboard_update_request module

class SharedDashboardUpdateRequest(arg: None)

class SharedDashboardUpdateRequest(arg: ModelComposed)

class SharedDashboardUpdateRequest(*args, **kwargs)

Bases: ModelNormal

Update a shared dashboard’s settings.

Parameters:

• embeddable_domains ([str], optional) – The SharedDashboard embeddable_domains.

• expiration (datetime, none_type, optional) – The time when an OPEN shared dashboard becomes publicly unavailable.

• global_time (SharedDashboardUpdateRequestGlobalTime, none_type, optional) – Timeframe setting for the shared dashboard.

• global_time_selectable_enabled (bool, none_type, optional) – Whether to allow viewers to select a different global time setting for the shared dashboard.

• invitees ([SharedDashboardInviteesItems], optional) – The SharedDashboard invitees.

• selectable_template_vars ([SelectableTemplateVariableItems], none_type, optional) – List of objects representing template variables on the shared dashboard which can have selectable values.

• share_list ([str], none_type, optional) – List of email addresses that can be given access to the shared dashboard. Deprecated.

• share_type (DashboardShareType, none_type, optional) – Type of sharing access (either open to anyone who has the public URL or invite-only).

• status (SharedDashboardStatus, optional) – Active means the dashboard is publicly available. Paused means the dashboard is not publicly available.

• title (str, optional) – Title of the shared dashboard.

• viewing_preferences (ViewingPreferences, optional) – The viewing preferences for a shared dashboard.

datadog_api_client.v1.model.shared_dashboard_update_request_global_time module

class SharedDashboardUpdateRequestGlobalTime(arg: None)

class SharedDashboardUpdateRequestGlobalTime(arg: ModelComposed)

class SharedDashboardUpdateRequestGlobalTime(*args, **kwargs)

Bases: ModelNormal

Timeframe setting for the shared dashboard.

Parameters:

live_span (DashboardGlobalTimeLiveSpan, optional) – Dashboard global time live_span selection

datadog_api_client.v1.model.signal_archive_reason module

class SignalArchiveReason(arg: None)

class SignalArchiveReason(arg: ModelComposed)

class SignalArchiveReason(*args, **kwargs)

Bases: ModelSimple

Reason why a signal has been archived.

Parameters:

• value (str) – Must be one of [“none”, “false_positive”, “testing_or_maintenance”, “investigated_case_opened”, “true_positive_benign”, “true_positive_malicious”, “other”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.signal_assignee_update_request module

class SignalAssigneeUpdateRequest(arg: None)

class SignalAssigneeUpdateRequest(arg: ModelComposed)

class SignalAssigneeUpdateRequest(*args, **kwargs)

Bases: ModelNormal

Attributes describing an assignee update operation over a security signal.

Parameters:

• assignee (str) – The UUID of the user being assigned. Use empty string to return signal to unassigned.

• version (int, optional) – Version of the updated signal. If server side version is higher, update will be rejected.

datadog_api_client.v1.model.signal_state_update_request module

class SignalStateUpdateRequest(arg: None)

class SignalStateUpdateRequest(arg: ModelComposed)

class SignalStateUpdateRequest(*args, **kwargs)

Bases: ModelNormal

Attributes describing the change of state for a given state.

Parameters:

• archive_comment (str, optional) – Optional comment to explain why a signal is being archived.

• archive_reason (SignalArchiveReason, optional) – Reason why a signal has been archived.

• state (SignalTriageState) – The new triage state of the signal.

• version (int, optional) – Version of the updated signal. If server side version is higher, update will be rejected.

datadog_api_client.v1.model.signal_triage_state module

class SignalTriageState(arg: None)

class SignalTriageState(arg: ModelComposed)

class SignalTriageState(*args, **kwargs)

Bases: ModelSimple

The new triage state of the signal.

Parameters:

• value (str) – Must be one of [“open”, “archived”, “under_review”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slack_integration_channel module

class SlackIntegrationChannel(arg: None)

class SlackIntegrationChannel(arg: ModelComposed)

class SlackIntegrationChannel(*args, **kwargs)

Bases: ModelNormal

The Slack channel configuration.

Parameters:

• display (SlackIntegrationChannelDisplay, optional) – Configuration options for what is shown in an alert event message.

• name (str, optional) – Your channel name.

datadog_api_client.v1.model.slack_integration_channel_display module

class SlackIntegrationChannelDisplay(arg: None)

class SlackIntegrationChannelDisplay(arg: ModelComposed)

class SlackIntegrationChannelDisplay(*args, **kwargs)

Bases: ModelNormal

Configuration options for what is shown in an alert event message.

Parameters:

• message (bool, optional) – Show the main body of the alert event.

• mute_buttons (bool, optional) – Show interactive buttons to mute the alerting monitor.

• notified (bool, optional) – Show the list of @-handles in the alert event.

• snapshot (bool, optional) – Show the alert event’s snapshot image.

• tags (bool, optional) – Show the scopes on which the monitor alerted.

datadog_api_client.v1.model.slack_integration_channels module

class SlackIntegrationChannels(arg: None)

class SlackIntegrationChannels(arg: ModelComposed)

class SlackIntegrationChannels(*args, **kwargs)

Bases: ModelSimple

A list of configured Slack channels.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_bulk_delete module

class SLOBulkDelete(arg: None)

class SLOBulkDelete(arg: ModelComposed)

class SLOBulkDelete(*args, **kwargs)

Bases: ModelNormal

A map of service level objective object IDs to arrays of timeframes, which indicate the thresholds to delete for each ID.

datadog_api_client.v1.model.slo_bulk_delete_error module

class SLOBulkDeleteError(arg: None)

class SLOBulkDeleteError(arg: ModelComposed)

class SLOBulkDeleteError(*args, **kwargs)

Bases: ModelNormal

Object describing the error.

Parameters:

• id (str) – The ID of the service level objective object associated with this error.

• message (str) – The error message.

• timeframe (SLOErrorTimeframe) – The timeframe of the threshold associated with this error or “all” if all thresholds are affected.

datadog_api_client.v1.model.slo_bulk_delete_response module

class SLOBulkDeleteResponse(arg: None)

class SLOBulkDeleteResponse(arg: ModelComposed)

class SLOBulkDeleteResponse(*args, **kwargs)

Bases: ModelNormal

The bulk partial delete service level objective object endpoint response.

This endpoint operates on multiple service level objective objects, so it may be partially successful. In such cases, the “data” and “error” fields in this response indicate which deletions succeeded and failed.

Parameters:

• data (SLOBulkDeleteResponseData, optional) – An array of service level objective objects.

• errors ([SLOBulkDeleteError], optional) – Array of errors object returned.

datadog_api_client.v1.model.slo_bulk_delete_response_data module

class SLOBulkDeleteResponseData(arg: None)

class SLOBulkDeleteResponseData(arg: ModelComposed)

class SLOBulkDeleteResponseData(*args, **kwargs)

Bases: ModelNormal

An array of service level objective objects.

Parameters:

• deleted ([str], optional) – An array of service level objective object IDs that indicates which objects that were completely deleted.

• updated ([str], optional) – An array of service level objective object IDs that indicates which objects that were modified (objects for which at least one threshold was deleted, but that were not completely deleted).

datadog_api_client.v1.model.slo_correction module

class SLOCorrection(arg: None)

class SLOCorrection(arg: ModelComposed)

class SLOCorrection(*args, **kwargs)

Bases: ModelNormal

The response object of a list of SLO corrections.

Parameters:

• attributes (SLOCorrectionResponseAttributes, optional) – The attribute object associated with the SLO correction.

• id (str, optional) – The ID of the SLO correction.

• type (SLOCorrectionType, optional) – SLO correction resource type.

datadog_api_client.v1.model.slo_correction_category module

class SLOCorrectionCategory(arg: None)

class SLOCorrectionCategory(arg: ModelComposed)

class SLOCorrectionCategory(*args, **kwargs)

Bases: ModelSimple

Category the SLO correction belongs to.

Parameters:

• value (str) – Must be one of [“Scheduled Maintenance”, “Outside Business Hours”, “Deployment”, “Other”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_correction_create_data module

class SLOCorrectionCreateData(arg: None)

class SLOCorrectionCreateData(arg: ModelComposed)

class SLOCorrectionCreateData(*args, **kwargs)

Bases: ModelNormal

The data object associated with the SLO correction to be created.

Parameters:

• attributes (SLOCorrectionCreateRequestAttributes, optional) – The attribute object associated with the SLO correction to be created.

• type (SLOCorrectionType) – SLO correction resource type.

datadog_api_client.v1.model.slo_correction_create_request module

class SLOCorrectionCreateRequest(arg: None)

class SLOCorrectionCreateRequest(arg: ModelComposed)

class SLOCorrectionCreateRequest(*args, **kwargs)

Bases: ModelNormal

An object that defines a correction to be applied to an SLO.

Parameters:

data (SLOCorrectionCreateData, optional) – The data object associated with the SLO correction to be created.

datadog_api_client.v1.model.slo_correction_create_request_attributes module

class SLOCorrectionCreateRequestAttributes(arg: None)

class SLOCorrectionCreateRequestAttributes(arg: ModelComposed)

class SLOCorrectionCreateRequestAttributes(*args, **kwargs)

Bases: ModelNormal

The attribute object associated with the SLO correction to be created.

Parameters:

• category (SLOCorrectionCategory) – Category the SLO correction belongs to.

• description (str, optional) – Description of the correction being made.

• duration (int, optional) – Length of time (in seconds) for a specified rrule recurring SLO correction.

• end (int, optional) – Ending time of the correction in epoch seconds.

• rrule (str, optional) – The recurrence rules as defined in the iCalendar RFC 5545. The supported rules for SLO corrections are FREQ , INTERVAL , COUNT , UNTIL and BYDAY.

• slo_id (str) – ID of the SLO that this correction applies to.

• start (int) – Starting time of the correction in epoch seconds.

• timezone (str, optional) – The timezone to display in the UI for the correction times (defaults to “UTC”).

datadog_api_client.v1.model.slo_correction_list_response module

class SLOCorrectionListResponse(arg: None)

class SLOCorrectionListResponse(arg: ModelComposed)

class SLOCorrectionListResponse(*args, **kwargs)

Bases: ModelNormal

A list of SLO correction objects.

Parameters:

• data ([SLOCorrection], optional) – The list of SLO corrections objects.

• meta (ResponseMetaAttributes, optional) – Object describing meta attributes of response.

datadog_api_client.v1.model.slo_correction_response module

class SLOCorrectionResponse(arg: None)

class SLOCorrectionResponse(arg: ModelComposed)

class SLOCorrectionResponse(*args, **kwargs)

Bases: ModelNormal

The response object of an SLO correction.

Parameters:

data (SLOCorrection, optional) – The response object of a list of SLO corrections.

datadog_api_client.v1.model.slo_correction_response_attributes module

class SLOCorrectionResponseAttributes(arg: None)

class SLOCorrectionResponseAttributes(arg: ModelComposed)

class SLOCorrectionResponseAttributes(*args, **kwargs)

Bases: ModelNormal

The attribute object associated with the SLO correction.

Parameters:

• category (SLOCorrectionCategory, optional) – Category the SLO correction belongs to.

• created_at (int, none_type, optional) – The epoch timestamp of when the correction was created at.

• creator (Creator, optional) – Object describing the creator of the shared element.

• description (str, optional) – Description of the correction being made.

• duration (int, none_type, optional) – Length of time (in seconds) for a specified rrule recurring SLO correction.

• end (int, none_type, optional) – Ending time of the correction in epoch seconds.

• modified_at (int, none_type, optional) – The epoch timestamp of when the correction was modified at.

• modifier (SLOCorrectionResponseAttributesModifier, none_type, optional) – Modifier of the object.

• rrule (str, none_type, optional) – The recurrence rules as defined in the iCalendar RFC 5545. The supported rules for SLO corrections are FREQ , INTERVAL , COUNT , UNTIL and BYDAY.

• slo_id (str, optional) – ID of the SLO that this correction applies to.

• start (int, optional) – Starting time of the correction in epoch seconds.

• timezone (str, optional) – The timezone to display in the UI for the correction times (defaults to “UTC”).

datadog_api_client.v1.model.slo_correction_response_attributes_modifier module

class SLOCorrectionResponseAttributesModifier(arg: None)

class SLOCorrectionResponseAttributesModifier(arg: ModelComposed)

class SLOCorrectionResponseAttributesModifier(*args, **kwargs)

Bases: ModelNormal

Modifier of the object.

Parameters:

• email (str, optional) – Email of the Modifier.

• handle (str, optional) – Handle of the Modifier.

• name (str, optional) – Name of the Modifier.

datadog_api_client.v1.model.slo_correction_type module

class SLOCorrectionType(arg: None)

class SLOCorrectionType(arg: ModelComposed)

class SLOCorrectionType(*args, **kwargs)

Bases: ModelSimple

SLO correction resource type.

Parameters:

• value (str) – If omitted defaults to “correction”. Must be one of [“correction”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_correction_update_data module

class SLOCorrectionUpdateData(arg: None)

class SLOCorrectionUpdateData(arg: ModelComposed)

class SLOCorrectionUpdateData(*args, **kwargs)

Bases: ModelNormal

The data object associated with the SLO correction to be updated.

Parameters:

• attributes (SLOCorrectionUpdateRequestAttributes, optional) – The attribute object associated with the SLO correction to be updated.

• type (SLOCorrectionType, optional) – SLO correction resource type.

datadog_api_client.v1.model.slo_correction_update_request module

class SLOCorrectionUpdateRequest(arg: None)

class SLOCorrectionUpdateRequest(arg: ModelComposed)

class SLOCorrectionUpdateRequest(*args, **kwargs)

Bases: ModelNormal

An object that defines a correction to be applied to an SLO.

Parameters:

data (SLOCorrectionUpdateData, optional) – The data object associated with the SLO correction to be updated.

datadog_api_client.v1.model.slo_correction_update_request_attributes module

class SLOCorrectionUpdateRequestAttributes(arg: None)

class SLOCorrectionUpdateRequestAttributes(arg: ModelComposed)

class SLOCorrectionUpdateRequestAttributes(*args, **kwargs)

Bases: ModelNormal

The attribute object associated with the SLO correction to be updated.

Parameters:

• category (SLOCorrectionCategory, optional) – Category the SLO correction belongs to.

• description (str, optional) – Description of the correction being made.

• duration (int, optional) – Length of time (in seconds) for a specified rrule recurring SLO correction.

• end (int, optional) – Ending time of the correction in epoch seconds.

• rrule (str, optional) – The recurrence rules as defined in the iCalendar RFC 5545. The supported rules for SLO corrections are FREQ , INTERVAL , COUNT , UNTIL and BYDAY.

• start (int, optional) – Starting time of the correction in epoch seconds.

• timezone (str, optional) – The timezone to display in the UI for the correction times (defaults to “UTC”).

datadog_api_client.v1.model.slo_creator module

class SLOCreator(arg: None)

class SLOCreator(arg: ModelComposed)

class SLOCreator(*args, **kwargs)

Bases: ModelNormal

The creator of the SLO

Parameters:

• email (str, optional) – Email of the creator.

• id (int, optional) – User ID of the creator.

• name (str, none_type, optional) – Name of the creator.

datadog_api_client.v1.model.slo_data_source_query_definition module

class SLODataSourceQueryDefinition(arg: None)

class SLODataSourceQueryDefinition(arg: ModelComposed)

class SLODataSourceQueryDefinition(*args, **kwargs)

Bases: ModelComposed

A formula and function query.

Parameters:

• aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.

• cross_org_uuids ([str], optional) – The source organization UUID for cross organization queries. Feature in Private Beta.

• data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.

• name (str) – Name of the query for use in formulas.

• query (str) – Metrics query definition.

datadog_api_client.v1.model.slo_delete_response module

class SLODeleteResponse(arg: None)

class SLODeleteResponse(arg: ModelComposed)

class SLODeleteResponse(*args, **kwargs)

Bases: ModelNormal

A response list of all service level objective deleted.

Parameters:

• data ([str], optional) – An array containing the ID of the deleted service level objective object.

• errors ({str: (str,)}, optional) – An dictionary containing the ID of the SLO as key and a deletion error as value.

datadog_api_client.v1.model.slo_error_budget_remaining_data module

class SLOErrorBudgetRemainingData(arg: None)

class SLOErrorBudgetRemainingData(arg: ModelComposed)

class SLOErrorBudgetRemainingData(*args, **kwargs)

Bases: ModelNormal

A mapping of threshold timeframe to the remaining error budget.

datadog_api_client.v1.model.slo_error_timeframe module

class SLOErrorTimeframe(arg: None)

class SLOErrorTimeframe(arg: ModelComposed)

class SLOErrorTimeframe(*args, **kwargs)

Bases: ModelSimple

The timeframe of the threshold associated with this error

or “all” if all thresholds are affected.

Parameters:

• value (str) – Must be one of [“7d”, “30d”, “90d”, “all”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_formula module

class SLOFormula(arg: None)

class SLOFormula(arg: ModelComposed)

class SLOFormula(*args, **kwargs)

Bases: ModelNormal

A formula that specifies how to combine the results of multiple queries.

Parameters:

formula (str) – The formula string, which is an expression involving named queries.

datadog_api_client.v1.model.slo_history_metrics module

class SLOHistoryMetrics(arg: None)

class SLOHistoryMetrics(arg: ModelComposed)

class SLOHistoryMetrics(*args, **kwargs)

Bases: ModelNormal

A metric based SLO history response.

This is not included in responses for monitor based SLOs.

Parameters:

• denominator (SLOHistoryMetricsSeries) – A representation of metric based SLO timeseries for the provided queries. This is the same response type from batch_query endpoint.

• interval (int) – The aggregated query interval for the series data. It’s implicit based on the query time window.

• message (str, optional) – Optional message if there are specific query issues/warnings.

• numerator (SLOHistoryMetricsSeries) – A representation of metric based SLO timeseries for the provided queries. This is the same response type from batch_query endpoint.

• query (str) – The combined numerator and denominator query CSV.

• res_type (str) – The series result type. This mimics batch_query response type.

• resp_version (int) – The series response version type. This mimics batch_query response type.

• times ([float]) – An array of query timestamps in EPOCH milliseconds.

datadog_api_client.v1.model.slo_history_metrics_series module

class SLOHistoryMetricsSeries(arg: None)

class SLOHistoryMetricsSeries(arg: ModelComposed)

class SLOHistoryMetricsSeries(*args, **kwargs)

Bases: ModelNormal

A representation of metric based SLO timeseries for the provided queries. This is the same response type from batch_query endpoint.

Parameters:

• count (int) – Count of submitted metrics.

• metadata (SLOHistoryMetricsSeriesMetadata, optional) – Query metadata.

• sum (float) – Total sum of the query.

• values ([float]) – The query values for each metric.

datadog_api_client.v1.model.slo_history_metrics_series_metadata module

class SLOHistoryMetricsSeriesMetadata(arg: None)

class SLOHistoryMetricsSeriesMetadata(arg: ModelComposed)

class SLOHistoryMetricsSeriesMetadata(*args, **kwargs)

Bases: ModelNormal

Query metadata.

Parameters:

• aggr (str, optional) – Query aggregator function. Deprecated.

• expression (str, optional) – Query expression. Deprecated.

• metric (str, optional) – Query metric used. Deprecated.

• query_index (int, optional) – Query index from original combined query. Deprecated.

• scope (str, optional) – Query scope. Deprecated.

• unit ([SLOHistoryMetricsSeriesMetadataUnit, none_type], none_type, optional) – An array of metric units that contains up to two unit objects. For example, bytes represents one unit object and bytes per second represents two unit objects. If a metric query only has one unit object, the second array element is null.

datadog_api_client.v1.model.slo_history_metrics_series_metadata_unit module

class SLOHistoryMetricsSeriesMetadataUnit(arg: None)

class SLOHistoryMetricsSeriesMetadataUnit(arg: ModelComposed)

class SLOHistoryMetricsSeriesMetadataUnit(*args, **kwargs)

Bases: ModelNormal

An Object of metric units.

Parameters:

• family (str, optional) – The family of metric unit, for example bytes is the family for kibibyte , byte , and bit units.

• id (int, optional) – The ID of the metric unit.

• name (str, optional) – The unit of the metric, for instance byte.

• plural (str, none_type, optional) – The plural Unit of metric, for instance bytes.

• scale_factor (float, optional) – The scale factor of metric unit, for instance 1.0.

• short_name (str, none_type, optional) – A shorter and abbreviated version of the metric unit, for instance B.

datadog_api_client.v1.model.slo_history_monitor module

class SLOHistoryMonitor(arg: None)

class SLOHistoryMonitor(arg: ModelComposed)

class SLOHistoryMonitor(*args, **kwargs)

Bases: ModelNormal

An object that holds an SLI value and its associated data. It can represent an SLO’s overall SLI value. This can also represent the SLI value for a specific monitor in multi-monitor SLOs, or a group in grouped SLOs.

Parameters:

• error_budget_remaining (SLOErrorBudgetRemainingData, optional) – A mapping of threshold timeframe to the remaining error budget.

• errors ([SLOHistoryResponseErrorWithType], optional) – An array of error objects returned while querying the history data for the service level objective.

• group (str, optional) – For groups in a grouped SLO, this is the group name.

• history ([[float]], optional) – The state transition history for the monitor. It is represented as an array of pairs. Each pair is an array containing the timestamp of the transition as an integer in Unix epoch format in the first element, and the state as an integer in the second element. An integer value of 0 for state means uptime, 1 means downtime, and 2 means no data. Periods of no data are counted either as uptime or downtime depending on monitor settings. See SLO documentation for detailed information.

• monitor_modified (int, optional) – For monitor based SLOs, this is the last modified timestamp in epoch seconds of the monitor.

• monitor_type (str, optional) – For monitor based SLOs, this describes the type of monitor.

• name (str, optional) – For groups in a grouped SLO, this is the group name. For monitors in a multi-monitor SLO, this is the monitor name.

• precision (float, optional) – The amount of decimal places the SLI value is accurate to for the given from && to timestamp. Use span_precision instead. Deprecated.

• preview (bool, optional) – For monitor based SLOs, when true this indicates that a replay is in progress to give an accurate uptime calculation.

• sli_value (float, none_type, optional) – The current SLI value of the SLO over the history window.

• span_precision (float, optional) – The amount of decimal places the SLI value is accurate to for the given from && to timestamp.

• uptime (float, optional) – Use sli_value instead. Deprecated.

datadog_api_client.v1.model.slo_history_response module

class SLOHistoryResponse(arg: None)

class SLOHistoryResponse(arg: ModelComposed)

class SLOHistoryResponse(*args, **kwargs)

Bases: ModelNormal

A service level objective history response.

Parameters:

• data (SLOHistoryResponseData, optional) – An array of service level objective objects.

• errors ([SLOHistoryResponseError], none_type, optional) – A list of errors while querying the history data for the service level objective.

datadog_api_client.v1.model.slo_history_response_data module

class SLOHistoryResponseData(arg: None)

class SLOHistoryResponseData(arg: ModelComposed)

class SLOHistoryResponseData(*args, **kwargs)

Bases: ModelNormal

An array of service level objective objects.

Parameters:

• from_ts (int, optional) – The from timestamp in epoch seconds.

• group_by ([str], optional) –

  For metric based SLOs where the query includes a group-by clause, this represents the list of grouping parameters.

  This is not included in responses for monitor based SLOs.

• groups ([SLOHistoryMonitor], optional) –

  For grouped SLOs, this represents SLI data for specific groups.

  This is not included in the responses for metric based SLOs.

• monitors ([SLOHistoryMonitor], optional) –

  For multi-monitor SLOs, this represents SLI data for specific monitors.

  This is not included in the responses for metric based SLOs.

• overall (SLOHistorySLIData, optional) – An object that holds an SLI value and its associated data. It can represent an SLO’s overall SLI value. This can also represent the SLI value for a specific monitor in multi-monitor SLOs, or a group in grouped SLOs.

• series (SLOHistoryMetrics, optional) –

  A metric based SLO history response.

  This is not included in responses for monitor based SLOs.

• thresholds ({str: (SLOThreshold,)}, optional) – mapping of string timeframe to the SLO threshold.

• to_ts (int, optional) – The to timestamp in epoch seconds.

• type (SLOType, optional) – The type of the service level objective.

• type_id (SLOTypeNumeric, optional) – A numeric representation of the type of the service level objective ( 0 for monitor, 1 for metric). Always included in service level objective responses. Ignored in create/update requests.

datadog_api_client.v1.model.slo_history_response_error module

class SLOHistoryResponseError(arg: None)

class SLOHistoryResponseError(arg: ModelComposed)

class SLOHistoryResponseError(*args, **kwargs)

Bases: ModelNormal

A list of errors while querying the history data for the service level objective.

Parameters:

error (str, optional) – Human readable error.

datadog_api_client.v1.model.slo_history_response_error_with_type module

class SLOHistoryResponseErrorWithType(arg: None)

class SLOHistoryResponseErrorWithType(arg: ModelComposed)

class SLOHistoryResponseErrorWithType(*args, **kwargs)

Bases: ModelNormal

An object describing the error with error type and error message.

Parameters:

• error_message (str) – A message with more details about the error.

• error_type (str) – Type of the error.

datadog_api_client.v1.model.slo_history_sli_data module

class SLOHistorySLIData(arg: None)

class SLOHistorySLIData(arg: ModelComposed)

class SLOHistorySLIData(*args, **kwargs)

Bases: ModelNormal

An object that holds an SLI value and its associated data. It can represent an SLO’s overall SLI value. This can also represent the SLI value for a specific monitor in multi-monitor SLOs, or a group in grouped SLOs.

Parameters:

• error_budget_remaining (SLOErrorBudgetRemainingData, optional) – A mapping of threshold timeframe to the remaining error budget.

• errors ([SLOHistoryResponseErrorWithType], optional) – An array of error objects returned while querying the history data for the service level objective.

• group (str, optional) – For groups in a grouped SLO, this is the group name.

• history ([[float]], optional) –

  The state transition history for monitor or time-slice SLOs. It is represented as an array of pairs. Each pair is an array containing the timestamp of the transition as an integer in Unix epoch format in the first element, and the state as an integer in the second element. An integer value of 0 for state means uptime, 1 means downtime, and 2 means no data. Periods of no data count as uptime in time-slice SLOs, while for monitor SLOs, no data is counted either as uptime or downtime depending on monitor settings. See SLO documentation for detailed information.

• monitor_modified (int, optional) – For monitor based SLOs, this is the last modified timestamp in epoch seconds of the monitor.

• monitor_type (str, optional) – For monitor based SLOs, this describes the type of monitor.

• name (str, optional) – For groups in a grouped SLO, this is the group name. For monitors in a multi-monitor SLO, this is the monitor name.

• precision ({str: (float,)}, optional) – A mapping of threshold timeframe to number of accurate decimals, regardless of the from && to timestamp.

• preview (bool, optional) – For monitor based SLOs, when true this indicates that a replay is in progress to give an accurate uptime calculation.

• sli_value (float, none_type, optional) – The current SLI value of the SLO over the history window.

• span_precision (float, optional) – The amount of decimal places the SLI value is accurate to for the given from && to timestamp.

• uptime (float, none_type, optional) – Use sli_value instead. Deprecated.

datadog_api_client.v1.model.slo_list_response module

class SLOListResponse(arg: None)

class SLOListResponse(arg: ModelComposed)

class SLOListResponse(*args, **kwargs)

Bases: ModelNormal

A response with one or more service level objective.

Parameters:

• data ([ServiceLevelObjective], optional) – An array of service level objective objects.

• errors ([str], optional) – An array of error messages. Each endpoint documents how/whether this field is used.

• metadata (SLOListResponseMetadata, optional) – The metadata object containing additional information about the list of SLOs.

datadog_api_client.v1.model.slo_list_response_metadata module

class SLOListResponseMetadata(arg: None)

class SLOListResponseMetadata(arg: ModelComposed)

class SLOListResponseMetadata(*args, **kwargs)

Bases: ModelNormal

The metadata object containing additional information about the list of SLOs.

Parameters:

page (SLOListResponseMetadataPage, optional) – The object containing information about the pages of the list of SLOs.

datadog_api_client.v1.model.slo_list_response_metadata_page module

class SLOListResponseMetadataPage(arg: None)

class SLOListResponseMetadataPage(arg: ModelComposed)

class SLOListResponseMetadataPage(*args, **kwargs)

Bases: ModelNormal

The object containing information about the pages of the list of SLOs.

Parameters:

• total_count (int, optional) – The total number of resources that could be retrieved ignoring the parameters and filters in the request.

• total_filtered_count (int, optional) – The total number of resources that match the parameters and filters in the request. This attribute can be used by a client to determine the total number of pages.

datadog_api_client.v1.model.slo_list_widget_definition module

class SLOListWidgetDefinition(arg: None)

class SLOListWidgetDefinition(arg: ModelComposed)

class SLOListWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Use the SLO List widget to track your SLOs (Service Level Objectives) on dashboards.

Parameters:

• requests ([SLOListWidgetRequest]) – Array of one request object to display in the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (SLOListWidgetDefinitionType) – Type of the SLO List widget.

datadog_api_client.v1.model.slo_list_widget_definition_type module

class SLOListWidgetDefinitionType(arg: None)

class SLOListWidgetDefinitionType(arg: ModelComposed)

class SLOListWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the SLO List widget.

Parameters:

• value (str) – If omitted defaults to “slo_list”. Must be one of [“slo_list”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_list_widget_query module

class SLOListWidgetQuery(arg: None)

class SLOListWidgetQuery(arg: ModelComposed)

class SLOListWidgetQuery(*args, **kwargs)

Bases: ModelNormal

Updated SLO List widget.

Parameters:

• limit (int, optional) – Maximum number of results to display in the table.

• query_string (str) – Widget query.

• sort ([WidgetFieldSort], optional) – Options for sorting results.

datadog_api_client.v1.model.slo_list_widget_request module

class SLOListWidgetRequest(arg: None)

class SLOListWidgetRequest(arg: ModelComposed)

class SLOListWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated SLO List widget.

Parameters:

• query (SLOListWidgetQuery) – Updated SLO List widget.

• request_type (SLOListWidgetRequestType) – Widget request type.

datadog_api_client.v1.model.slo_list_widget_request_type module

class SLOListWidgetRequestType(arg: None)

class SLOListWidgetRequestType(arg: ModelComposed)

class SLOListWidgetRequestType(*args, **kwargs)

Bases: ModelSimple

Widget request type.

Parameters:

• value (str) – If omitted defaults to “slo_list”. Must be one of [“slo_list”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_overall_statuses module

class SLOOverallStatuses(arg: None)

class SLOOverallStatuses(arg: ModelComposed)

class SLOOverallStatuses(*args, **kwargs)

Bases: ModelNormal

Overall status of the SLO by timeframes.

Parameters:

• error (str, none_type, optional) – Error message if SLO status or error budget could not be calculated.

• error_budget_remaining (float, none_type, optional) – Remaining error budget of the SLO in percentage.

• indexed_at (int, optional) – timestamp (UNIX time in seconds) of when the SLO status and error budget were calculated.

• raw_error_budget_remaining (SLORawErrorBudgetRemaining, none_type, optional) – Error budget remaining for an SLO.

• span_precision (int, none_type, optional) – The amount of decimal places the SLI value is accurate to.

• state (SLOState, optional) – State of the SLO.

• status (float, none_type, optional) – The status of the SLO.

• target (float, optional) – The target of the SLO.

• timeframe (SLOTimeframe, optional) – The SLO time window options. Note that “custom” is not a valid option for creating or updating SLOs. It is only used when querying SLO history over custom timeframes.

datadog_api_client.v1.model.slo_raw_error_budget_remaining module

class SLORawErrorBudgetRemaining(arg: None)

class SLORawErrorBudgetRemaining(arg: ModelComposed)

class SLORawErrorBudgetRemaining(*args, **kwargs)

Bases: ModelNormal

Error budget remaining for an SLO.

Parameters:

• unit (str, optional) – Error budget remaining unit.

• value (float, optional) – Error budget remaining value.

datadog_api_client.v1.model.slo_response module

class SLOResponse(arg: None)

class SLOResponse(arg: ModelComposed)

class SLOResponse(*args, **kwargs)

Bases: ModelNormal

A service level objective response containing a single service level objective.

Parameters:

• data (SLOResponseData, optional) – A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).

• errors ([str], optional) – An array of error messages. Each endpoint documents how/whether this field is used.

datadog_api_client.v1.model.slo_response_data module

class SLOResponseData(arg: None)

class SLOResponseData(arg: ModelComposed)

class SLOResponseData(*args, **kwargs)

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).

Parameters:

• configured_alert_ids ([int], optional) – A list of SLO monitors IDs that reference this SLO. This field is returned only when with_configured_alert_ids parameter is true in query.

• created_at (int, optional) –

  Creation timestamp (UNIX time in seconds)

  Always included in service level objective responses.

• creator (Creator, optional) – Object describing the creator of the shared element.

• description (str, none_type, optional) –

  A user-defined description of the service level objective.

  Always included in service level objective responses (but may be null ). Optional in create/update requests.

• groups ([str], optional) –

  A list of (up to 20) monitor groups that narrow the scope of a monitor service level objective.

  Included in service level objective responses if it is not empty. Optional in create/update requests for monitor service level objectives, but may only be used when then length of the monitor_ids field is one.

• id (str, optional) –

  A unique identifier for the service level objective object.

  Always included in service level objective responses.

• modified_at (int, optional) –

  Modification timestamp (UNIX time in seconds)

  Always included in service level objective responses.

• monitor_ids ([int], optional) – A list of monitor ids that defines the scope of a monitor service level objective. Required if type is monitor.

• monitor_tags ([str], optional) – The union of monitor tags for all monitors referenced by the monitor_ids field. Always included in service level objective responses for monitor service level objectives (but may be empty). Ignored in create/update requests. Does not affect which monitors are included in the service level objective (that is determined entirely by the monitor_ids field).

• name (str, optional) – The name of the service level objective object.

• query (ServiceLevelObjectiveQuery, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

• sli_specification (SLOSliSpec, optional) – A generic SLI specification. This is currently used for time-slice SLOs only.

• tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty). Optional in create/update requests.

• target_threshold (float, optional) – The target threshold such that when the service level indicator is above this threshold over the given timeframe, the objective is being met.

• thresholds ([SLOThreshold], optional) – The thresholds (timeframes and associated targets) for this service level objective object.

• timeframe (SLOTimeframe, optional) – The SLO time window options. Note that “custom” is not a valid option for creating or updating SLOs. It is only used when querying SLO history over custom timeframes.

• type (SLOType, optional) – The type of the service level objective.

• warning_threshold (float, optional) – The optional warning threshold such that when the service level indicator is below this value for the given threshold, but above the target threshold, the objective appears in a “warning” state. This value must be greater than the target threshold.

datadog_api_client.v1.model.slo_sli_spec module

class SLOSliSpec(arg: None)

class SLOSliSpec(arg: ModelComposed)

class SLOSliSpec(*args, **kwargs)

Bases: ModelComposed

A generic SLI specification. This is currently used for time-slice SLOs only.

Parameters:

time_slice (SLOTimeSliceCondition) – The time-slice condition, composed of 3 parts: 1. the metric timeseries query, 2. the comparator, and 3. the threshold. Optionally, a fourth part, the query interval, can be provided.

datadog_api_client.v1.model.slo_state module

class SLOState(arg: None)

class SLOState(arg: ModelComposed)

class SLOState(*args, **kwargs)

Bases: ModelSimple

State of the SLO.

Parameters:

• value (str) – Must be one of [“breached”, “warning”, “ok”, “no_data”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_status module

class SLOStatus(arg: None)

class SLOStatus(arg: ModelComposed)

class SLOStatus(*args, **kwargs)

Bases: ModelNormal

Status of the SLO’s primary timeframe.

Parameters:

• calculation_error (str, none_type, optional) – Error message if SLO status or error budget could not be calculated.

• error_budget_remaining (float, none_type, optional) – Remaining error budget of the SLO in percentage.

• indexed_at (int, optional) – timestamp (UNIX time in seconds) of when the SLO status and error budget were calculated.

• raw_error_budget_remaining (SLORawErrorBudgetRemaining, none_type, optional) – Error budget remaining for an SLO.

• sli (float, none_type, optional) – The current service level indicator (SLI) of the SLO, also known as ‘status’. This is a percentage value from 0-100 (inclusive).

• span_precision (int, none_type, optional) – The number of decimal places the SLI value is accurate to.

• state (SLOState, optional) – State of the SLO.

datadog_api_client.v1.model.slo_threshold module

class SLOThreshold(arg: None)

class SLOThreshold(arg: ModelComposed)

class SLOThreshold(*args, **kwargs)

Bases: ModelNormal

SLO thresholds (target and optionally warning) for a single time window.

Parameters:

• target (float) – The target value for the service level indicator within the corresponding timeframe.

• target_display (str, optional) –

  A string representation of the target that indicates its precision. It uses trailing zeros to show significant decimal places (for example 98.00 ).

  Always included in service level objective responses. Ignored in create/update requests.

• timeframe (SLOTimeframe) – The SLO time window options. Note that “custom” is not a valid option for creating or updating SLOs. It is only used when querying SLO history over custom timeframes.

• warning (float, optional) – The warning value for the service level objective.

• warning_display (str, optional) –

  A string representation of the warning target (see the description of the target_display field for details).

  Included in service level objective responses if a warning target exists. Ignored in create/update requests.

datadog_api_client.v1.model.slo_time_slice_comparator module

class SLOTimeSliceComparator(arg: None)

class SLOTimeSliceComparator(arg: ModelComposed)

class SLOTimeSliceComparator(*args, **kwargs)

Bases: ModelSimple

The comparator used to compare the SLI value to the threshold.

Parameters:

• value (str) – Must be one of [“>”, “>=”, “<”, “<=”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_time_slice_condition module

class SLOTimeSliceCondition(arg: None)

class SLOTimeSliceCondition(arg: ModelComposed)

class SLOTimeSliceCondition(*args, **kwargs)

Bases: ModelNormal

The time-slice condition, composed of 3 parts: 1. the metric timeseries query, 2. the comparator, and 3. the threshold. Optionally, a fourth part, the query interval, can be provided.

Parameters:

• comparator (SLOTimeSliceComparator) – The comparator used to compare the SLI value to the threshold.

• query (SLOTimeSliceQuery) – The queries and formula used to calculate the SLI value.

• query_interval_seconds (SLOTimeSliceInterval, optional) – The interval used when querying data, which defines the size of a time slice. Two values are allowed: 60 (1 minute) and 300 (5 minutes). If not provided, the value defaults to 300 (5 minutes).

• threshold (float) – The threshold value to which each SLI value will be compared.

datadog_api_client.v1.model.slo_time_slice_interval module

class SLOTimeSliceInterval(arg: None)

class SLOTimeSliceInterval(arg: ModelComposed)

class SLOTimeSliceInterval(*args, **kwargs)

Bases: ModelSimple

The interval used when querying data, which defines the size of a time slice.

Two values are allowed: 60 (1 minute) and 300 (5 minutes). If not provided, the value defaults to 300 (5 minutes).

Parameters:

• value (int) – Must be one of [60, 300].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_time_slice_query module

class SLOTimeSliceQuery(arg: None)

class SLOTimeSliceQuery(arg: ModelComposed)

class SLOTimeSliceQuery(*args, **kwargs)

Bases: ModelNormal

The queries and formula used to calculate the SLI value.

Parameters:

• formulas ([SLOFormula]) – A list that contains exactly one formula, as only a single formula may be used in a time-slice SLO.

• queries ([SLODataSourceQueryDefinition]) – A list of queries that are used to calculate the SLI value.

datadog_api_client.v1.model.slo_time_slice_spec module

class SLOTimeSliceSpec(arg: None)

class SLOTimeSliceSpec(arg: ModelComposed)

class SLOTimeSliceSpec(*args, **kwargs)

Bases: ModelNormal

A time-slice SLI specification.

Parameters:

time_slice (SLOTimeSliceCondition) – The time-slice condition, composed of 3 parts: 1. the metric timeseries query, 2. the comparator, and 3. the threshold. Optionally, a fourth part, the query interval, can be provided.

additional_properties_type = None

datadog_api_client.v1.model.slo_timeframe module

class SLOTimeframe(arg: None)

class SLOTimeframe(arg: ModelComposed)

class SLOTimeframe(*args, **kwargs)

Bases: ModelSimple

The SLO time window options. Note that “custom” is not a valid option for creating

or updating SLOs. It is only used when querying SLO history over custom timeframes.

Parameters:

• value (str) – Must be one of [“7d”, “30d”, “90d”, “custom”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_type module

class SLOType(arg: None)

class SLOType(arg: ModelComposed)

class SLOType(*args, **kwargs)

Bases: ModelSimple

The type of the service level objective.

Parameters:

• value (str) – Must be one of [“metric”, “monitor”, “time_slice”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_type_numeric module

class SLOTypeNumeric(arg: None)

class SLOTypeNumeric(arg: ModelComposed)

class SLOTypeNumeric(*args, **kwargs)

Bases: ModelSimple

A numeric representation of the type of the service level objective (0 for

monitor, 1 for metric). Always included in service level objective responses. Ignored in create/update requests.

Parameters:

• value (int) – Must be one of [0, 1, 2].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.slo_widget_definition module

class SLOWidgetDefinition(arg: None)

class SLOWidgetDefinition(arg: ModelComposed)

class SLOWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Use the SLO and uptime widget to track your SLOs (Service Level Objectives) and uptime on screenboards and timeboards.

Parameters:

• additional_query_filters (str, optional) – Additional filters applied to the SLO query.

• global_time_target (str, optional) – Defined global time target.

• show_error_budget (bool, optional) – Defined error budget.

• slo_id (str, optional) – ID of the SLO displayed.

• time_windows ([WidgetTimeWindows], optional) – Times being monitored.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (SLOWidgetDefinitionType) – Type of the SLO widget.

• view_mode (WidgetViewMode, optional) – Define how you want the SLO to be displayed.

• view_type (str) – Type of view displayed by the widget.

datadog_api_client.v1.model.slo_widget_definition_type module

class SLOWidgetDefinitionType(arg: None)

class SLOWidgetDefinitionType(arg: ModelComposed)

class SLOWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the SLO widget.

Parameters:

• value (str) – If omitted defaults to “slo”. Must be one of [“slo”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.split_config module

class SplitConfig(arg: None)

class SplitConfig(arg: ModelComposed)

class SplitConfig(*args, **kwargs)

Bases: ModelNormal

Encapsulates all user choices about how to split a graph.

Parameters:

• limit (int) – Maximum number of graphs to display in the widget.

• sort (SplitSort) – Controls the order in which graphs appear in the split.

• split_dimensions ([SplitDimension]) – The dimension(s) on which to split the graph

• static_splits ([[SplitVectorEntryItem]], optional) – Manual selection of tags making split graph widget static

datadog_api_client.v1.model.split_config_sort_compute module

class SplitConfigSortCompute(arg: None)

class SplitConfigSortCompute(arg: ModelComposed)

class SplitConfigSortCompute(*args, **kwargs)

Bases: ModelNormal

Defines the metric and aggregation used as the sort value.

Parameters:

• aggregation (str) – How to aggregate the sort metric for the purposes of ordering.

• metric (str) – The metric to use for sorting graphs.

datadog_api_client.v1.model.split_dimension module

class SplitDimension(arg: None)

class SplitDimension(arg: ModelComposed)

class SplitDimension(*args, **kwargs)

Bases: ModelNormal

The property by which the graph splits

Parameters:

one_graph_per (str) – The system interprets this attribute differently depending on the data source of the query being split. For metrics, it’s a tag. For the events platform, it’s an attribute or tag.

datadog_api_client.v1.model.split_graph_source_widget_definition module

class SplitGraphSourceWidgetDefinition(arg: None)

class SplitGraphSourceWidgetDefinition(arg: ModelComposed)

class SplitGraphSourceWidgetDefinition(*args, **kwargs)

Bases: ModelComposed

The original widget we are splitting on.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• requests ([ChangeWidgetRequest]) –

  Array of one request object to display in the widget.

  See the dedicated [Request JSON schema documentation](https://docs.datadoghq.com/dashboards/graphing_json/request_json)

  to learn how to build the REQUEST_SCHEMA.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (ChangeWidgetDefinitionType) – Type of the change widget.

• style (GeomapWidgetDefinitionStyle) – The style to apply to the widget.

• view (GeomapWidgetDefinitionView) – The view of the world that the map should render.

• autoscale (bool, optional) – Whether to use auto-scaling or not.

• custom_unit (str, optional) – Display a unit of your choice on the widget.

• precision (int, optional) – Number of decimals to show. If not defined, the widget uses the raw value.

• text_align (WidgetTextAlign, optional) – How to align the text on the widget.

• timeseries_background (TimeseriesBackground, optional) – Set a timeseries on the widget background.

• color_by_groups ([str], optional) – List of groups used for colors.

• xaxis (WidgetAxis, optional) – Axis controls for the widget.

• yaxis (WidgetAxis, optional) – Axis controls for the widget.

• hide_total (bool, optional) – Show the total value in this widget.

• legend (SunburstWidgetLegend, optional) – Configuration of the legend.

• has_search_bar (TableWidgetHasSearchBar, optional) – Controls the display of the search bar.

• events ([WidgetEvent], optional) – List of widget events.

• legend_columns ([TimeseriesWidgetLegendColumn], optional) – Columns displayed in the legend.

• legend_layout (TimeseriesWidgetLegendLayout, optional) – Layout of the legend.

• legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.

• markers ([WidgetMarker], optional) – List of markers.

• right_yaxis (WidgetAxis, optional) – Axis controls for the widget.

• show_legend (bool, optional) – (screenboard only) Show the legend for this widget.

• color_by (TreeMapColorBy, optional) – (deprecated) The attribute formerly used to determine color in the widget.

• group_by (TreeMapGroupBy, optional) – (deprecated) The attribute formerly used to group elements in the widget.

• size_by (TreeMapSizeBy, optional) – (deprecated) The attribute formerly used to determine size in the widget.

datadog_api_client.v1.model.split_graph_viz_size module

class SplitGraphVizSize(arg: None)

class SplitGraphVizSize(arg: ModelComposed)

class SplitGraphVizSize(*args, **kwargs)

Bases: ModelSimple

Size of the individual graphs in the split.

Parameters:

• value (str) – Must be one of [“xs”, “sm”, “md”, “lg”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.split_graph_widget_definition module

class SplitGraphWidgetDefinition(arg: None)

class SplitGraphWidgetDefinition(arg: ModelComposed)

class SplitGraphWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The split graph widget allows you to create repeating units of a graph - one for each value in a group (for example: one per service)

Parameters:

• has_uniform_y_axes (bool, optional) – Normalize y axes across graphs

• size (SplitGraphVizSize) – Size of the individual graphs in the split.

• source_widget_definition (SplitGraphSourceWidgetDefinition) – The original widget we are splitting on.

• split_config (SplitConfig) – Encapsulates all user choices about how to split a graph.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• type (SplitGraphWidgetDefinitionType) – Type of the split graph widget

datadog_api_client.v1.model.split_graph_widget_definition_type module

class SplitGraphWidgetDefinitionType(arg: None)

class SplitGraphWidgetDefinitionType(arg: ModelComposed)

class SplitGraphWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the split graph widget

Parameters:

• value (str) – If omitted defaults to “split_group”. Must be one of [“split_group”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.split_sort module

class SplitSort(arg: None)

class SplitSort(arg: ModelComposed)

class SplitSort(*args, **kwargs)

Bases: ModelNormal

Controls the order in which graphs appear in the split.

Parameters:

• compute (SplitConfigSortCompute, optional) – Defines the metric and aggregation used as the sort value.

• order (WidgetSort) – Widget sorting methods.

datadog_api_client.v1.model.split_vector_entry_item module

class SplitVectorEntryItem(arg: None)

class SplitVectorEntryItem(arg: ModelComposed)

class SplitVectorEntryItem(*args, **kwargs)

Bases: ModelNormal

The split graph list contains a graph for each value of the split dimension.

Parameters:

• tag_key (str) – The tag key.

• tag_values ([str]) – The tag values.

datadog_api_client.v1.model.successful_signal_update_response module

class SuccessfulSignalUpdateResponse(arg: None)

class SuccessfulSignalUpdateResponse(arg: ModelComposed)

class SuccessfulSignalUpdateResponse(*args, **kwargs)

Bases: ModelNormal

Updated signal data following a successfully performed update.

Parameters:

status (str, optional) – Status of the response.

datadog_api_client.v1.model.sunburst_widget_definition module

class SunburstWidgetDefinition(arg: None)

class SunburstWidgetDefinition(arg: ModelComposed)

class SunburstWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

Sunbursts are spot on to highlight how groups contribute to the total of a query.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• hide_total (bool, optional) – Show the total value in this widget.

• legend (SunburstWidgetLegend, optional) – Configuration of the legend.

• requests ([SunburstWidgetRequest]) – List of sunburst widget requests.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (SunburstWidgetDefinitionType) – Type of the Sunburst widget.

datadog_api_client.v1.model.sunburst_widget_definition_type module

class SunburstWidgetDefinitionType(arg: None)

class SunburstWidgetDefinitionType(arg: ModelComposed)

class SunburstWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the Sunburst widget.

Parameters:

• value (str) – If omitted defaults to “sunburst”. Must be one of [“sunburst”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.sunburst_widget_legend module

class SunburstWidgetLegend(arg: None)

class SunburstWidgetLegend(arg: ModelComposed)

class SunburstWidgetLegend(*args, **kwargs)

Bases: ModelComposed

Configuration of the legend.

Parameters:

• type (SunburstWidgetLegendTableType) – Whether or not to show a table legend.

• hide_percent (bool, optional) – Whether to hide the percentages of the groups.

• hide_value (bool, optional) – Whether to hide the values of the groups.

datadog_api_client.v1.model.sunburst_widget_legend_inline_automatic module

class SunburstWidgetLegendInlineAutomatic(arg: None)

class SunburstWidgetLegendInlineAutomatic(arg: ModelComposed)

class SunburstWidgetLegendInlineAutomatic(*args, **kwargs)

Bases: ModelNormal

Configuration of inline or automatic legends.

Parameters:

• hide_percent (bool, optional) – Whether to hide the percentages of the groups.

• hide_value (bool, optional) – Whether to hide the values of the groups.

• type (SunburstWidgetLegendInlineAutomaticType) – Whether to show the legend inline or let it be automatically generated.

datadog_api_client.v1.model.sunburst_widget_legend_inline_automatic_type module

class SunburstWidgetLegendInlineAutomaticType(arg: None)

class SunburstWidgetLegendInlineAutomaticType(arg: ModelComposed)

class SunburstWidgetLegendInlineAutomaticType(*args, **kwargs)

Bases: ModelSimple

Whether to show the legend inline or let it be automatically generated.

Parameters:

• value (str) – Must be one of [“inline”, “automatic”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.sunburst_widget_legend_table module

class SunburstWidgetLegendTable(arg: None)

class SunburstWidgetLegendTable(arg: ModelComposed)

class SunburstWidgetLegendTable(*args, **kwargs)

Bases: ModelNormal

Configuration of table-based legend.

Parameters:

type (SunburstWidgetLegendTableType) – Whether or not to show a table legend.

datadog_api_client.v1.model.sunburst_widget_legend_table_type module

class SunburstWidgetLegendTableType(arg: None)

class SunburstWidgetLegendTableType(arg: ModelComposed)

class SunburstWidgetLegendTableType(*args, **kwargs)

Bases: ModelSimple

Whether or not to show a table legend.

Parameters:

• value (str) – Must be one of [“table”, “none”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.sunburst_widget_request module

class SunburstWidgetRequest(arg: None)

class SunburstWidgetRequest(arg: ModelComposed)

class SunburstWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Request definition of sunburst widget.

Parameters:

• apm_query (LogQueryDefinition, optional) – The log query.

• audit_query (LogQueryDefinition, optional) – The log query.

• event_query (LogQueryDefinition, optional) – The log query.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Widget query.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• style (WidgetStyle, optional) – Widget style definition.

datadog_api_client.v1.model.synthetics_api_step module

class SyntheticsAPIStep(arg: None)

class SyntheticsAPIStep(arg: ModelComposed)

class SyntheticsAPIStep(*args, **kwargs)

Bases: ModelComposed

The steps used in a Synthetic multi-step API test.

Parameters:

• allow_failure (bool, optional) – Determines whether or not to continue with test if this step fails.

• assertions ([SyntheticsAssertion]) – Array of assertions used for the test.

• exit_if_succeed (bool, optional) – Determines whether or not to exit the test if the step succeeds.

• extracted_values ([SyntheticsParsingOptions], optional) – Array of values to parse and save as variables from the response.

• extracted_values_from_script (str, optional) – Generate variables using JavaScript.

• id (str, optional) – ID of the step.

• is_critical (bool, optional) – Determines whether or not to consider the entire test as failed if this step fails. Can be used only if allowFailure is true.

• name (str) – The name of the step.

• request (SyntheticsTestRequest) – Object describing the Synthetic test request.

• retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.

• subtype (SyntheticsAPITestStepSubtype) – The subtype of the Synthetic multi-step API test step.

• value (int) – The time to wait in seconds. Minimum value: 0. Maximum value: 180.

datadog_api_client.v1.model.synthetics_api_test module

class SyntheticsAPITest(arg: None)

class SyntheticsAPITest(arg: ModelComposed)

class SyntheticsAPITest(*args, **kwargs)

Bases: ModelNormal

Object containing details about a Synthetic API test.

Parameters:

• config (SyntheticsAPITestConfig) – Configuration object for a Synthetic API test.

• locations ([str]) – Array of locations used to run the test.

• message (str) – Notification message associated with the test.

• monitor_id (int, optional) – The associated monitor ID.

• name (str) – Name of the test.

• options (SyntheticsTestOptions) – Object describing the extra options for a Synthetic test.

• public_id (str, optional) – The public ID for the test.

• status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.

• subtype (SyntheticsTestDetailsSubType, optional) – The subtype of the Synthetic API test, http , ssl , tcp , dns , icmp , udp , websocket , grpc or multi.

• tags ([str], optional) – Array of tags attached to the test.

• type (SyntheticsAPITestType) – Type of the Synthetic test, api.

datadog_api_client.v1.model.synthetics_api_test_config module

class SyntheticsAPITestConfig(arg: None)

class SyntheticsAPITestConfig(arg: ModelComposed)

class SyntheticsAPITestConfig(*args, **kwargs)

Bases: ModelNormal

Configuration object for a Synthetic API test.

Parameters:

• assertions ([SyntheticsAssertion], optional) – Array of assertions used for the test. Required for single API tests.

• config_variables ([SyntheticsConfigVariable], optional) – Array of variables used for the test.

• request (SyntheticsTestRequest, optional) – Object describing the Synthetic test request.

• steps ([SyntheticsAPIStep], optional) – When the test subtype is multi , the steps of the test.

• variables_from_script (str, optional) – Variables defined from JavaScript code.

datadog_api_client.v1.model.synthetics_api_test_failure_code module

class SyntheticsApiTestFailureCode(arg: None)

class SyntheticsApiTestFailureCode(arg: ModelComposed)

class SyntheticsApiTestFailureCode(*args, **kwargs)

Bases: ModelSimple

Error code that can be returned by a Synthetic test.

Parameters:

• value (str) – Must be one of [“BODY_TOO_LARGE”, “DENIED”, “TOO_MANY_REDIRECTS”, “AUTHENTICATION_ERROR”, “DECRYPTION”, “INVALID_CHAR_IN_HEADER”, “HEADER_TOO_LARGE”, “HEADERS_INCOMPATIBLE_CONTENT_LENGTH”, “INVALID_REQUEST”, “REQUIRES_UPDATE”, “UNESCAPED_CHARACTERS_IN_REQUEST_PATH”, “MALFORMED_RESPONSE”, “INCORRECT_ASSERTION”, “CONNREFUSED”, “CONNRESET”, “DNS”, “HOSTUNREACH”, “NETUNREACH”, “TIMEOUT”, “SSL”, “OCSP”, “INVALID_TEST”, “TUNNEL”, “WEBSOCKET”, “UNKNOWN”, “INTERNAL_ERROR”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_api_test_result_data module

class SyntheticsAPITestResultData(arg: None)

class SyntheticsAPITestResultData(arg: ModelComposed)

class SyntheticsAPITestResultData(*args, **kwargs)

Bases: ModelNormal

Object containing results for your Synthetic API test.

Parameters:

• cert (SyntheticsSSLCertificate, optional) – Object describing the SSL certificate used for a Synthetic test.

• event_type (SyntheticsTestProcessStatus, optional) – Status of a Synthetic test.

• failure (SyntheticsApiTestResultFailure, optional) – The API test failure details.

• http_status_code (int, optional) – The API test HTTP status code.

• request_headers ({str: (dict,)}, optional) – Request header object used for the API test.

• response_body (str, optional) – Response body returned for the API test.

• response_headers ({str: (bool, date, datetime, dict, float, int, list, str, UUID, none_type,)}, optional) – Response headers returned for the API test.

• response_size (int, optional) – Global size in byte of the API test response.

• timings (SyntheticsTiming, optional) – Object containing all metrics and their values collected for a Synthetic API test. See the Synthetic Monitoring Metrics documentation.

datadog_api_client.v1.model.synthetics_api_test_result_failure module

class SyntheticsApiTestResultFailure(arg: None)

class SyntheticsApiTestResultFailure(arg: ModelComposed)

class SyntheticsApiTestResultFailure(*args, **kwargs)

Bases: ModelNormal

The API test failure details.

Parameters:

• code (SyntheticsApiTestFailureCode, optional) – Error code that can be returned by a Synthetic test.

• message (str, optional) – The API test error message.

datadog_api_client.v1.model.synthetics_api_test_result_full module

class SyntheticsAPITestResultFull(arg: None)

class SyntheticsAPITestResultFull(arg: ModelComposed)

class SyntheticsAPITestResultFull(*args, **kwargs)

Bases: ModelNormal

Object returned describing a API test result.

Parameters:

• check (SyntheticsAPITestResultFullCheck, optional) – Object describing the API test configuration.

• check_time (float, optional) – When the API test was conducted.

• check_version (int, optional) – Version of the API test used.

• probe_dc (str, optional) – Locations for which to query the API test results.

• result (SyntheticsAPITestResultData, optional) – Object containing results for your Synthetic API test.

• result_id (str, optional) – ID of the API test result.

• status (SyntheticsTestMonitorStatus, optional) –

  The status of your Synthetic monitor.

  • O for not triggered

  • 1 for triggered

  • 2 for no data

datadog_api_client.v1.model.synthetics_api_test_result_full_check module

class SyntheticsAPITestResultFullCheck(arg: None)

class SyntheticsAPITestResultFullCheck(arg: ModelComposed)

class SyntheticsAPITestResultFullCheck(*args, **kwargs)

Bases: ModelNormal

Object describing the API test configuration.

Parameters:

config (SyntheticsTestConfig) – Configuration object for a Synthetic test.

datadog_api_client.v1.model.synthetics_api_test_result_short module

class SyntheticsAPITestResultShort(arg: None)

class SyntheticsAPITestResultShort(arg: ModelComposed)

class SyntheticsAPITestResultShort(*args, **kwargs)

Bases: ModelNormal

Object with the results of a single Synthetic API test.

Parameters:

• check_time (float, optional) – Last time the API test was performed.

• probe_dc (str, optional) – Location from which the API test was performed.

• result (SyntheticsAPITestResultShortResult, optional) – Result of the last API test run.

• result_id (str, optional) – ID of the API test result.

• status (SyntheticsTestMonitorStatus, optional) –

  The status of your Synthetic monitor.

  • O for not triggered

  • 1 for triggered

  • 2 for no data

datadog_api_client.v1.model.synthetics_api_test_result_short_result module

class SyntheticsAPITestResultShortResult(arg: None)

class SyntheticsAPITestResultShortResult(arg: ModelComposed)

class SyntheticsAPITestResultShortResult(*args, **kwargs)

Bases: ModelNormal

Result of the last API test run.

Parameters:

• passed (bool, optional) – Describes if the test run has passed or failed.

• timings (SyntheticsTiming, optional) –

  Object containing all metrics and their values collected for a Synthetic API test. See the Synthetic Monitoring Metrics documentation.

datadog_api_client.v1.model.synthetics_api_test_step module

class SyntheticsAPITestStep(arg: None)

class SyntheticsAPITestStep(arg: ModelComposed)

class SyntheticsAPITestStep(*args, **kwargs)

Bases: ModelNormal

The Test step used in a Synthetic multi-step API test.

Parameters:

• allow_failure (bool, optional) – Determines whether or not to continue with test if this step fails.

• assertions ([SyntheticsAssertion]) – Array of assertions used for the test.

• exit_if_succeed (bool, optional) – Determines whether or not to exit the test if the step succeeds.

• extracted_values ([SyntheticsParsingOptions], optional) – Array of values to parse and save as variables from the response.

• extracted_values_from_script (str, optional) – Generate variables using JavaScript.

• id (str, optional) – ID of the step.

• is_critical (bool, optional) – Determines whether or not to consider the entire test as failed if this step fails. Can be used only if allowFailure is true.

• name (str) – The name of the step.

• request (SyntheticsTestRequest) – Object describing the Synthetic test request.

• retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.

• subtype (SyntheticsAPITestStepSubtype) – The subtype of the Synthetic multi-step API test step.

datadog_api_client.v1.model.synthetics_api_test_step_subtype module

class SyntheticsAPITestStepSubtype(arg: None)

class SyntheticsAPITestStepSubtype(arg: ModelComposed)

class SyntheticsAPITestStepSubtype(*args, **kwargs)

Bases: ModelSimple

The subtype of the Synthetic multi-step API test step.

Parameters:

• value (str) – Must be one of [“http”, “grpc”, “ssl”, “dns”, “tcp”, “udp”, “icmp”, “websocket”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_api_test_type module

class SyntheticsAPITestType(arg: None)

class SyntheticsAPITestType(arg: ModelComposed)

class SyntheticsAPITestType(*args, **kwargs)

Bases: ModelSimple

Type of the Synthetic test, api.

Parameters:

• value (str) – If omitted defaults to “api”. Must be one of [“api”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_api_wait_step module

class SyntheticsAPIWaitStep(arg: None)

class SyntheticsAPIWaitStep(arg: ModelComposed)

class SyntheticsAPIWaitStep(*args, **kwargs)

Bases: ModelNormal

The Wait step used in a Synthetic multi-step API test.

Parameters:

• id (str, optional) – ID of the step.

• name (str) – The name of the step.

• subtype (SyntheticsAPIWaitStepSubtype) – The subtype of the Synthetic multi-step API wait step.

• value (int) – The time to wait in seconds. Minimum value: 0. Maximum value: 180.

datadog_api_client.v1.model.synthetics_api_wait_step_subtype module

class SyntheticsAPIWaitStepSubtype(arg: None)

class SyntheticsAPIWaitStepSubtype(arg: ModelComposed)

class SyntheticsAPIWaitStepSubtype(*args, **kwargs)

Bases: ModelSimple

The subtype of the Synthetic multi-step API wait step.

Parameters:

• value (str) – If omitted defaults to “wait”. Must be one of [“wait”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion module

class SyntheticsAssertion(arg: None)

class SyntheticsAssertion(arg: ModelComposed)

class SyntheticsAssertion(*args, **kwargs)

Bases: ModelComposed

Object describing the assertions type, their associated operator, which property they apply, and upon which target.

Parameters:

• operator (SyntheticsAssertionOperator) – Assertion operator to apply.

• _property (str, optional) – The associated assertion property.

• target (SyntheticsAssertionTargetValue) – Value used by the operator in assertions. Can be either a number or string.

• timings_scope (SyntheticsAssertionTimingsScope, optional) – Timings scope for response time assertions.

• type (SyntheticsAssertionType) – Type of the assertion.

• code (str) – The JavaScript code that performs the assertions.

datadog_api_client.v1.model.synthetics_assertion_body_hash_operator module

class SyntheticsAssertionBodyHashOperator(arg: None)

class SyntheticsAssertionBodyHashOperator(arg: ModelComposed)

class SyntheticsAssertionBodyHashOperator(*args, **kwargs)

Bases: ModelSimple

Assertion operator to apply.

Parameters:

• value (str) – Must be one of [“md5”, “sha1”, “sha256”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_body_hash_target module

class SyntheticsAssertionBodyHashTarget(arg: None)

class SyntheticsAssertionBodyHashTarget(arg: ModelComposed)

class SyntheticsAssertionBodyHashTarget(*args, **kwargs)

Bases: ModelNormal

An assertion which targets body hash.

Parameters:

• operator (SyntheticsAssertionBodyHashOperator) – Assertion operator to apply.

• target (SyntheticsAssertionTargetValue) – Value used by the operator in assertions. Can be either a number or string.

• type (SyntheticsAssertionBodyHashType) – Type of the assertion.

datadog_api_client.v1.model.synthetics_assertion_body_hash_type module

class SyntheticsAssertionBodyHashType(arg: None)

class SyntheticsAssertionBodyHashType(arg: ModelComposed)

class SyntheticsAssertionBodyHashType(*args, **kwargs)

Bases: ModelSimple

Type of the assertion.

Parameters:

• value (str) – If omitted defaults to “bodyHash”. Must be one of [“bodyHash”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_javascript module

class SyntheticsAssertionJavascript(arg: None)

class SyntheticsAssertionJavascript(arg: ModelComposed)

class SyntheticsAssertionJavascript(*args, **kwargs)

Bases: ModelNormal

A JavaScript assertion.

Parameters:

• code (str) – The JavaScript code that performs the assertions.

• type (SyntheticsAssertionJavascriptType) – Type of the assertion.

datadog_api_client.v1.model.synthetics_assertion_javascript_type module

class SyntheticsAssertionJavascriptType(arg: None)

class SyntheticsAssertionJavascriptType(arg: ModelComposed)

class SyntheticsAssertionJavascriptType(*args, **kwargs)

Bases: ModelSimple

Type of the assertion.

Parameters:

• value (str) – If omitted defaults to “javascript”. Must be one of [“javascript”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_json_path_operator module

class SyntheticsAssertionJSONPathOperator(arg: None)

class SyntheticsAssertionJSONPathOperator(arg: ModelComposed)

class SyntheticsAssertionJSONPathOperator(*args, **kwargs)

Bases: ModelSimple

Assertion operator to apply.

Parameters:

• value (str) – If omitted defaults to “validatesJSONPath”. Must be one of [“validatesJSONPath”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_json_path_target module

class SyntheticsAssertionJSONPathTarget(arg: None)

class SyntheticsAssertionJSONPathTarget(arg: ModelComposed)

class SyntheticsAssertionJSONPathTarget(*args, **kwargs)

Bases: ModelNormal

An assertion for the validatesJSONPath operator.

Parameters:

• operator (SyntheticsAssertionJSONPathOperator) – Assertion operator to apply.

• _property (str, optional) – The associated assertion property.

• target (SyntheticsAssertionJSONPathTargetTarget, optional) – Composed target for validatesJSONPath operator.

• type (SyntheticsAssertionType) – Type of the assertion.

datadog_api_client.v1.model.synthetics_assertion_json_path_target_target module

class SyntheticsAssertionJSONPathTargetTarget(arg: None)

class SyntheticsAssertionJSONPathTargetTarget(arg: ModelComposed)

class SyntheticsAssertionJSONPathTargetTarget(*args, **kwargs)

Bases: ModelNormal

Composed target for validatesJSONPath operator.

Parameters:

• elements_operator (str, optional) – The element from the list of results to assert on. To choose from the first element in the list firstElementMatches , every element in the list everyElementMatches , at least one element in the list atLeastOneElementMatches or the serialized value of the list serializationMatches.

• json_path (str, optional) – The JSON path to assert.

• operator (str, optional) – The specific operator to use on the path.

• target_value (SyntheticsAssertionTargetValue, optional) – Value used by the operator in assertions. Can be either a number or string.

datadog_api_client.v1.model.synthetics_assertion_json_schema_meta_schema module

class SyntheticsAssertionJSONSchemaMetaSchema(arg: None)

class SyntheticsAssertionJSONSchemaMetaSchema(arg: ModelComposed)

class SyntheticsAssertionJSONSchemaMetaSchema(*args, **kwargs)

Bases: ModelSimple

The JSON Schema meta-schema version used in the assertion.

Parameters:

• value (str) – Must be one of [“draft-07”, “draft-06”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_json_schema_operator module

class SyntheticsAssertionJSONSchemaOperator(arg: None)

class SyntheticsAssertionJSONSchemaOperator(arg: ModelComposed)

class SyntheticsAssertionJSONSchemaOperator(*args, **kwargs)

Bases: ModelSimple

Assertion operator to apply.

Parameters:

• value (str) – If omitted defaults to “validatesJSONSchema”. Must be one of [“validatesJSONSchema”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_json_schema_target module

class SyntheticsAssertionJSONSchemaTarget(arg: None)

class SyntheticsAssertionJSONSchemaTarget(arg: ModelComposed)

class SyntheticsAssertionJSONSchemaTarget(*args, **kwargs)

Bases: ModelNormal

An assertion for the validatesJSONSchema operator.

Parameters:

• operator (SyntheticsAssertionJSONSchemaOperator) – Assertion operator to apply.

• target (SyntheticsAssertionJSONSchemaTargetTarget, optional) – Composed target for validatesJSONSchema operator.

• type (SyntheticsAssertionType) – Type of the assertion.

datadog_api_client.v1.model.synthetics_assertion_json_schema_target_target module

class SyntheticsAssertionJSONSchemaTargetTarget(arg: None)

class SyntheticsAssertionJSONSchemaTargetTarget(arg: ModelComposed)

class SyntheticsAssertionJSONSchemaTargetTarget(*args, **kwargs)

Bases: ModelNormal

Composed target for validatesJSONSchema operator.

Parameters:

• json_schema (str, optional) – The JSON Schema to assert.

• meta_schema (SyntheticsAssertionJSONSchemaMetaSchema, optional) – The JSON Schema meta-schema version used in the assertion.

datadog_api_client.v1.model.synthetics_assertion_operator module

class SyntheticsAssertionOperator(arg: None)

class SyntheticsAssertionOperator(arg: ModelComposed)

class SyntheticsAssertionOperator(*args, **kwargs)

Bases: ModelSimple

Assertion operator to apply.

Parameters:

• value (str) – Must be one of [“contains”, “doesNotContain”, “is”, “isNot”, “lessThan”, “lessThanOrEqual”, “moreThan”, “moreThanOrEqual”, “matches”, “doesNotMatch”, “validates”, “isInMoreThan”, “isInLessThan”, “doesNotExist”, “isUndefined”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_target module

class SyntheticsAssertionTarget(arg: None)

class SyntheticsAssertionTarget(arg: ModelComposed)

class SyntheticsAssertionTarget(*args, **kwargs)

Bases: ModelNormal

An assertion which uses a simple target.

Parameters:

• operator (SyntheticsAssertionOperator) – Assertion operator to apply.

• _property (str, optional) – The associated assertion property.

• target (SyntheticsAssertionTargetValue) – Value used by the operator in assertions. Can be either a number or string.

• timings_scope (SyntheticsAssertionTimingsScope, optional) – Timings scope for response time assertions.

• type (SyntheticsAssertionType) – Type of the assertion.

datadog_api_client.v1.model.synthetics_assertion_target_value module

class SyntheticsAssertionTargetValue(arg: None)

class SyntheticsAssertionTargetValue(arg: ModelComposed)

class SyntheticsAssertionTargetValue(*args, **kwargs)

Bases: ModelComposed

Value used by the operator in assertions. Can be either a number or string.

datadog_api_client.v1.model.synthetics_assertion_timings_scope module

class SyntheticsAssertionTimingsScope(arg: None)

class SyntheticsAssertionTimingsScope(arg: ModelComposed)

class SyntheticsAssertionTimingsScope(*args, **kwargs)

Bases: ModelSimple

Timings scope for response time assertions.

Parameters:

• value (str) – Must be one of [“all”, “withoutDNS”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_type module

class SyntheticsAssertionType(arg: None)

class SyntheticsAssertionType(arg: ModelComposed)

class SyntheticsAssertionType(*args, **kwargs)

Bases: ModelSimple

Type of the assertion.

Parameters:

• value (str) – Must be one of [“body”, “header”, “statusCode”, “certificate”, “responseTime”, “property”, “recordEvery”, “recordSome”, “tlsVersion”, “minTlsVersion”, “latency”, “packetLossPercentage”, “packetsReceived”, “networkHop”, “receivedMessage”, “grpcHealthcheckStatus”, “grpcMetadata”, “grpcProto”, “connection”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_x_path_operator module

class SyntheticsAssertionXPathOperator(arg: None)

class SyntheticsAssertionXPathOperator(arg: ModelComposed)

class SyntheticsAssertionXPathOperator(*args, **kwargs)

Bases: ModelSimple

Assertion operator to apply.

Parameters:

• value (str) – If omitted defaults to “validatesXPath”. Must be one of [“validatesXPath”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_assertion_x_path_target module

class SyntheticsAssertionXPathTarget(arg: None)

class SyntheticsAssertionXPathTarget(arg: ModelComposed)

class SyntheticsAssertionXPathTarget(*args, **kwargs)

Bases: ModelNormal

An assertion for the validatesXPath operator.

Parameters:

• operator (SyntheticsAssertionXPathOperator) – Assertion operator to apply.

• _property (str, optional) – The associated assertion property.

• target (SyntheticsAssertionXPathTargetTarget, optional) – Composed target for validatesXPath operator.

• type (SyntheticsAssertionType) – Type of the assertion.

datadog_api_client.v1.model.synthetics_assertion_x_path_target_target module

class SyntheticsAssertionXPathTargetTarget(arg: None)

class SyntheticsAssertionXPathTargetTarget(arg: ModelComposed)

class SyntheticsAssertionXPathTargetTarget(*args, **kwargs)

Bases: ModelNormal

Composed target for validatesXPath operator.

Parameters:

• operator (str, optional) – The specific operator to use on the path.

• target_value (SyntheticsAssertionTargetValue, optional) – Value used by the operator in assertions. Can be either a number or string.

• x_path (str, optional) – The X path to assert.

datadog_api_client.v1.model.synthetics_basic_auth module

class SyntheticsBasicAuth(arg: None)

class SyntheticsBasicAuth(arg: ModelComposed)

class SyntheticsBasicAuth(*args, **kwargs)

Bases: ModelComposed

Object to handle basic authentication when performing the test.

Parameters:

• password (str, optional) – Password to use for the basic authentication.

• type (SyntheticsBasicAuthWebType, optional) – The type of basic authentication to use when performing the test.

• username (str, optional) – Username to use for the basic authentication.

• access_key (str) – Access key for the SIGV4 authentication.

• region (str, optional) – Region for the SIGV4 authentication.

• secret_key (str) – Secret key for the SIGV4 authentication.

• service_name (str, optional) – Service name for the SIGV4 authentication.

• session_token (str, optional) – Session token for the SIGV4 authentication.

• domain (str, optional) – Domain for the authentication to use when performing the test.

• workstation (str, optional) – Workstation for the authentication to use when performing the test.

• access_token_url (str) – Access token URL to use when performing the authentication.

• audience (str, optional) – Audience to use when performing the authentication.

• client_id (str) – Client ID to use when performing the authentication.

• client_secret (str) – Client secret to use when performing the authentication.

• resource (str, optional) – Resource to use when performing the authentication.

• scope (str, optional) – Scope to use when performing the authentication.

• token_api_authentication (SyntheticsBasicAuthOauthTokenApiAuthentication) – Type of token to use when performing the authentication.

datadog_api_client.v1.model.synthetics_basic_auth_digest module

class SyntheticsBasicAuthDigest(arg: None)

class SyntheticsBasicAuthDigest(arg: ModelComposed)

class SyntheticsBasicAuthDigest(*args, **kwargs)

Bases: ModelNormal

Object to handle digest authentication when performing the test.

Parameters:

• password (str) – Password to use for the digest authentication.

• type (SyntheticsBasicAuthDigestType) – The type of basic authentication to use when performing the test.

• username (str) – Username to use for the digest authentication.

datadog_api_client.v1.model.synthetics_basic_auth_digest_type module

class SyntheticsBasicAuthDigestType(arg: None)

class SyntheticsBasicAuthDigestType(arg: ModelComposed)

class SyntheticsBasicAuthDigestType(*args, **kwargs)

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

• value (str) – If omitted defaults to “digest”. Must be one of [“digest”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_basic_auth_ntlm module

class SyntheticsBasicAuthNTLM(arg: None)

class SyntheticsBasicAuthNTLM(arg: ModelComposed)

class SyntheticsBasicAuthNTLM(*args, **kwargs)

Bases: ModelNormal

Object to handle NTLM authentication when performing the test.

Parameters:

• domain (str, optional) – Domain for the authentication to use when performing the test.

• password (str, optional) – Password for the authentication to use when performing the test.

• type (SyntheticsBasicAuthNTLMType) – The type of authentication to use when performing the test.

• username (str, optional) – Username for the authentication to use when performing the test.

• workstation (str, optional) – Workstation for the authentication to use when performing the test.

datadog_api_client.v1.model.synthetics_basic_auth_ntlm_type module

class SyntheticsBasicAuthNTLMType(arg: None)

class SyntheticsBasicAuthNTLMType(arg: ModelComposed)

class SyntheticsBasicAuthNTLMType(*args, **kwargs)

Bases: ModelSimple

The type of authentication to use when performing the test.

Parameters:

• value (str) – If omitted defaults to “ntlm”. Must be one of [“ntlm”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_basic_auth_oauth_client module

class SyntheticsBasicAuthOauthClient(arg: None)

class SyntheticsBasicAuthOauthClient(arg: ModelComposed)

class SyntheticsBasicAuthOauthClient(*args, **kwargs)

Bases: ModelNormal

Object to handle oauth client authentication when performing the test.

Parameters:

• access_token_url (str) – Access token URL to use when performing the authentication.

• audience (str, optional) – Audience to use when performing the authentication.

• client_id (str) – Client ID to use when performing the authentication.

• client_secret (str) – Client secret to use when performing the authentication.

• resource (str, optional) – Resource to use when performing the authentication.

• scope (str, optional) – Scope to use when performing the authentication.

• token_api_authentication (SyntheticsBasicAuthOauthTokenApiAuthentication) – Type of token to use when performing the authentication.

• type (SyntheticsBasicAuthOauthClientType) – The type of basic authentication to use when performing the test.

datadog_api_client.v1.model.synthetics_basic_auth_oauth_client_type module

class SyntheticsBasicAuthOauthClientType(arg: None)

class SyntheticsBasicAuthOauthClientType(arg: ModelComposed)

class SyntheticsBasicAuthOauthClientType(*args, **kwargs)

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

• value (str) – If omitted defaults to “oauth-client”. Must be one of [“oauth-client”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_basic_auth_oauth_rop module

class SyntheticsBasicAuthOauthROP(arg: None)

class SyntheticsBasicAuthOauthROP(arg: ModelComposed)

class SyntheticsBasicAuthOauthROP(*args, **kwargs)

Bases: ModelNormal

Object to handle oauth rop authentication when performing the test.

Parameters:

• access_token_url (str) – Access token URL to use when performing the authentication.

• audience (str, optional) – Audience to use when performing the authentication.

• client_id (str, optional) – Client ID to use when performing the authentication.

• client_secret (str, optional) – Client secret to use when performing the authentication.

• password (str) – Password to use when performing the authentication.

• resource (str, optional) – Resource to use when performing the authentication.

• scope (str, optional) – Scope to use when performing the authentication.

• token_api_authentication (SyntheticsBasicAuthOauthTokenApiAuthentication) – Type of token to use when performing the authentication.

• type (SyntheticsBasicAuthOauthROPType) – The type of basic authentication to use when performing the test.

• username (str) – Username to use when performing the authentication.

datadog_api_client.v1.model.synthetics_basic_auth_oauth_rop_type module

class SyntheticsBasicAuthOauthROPType(arg: None)

class SyntheticsBasicAuthOauthROPType(arg: ModelComposed)

class SyntheticsBasicAuthOauthROPType(*args, **kwargs)

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

• value (str) – If omitted defaults to “oauth-rop”. Must be one of [“oauth-rop”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_basic_auth_oauth_token_api_authentication module

class SyntheticsBasicAuthOauthTokenApiAuthentication(arg: None)

class SyntheticsBasicAuthOauthTokenApiAuthentication(arg: ModelComposed)

class SyntheticsBasicAuthOauthTokenApiAuthentication(*args, **kwargs)

Bases: ModelSimple

Type of token to use when performing the authentication.

Parameters:

• value (str) – Must be one of [“header”, “body”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_basic_auth_sigv4 module

class SyntheticsBasicAuthSigv4(arg: None)

class SyntheticsBasicAuthSigv4(arg: ModelComposed)

class SyntheticsBasicAuthSigv4(*args, **kwargs)

Bases: ModelNormal

Object to handle SIGV4 authentication when performing the test.

Parameters:

• access_key (str) – Access key for the SIGV4 authentication.

• region (str, optional) – Region for the SIGV4 authentication.

• secret_key (str) – Secret key for the SIGV4 authentication.

• service_name (str, optional) – Service name for the SIGV4 authentication.

• session_token (str, optional) – Session token for the SIGV4 authentication.

• type (SyntheticsBasicAuthSigv4Type) – The type of authentication to use when performing the test.

datadog_api_client.v1.model.synthetics_basic_auth_sigv4_type module

class SyntheticsBasicAuthSigv4Type(arg: None)

class SyntheticsBasicAuthSigv4Type(arg: ModelComposed)

class SyntheticsBasicAuthSigv4Type(*args, **kwargs)

Bases: ModelSimple

The type of authentication to use when performing the test.

Parameters:

• value (str) – If omitted defaults to “sigv4”. Must be one of [“sigv4”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_basic_auth_web module

class SyntheticsBasicAuthWeb(arg: None)

class SyntheticsBasicAuthWeb(arg: ModelComposed)

class SyntheticsBasicAuthWeb(*args, **kwargs)

Bases: ModelNormal

Object to handle basic authentication when performing the test.

Parameters:

• password (str, optional) – Password to use for the basic authentication.

• type (SyntheticsBasicAuthWebType, optional) – The type of basic authentication to use when performing the test.

• username (str, optional) – Username to use for the basic authentication.

datadog_api_client.v1.model.synthetics_basic_auth_web_type module

class SyntheticsBasicAuthWebType(arg: None)

class SyntheticsBasicAuthWebType(arg: ModelComposed)

class SyntheticsBasicAuthWebType(*args, **kwargs)

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

• value (str) – If omitted defaults to “web”. Must be one of [“web”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_batch_details module

class SyntheticsBatchDetails(arg: None)

class SyntheticsBatchDetails(arg: ModelComposed)

class SyntheticsBatchDetails(*args, **kwargs)

Bases: ModelNormal

Details about a batch response.

Parameters:

data (SyntheticsBatchDetailsData, optional) – Wrapper object that contains the details of a batch.

datadog_api_client.v1.model.synthetics_batch_details_data module

class SyntheticsBatchDetailsData(arg: None)

class SyntheticsBatchDetailsData(arg: ModelComposed)

class SyntheticsBatchDetailsData(*args, **kwargs)

Bases: ModelNormal

Wrapper object that contains the details of a batch.

Parameters:

• metadata (SyntheticsCIBatchMetadata, optional) – Metadata for the Synthetic tests run.

• results ([SyntheticsBatchResult], optional) – List of results for the batch.

• status (SyntheticsBatchStatus, optional) – Determines whether the batch has passed, failed, or is in progress.

datadog_api_client.v1.model.synthetics_batch_result module

class SyntheticsBatchResult(arg: None)

class SyntheticsBatchResult(arg: ModelComposed)

class SyntheticsBatchResult(*args, **kwargs)

Bases: ModelNormal

Object with the results of a Synthetic batch.

Parameters:

• device (str, optional) – The device ID.

• duration (float, optional) – Total duration in millisecond of the test.

• execution_rule (SyntheticsTestExecutionRule, optional) – Execution rule for a Synthetic test.

• location (str, optional) – Name of the location.

• result_id (str, optional) – The ID of the result to get.

• retries (float, optional) – Number of times this result has been retried.

• status (SyntheticsBatchStatus, optional) – Determines whether the batch has passed, failed, or is in progress.

• test_name (str, optional) – Name of the test.

• test_public_id (str, optional) – The public ID of the Synthetic test.

• test_type (SyntheticsTestDetailsType, optional) – Type of the Synthetic test, either api or browser.

datadog_api_client.v1.model.synthetics_batch_status module

class SyntheticsBatchStatus(arg: None)

class SyntheticsBatchStatus(arg: ModelComposed)

class SyntheticsBatchStatus(*args, **kwargs)

Bases: ModelSimple

Determines whether the batch has passed, failed, or is in progress.

Parameters:

• value (str) – Must be one of [“passed”, “skipped”, “failed”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_browser_error module

class SyntheticsBrowserError(arg: None)

class SyntheticsBrowserError(arg: ModelComposed)

class SyntheticsBrowserError(*args, **kwargs)

Bases: ModelNormal

Error response object for a browser test.

Parameters:

• description (str) – Description of the error.

• name (str) – Name of the error.

• status (int, optional) – Status Code of the error.

• type (SyntheticsBrowserErrorType) – Error type returned by a browser test.

datadog_api_client.v1.model.synthetics_browser_error_type module

class SyntheticsBrowserErrorType(arg: None)

class SyntheticsBrowserErrorType(arg: ModelComposed)

class SyntheticsBrowserErrorType(*args, **kwargs)

Bases: ModelSimple

Error type returned by a browser test.

Parameters:

• value (str) – Must be one of [“network”, “js”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_browser_test module

class SyntheticsBrowserTest(arg: None)

class SyntheticsBrowserTest(arg: ModelComposed)

class SyntheticsBrowserTest(*args, **kwargs)

Bases: ModelNormal

Object containing details about a Synthetic browser test.

Parameters:

• config (SyntheticsBrowserTestConfig) – Configuration object for a Synthetic browser test.

• locations ([str]) – Array of locations used to run the test.

• message (str) – Notification message associated with the test. Message can either be text or an empty string.

• monitor_id (int, optional) – The associated monitor ID.

• name (str) – Name of the test.

• options (SyntheticsTestOptions) – Object describing the extra options for a Synthetic test.

• public_id (str, optional) – The public ID of the test.

• status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.

• steps ([SyntheticsStep], optional) – Array of steps for the test.

• tags ([str], optional) – Array of tags attached to the test.

• type (SyntheticsBrowserTestType) – Type of the Synthetic test, browser.

datadog_api_client.v1.model.synthetics_browser_test_config module

class SyntheticsBrowserTestConfig(arg: None)

class SyntheticsBrowserTestConfig(arg: ModelComposed)

class SyntheticsBrowserTestConfig(*args, **kwargs)

Bases: ModelNormal

Configuration object for a Synthetic browser test.

Parameters:

• assertions ([SyntheticsAssertion]) – Array of assertions used for the test.

• config_variables ([SyntheticsConfigVariable], optional) – Array of variables used for the test.

• request (SyntheticsTestRequest) – Object describing the Synthetic test request.

• set_cookie (str, optional) – Cookies to be used for the request, using the Set-Cookie syntax.

• variables ([SyntheticsBrowserVariable], optional) – Array of variables used for the test steps.

datadog_api_client.v1.model.synthetics_browser_test_failure_code module

class SyntheticsBrowserTestFailureCode(arg: None)

class SyntheticsBrowserTestFailureCode(arg: ModelComposed)

class SyntheticsBrowserTestFailureCode(*args, **kwargs)

Bases: ModelSimple

Error code that can be returned by a Synthetic test.

Parameters:

• value (str) – Must be one of [“API_REQUEST_FAILURE”, “ASSERTION_FAILURE”, “DOWNLOAD_FILE_TOO_LARGE”, “ELEMENT_NOT_INTERACTABLE”, “EMAIL_VARIABLE_NOT_DEFINED”, “EVALUATE_JAVASCRIPT”, “EVALUATE_JAVASCRIPT_CONTEXT”, “EXTRACT_VARIABLE”, “FORBIDDEN_URL”, “FRAME_DETACHED”, “INCONSISTENCIES”, “INTERNAL_ERROR”, “INVALID_TYPE_TEXT_DELAY”, “INVALID_URL”, “INVALID_VARIABLE_PATTERN”, “INVISIBLE_ELEMENT”, “LOCATE_ELEMENT”, “NAVIGATE_TO_LINK”, “OPEN_URL”, “PRESS_KEY”, “SERVER_CERTIFICATE”, “SELECT_OPTION”, “STEP_TIMEOUT”, “SUB_TEST_NOT_PASSED”, “TEST_TIMEOUT”, “TOO_MANY_HTTP_REQUESTS”, “UNAVAILABLE_BROWSER”, “UNKNOWN”, “UNSUPPORTED_AUTH_SCHEMA”, “UPLOAD_FILES_ELEMENT_TYPE”, “UPLOAD_FILES_DIALOG”, “UPLOAD_FILES_DYNAMIC_ELEMENT”, “UPLOAD_FILES_NAME”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_browser_test_result_data module

class SyntheticsBrowserTestResultData(arg: None)

class SyntheticsBrowserTestResultData(arg: ModelComposed)

class SyntheticsBrowserTestResultData(*args, **kwargs)

Bases: ModelNormal

Object containing results for your Synthetic browser test.

Parameters:

• browser_type (str, optional) – Type of browser device used for the browser test.

• browser_version (str, optional) – Browser version used for the browser test.

• device (SyntheticsDevice, optional) – Object describing the device used to perform the Synthetic test.

• duration (float, optional) – Global duration in second of the browser test.

• error (str, optional) – Error returned for the browser test.

• failure (SyntheticsBrowserTestResultFailure, optional) – The browser test failure details.

• passed (bool, optional) – Whether or not the browser test was conducted.

• received_email_count (int, optional) – The amount of email received during the browser test.

• start_url (str, optional) – Starting URL for the browser test.

• step_details ([SyntheticsStepDetail], optional) – Array containing the different browser test steps.

• thumbnails_bucket_key (bool, optional) – Whether or not a thumbnail is associated with the browser test.

• time_to_interactive (float, optional) – Time in second to wait before the browser test starts after reaching the start URL.

datadog_api_client.v1.model.synthetics_browser_test_result_failure module

class SyntheticsBrowserTestResultFailure(arg: None)

class SyntheticsBrowserTestResultFailure(arg: ModelComposed)

class SyntheticsBrowserTestResultFailure(*args, **kwargs)

Bases: ModelNormal

The browser test failure details.

Parameters:

• code (SyntheticsBrowserTestFailureCode, optional) – Error code that can be returned by a Synthetic test.

• message (str, optional) – The browser test error message.

datadog_api_client.v1.model.synthetics_browser_test_result_full module

class SyntheticsBrowserTestResultFull(arg: None)

class SyntheticsBrowserTestResultFull(arg: ModelComposed)

class SyntheticsBrowserTestResultFull(*args, **kwargs)

Bases: ModelNormal

Object returned describing a browser test result.

Parameters:

• check (SyntheticsBrowserTestResultFullCheck, optional) – Object describing the browser test configuration.

• check_time (float, optional) – When the browser test was conducted.

• check_version (int, optional) – Version of the browser test used.

• probe_dc (str, optional) – Location from which the browser test was performed.

• result (SyntheticsBrowserTestResultData, optional) – Object containing results for your Synthetic browser test.

• result_id (str, optional) – ID of the browser test result.

• status (SyntheticsTestMonitorStatus, optional) –

  The status of your Synthetic monitor.

  • O for not triggered

  • 1 for triggered

  • 2 for no data

datadog_api_client.v1.model.synthetics_browser_test_result_full_check module

class SyntheticsBrowserTestResultFullCheck(arg: None)

class SyntheticsBrowserTestResultFullCheck(arg: ModelComposed)

class SyntheticsBrowserTestResultFullCheck(*args, **kwargs)

Bases: ModelNormal

Object describing the browser test configuration.

Parameters:

config (SyntheticsTestConfig) – Configuration object for a Synthetic test.

datadog_api_client.v1.model.synthetics_browser_test_result_short module

class SyntheticsBrowserTestResultShort(arg: None)

class SyntheticsBrowserTestResultShort(arg: ModelComposed)

class SyntheticsBrowserTestResultShort(*args, **kwargs)

Bases: ModelNormal

Object with the results of a single Synthetic browser test.

Parameters:

• check_time (float, optional) – Last time the browser test was performed.

• probe_dc (str, optional) – Location from which the Browser test was performed.

• result (SyntheticsBrowserTestResultShortResult, optional) – Object with the result of the last browser test run.

• result_id (str, optional) – ID of the browser test result.

• status (SyntheticsTestMonitorStatus, optional) –

  The status of your Synthetic monitor.

  • O for not triggered

  • 1 for triggered

  • 2 for no data

datadog_api_client.v1.model.synthetics_browser_test_result_short_result module

class SyntheticsBrowserTestResultShortResult(arg: None)

class SyntheticsBrowserTestResultShortResult(arg: ModelComposed)

class SyntheticsBrowserTestResultShortResult(*args, **kwargs)

Bases: ModelNormal

Object with the result of the last browser test run.

Parameters:

• device (SyntheticsDevice, optional) – Object describing the device used to perform the Synthetic test.

• duration (float, optional) – Length in milliseconds of the browser test run.

• error_count (int, optional) – Amount of errors collected for a single browser test run.

• step_count_completed (int, optional) – Amount of browser test steps completed before failing.

• step_count_total (int, optional) – Total amount of browser test steps.

datadog_api_client.v1.model.synthetics_browser_test_rum_settings module

class SyntheticsBrowserTestRumSettings(arg: None)

class SyntheticsBrowserTestRumSettings(arg: ModelComposed)

class SyntheticsBrowserTestRumSettings(*args, **kwargs)

Bases: ModelNormal

The RUM data collection settings for the Synthetic browser test. Note: There are 3 ways to format RUM settings:

{ isEnabled: false } RUM data is not collected.

{ isEnabled: true } RUM data is collected from the Synthetic test’s default application.

{ isEnabled: true, applicationId: "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx", clientTokenId: 12345 } RUM data is collected using the specified application.

Parameters:

• application_id (str, optional) – RUM application ID used to collect RUM data for the browser test.

• client_token_id (int, optional) – RUM application API key ID used to collect RUM data for the browser test.

• is_enabled (bool) – Determines whether RUM data is collected during test runs.

datadog_api_client.v1.model.synthetics_browser_test_type module

class SyntheticsBrowserTestType(arg: None)

class SyntheticsBrowserTestType(arg: ModelComposed)

class SyntheticsBrowserTestType(*args, **kwargs)

Bases: ModelSimple

Type of the Synthetic test, browser.

Parameters:

• value (str) – If omitted defaults to “browser”. Must be one of [“browser”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_browser_variable module

class SyntheticsBrowserVariable(arg: None)

class SyntheticsBrowserVariable(arg: ModelComposed)

class SyntheticsBrowserVariable(*args, **kwargs)

Bases: ModelNormal

Object defining a variable that can be used in your browser test. See the Recording Steps documentation.

Parameters:

• example (str, optional) – Example for the variable.

• id (str, optional) – ID for the variable. Global variables require an ID.

• name (str) – Name of the variable.

• pattern (str, optional) – Pattern of the variable.

• secure (bool, optional) – Determines whether or not the browser test variable is obfuscated. Can only be used with browser variables of type text.

• type (SyntheticsBrowserVariableType) – Type of browser test variable.

datadog_api_client.v1.model.synthetics_browser_variable_type module

class SyntheticsBrowserVariableType(arg: None)

class SyntheticsBrowserVariableType(arg: ModelComposed)

class SyntheticsBrowserVariableType(*args, **kwargs)

Bases: ModelSimple

Type of browser test variable.

Parameters:

• value (str) – Must be one of [“element”, “email”, “global”, “text”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_check_type module

class SyntheticsCheckType(arg: None)

class SyntheticsCheckType(arg: ModelComposed)

class SyntheticsCheckType(*args, **kwargs)

Bases: ModelSimple

Type of assertion to apply in an API test.

Parameters:

• value (str) – Must be one of [“equals”, “notEquals”, “contains”, “notContains”, “startsWith”, “notStartsWith”, “greater”, “lower”, “greaterEquals”, “lowerEquals”, “matchRegex”, “between”, “isEmpty”, “notIsEmpty”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_ci_batch_metadata module

class SyntheticsCIBatchMetadata(arg: None)

class SyntheticsCIBatchMetadata(arg: ModelComposed)

class SyntheticsCIBatchMetadata(*args, **kwargs)

Bases: ModelNormal

Metadata for the Synthetic tests run.

Parameters:

• ci (SyntheticsCIBatchMetadataCI, optional) – Description of the CI provider.

• git (SyntheticsCIBatchMetadataGit, optional) – Git information.

datadog_api_client.v1.model.synthetics_ci_batch_metadata_ci module

class SyntheticsCIBatchMetadataCI(arg: None)

class SyntheticsCIBatchMetadataCI(arg: ModelComposed)

class SyntheticsCIBatchMetadataCI(*args, **kwargs)

Bases: ModelNormal

Description of the CI provider.

Parameters:

• pipeline (SyntheticsCIBatchMetadataPipeline, optional) – Description of the CI pipeline.

• provider (SyntheticsCIBatchMetadataProvider, optional) – Description of the CI provider.

datadog_api_client.v1.model.synthetics_ci_batch_metadata_git module

class SyntheticsCIBatchMetadataGit(arg: None)

class SyntheticsCIBatchMetadataGit(arg: ModelComposed)

class SyntheticsCIBatchMetadataGit(*args, **kwargs)

Bases: ModelNormal

Git information.

Parameters:

• branch (str, optional) – Branch name.

• commit_sha (str, optional) – The commit SHA.

datadog_api_client.v1.model.synthetics_ci_batch_metadata_pipeline module

class SyntheticsCIBatchMetadataPipeline(arg: None)

class SyntheticsCIBatchMetadataPipeline(arg: ModelComposed)

class SyntheticsCIBatchMetadataPipeline(*args, **kwargs)

Bases: ModelNormal

Description of the CI pipeline.

Parameters:

url (str, optional) – URL of the pipeline.

datadog_api_client.v1.model.synthetics_ci_batch_metadata_provider module

class SyntheticsCIBatchMetadataProvider(arg: None)

class SyntheticsCIBatchMetadataProvider(arg: ModelComposed)

class SyntheticsCIBatchMetadataProvider(*args, **kwargs)

Bases: ModelNormal

Description of the CI provider.

Parameters:

name (str, optional) – Name of the CI provider.

datadog_api_client.v1.model.synthetics_ci_test module

class SyntheticsCITest(arg: None)

class SyntheticsCITest(arg: ModelComposed)

class SyntheticsCITest(*args, **kwargs)

Bases: ModelNormal

Configuration for Continuous Testing.

Parameters:

• allow_insecure_certificates (bool, optional) – Disable certificate checks in API tests.

• basic_auth (SyntheticsBasicAuth, optional) – Object to handle basic authentication when performing the test.

• body (str, optional) – Body to include in the test.

• body_type (str, optional) – Type of the data sent in a Synthetic API test.

• cookies (str, optional) – Cookies for the request.

• device_ids ([str], optional) – For browser test, array with the different device IDs used to run the test.

• follow_redirects (bool, optional) – For API HTTP test, whether or not the test should follow redirects.

• headers (SyntheticsTestHeaders, optional) – Headers to include when performing the test.

• locations ([str], optional) – Array of locations used to run the test.

• metadata (SyntheticsCIBatchMetadata, optional) – Metadata for the Synthetic tests run.

• public_id (str) – The public ID of the Synthetic test to trigger.

• retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.

• start_url (str, optional) – Starting URL for the browser test.

• variables ({str: (str,)}, optional) – Variables to replace in the test.

• version (int, optional) – The version number of the Synthetic test version to trigger.

datadog_api_client.v1.model.synthetics_ci_test_body module

class SyntheticsCITestBody(arg: None)

class SyntheticsCITestBody(arg: ModelComposed)

class SyntheticsCITestBody(*args, **kwargs)

Bases: ModelNormal

Object describing the synthetics tests to trigger.

Parameters:

tests ([SyntheticsCITest], optional) – List of Synthetic tests with overrides.

datadog_api_client.v1.model.synthetics_config_variable module

class SyntheticsConfigVariable(arg: None)

class SyntheticsConfigVariable(arg: ModelComposed)

class SyntheticsConfigVariable(*args, **kwargs)

Bases: ModelNormal

Object defining a variable that can be used in your test configuration.

Parameters:

• example (str, optional) – Example for the variable.

• id (str, optional) – ID of the variable for global variables.

• name (str) – Name of the variable.

• pattern (str, optional) – Pattern of the variable.

• secure (bool, optional) – Whether the value of this variable will be obfuscated in test results. Only for config variables of type text.

• type (SyntheticsConfigVariableType) – Type of the configuration variable.

datadog_api_client.v1.model.synthetics_config_variable_type module

class SyntheticsConfigVariableType(arg: None)

class SyntheticsConfigVariableType(arg: ModelComposed)

class SyntheticsConfigVariableType(*args, **kwargs)

Bases: ModelSimple

Type of the configuration variable.

Parameters:

• value (str) – Must be one of [“global”, “text”, “email”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_core_web_vitals module

class SyntheticsCoreWebVitals(arg: None)

class SyntheticsCoreWebVitals(arg: ModelComposed)

class SyntheticsCoreWebVitals(*args, **kwargs)

Bases: ModelNormal

Core Web Vitals attached to a browser test step.

Parameters:

• _cls (float, optional) – Cumulative Layout Shift.

• lcp (float, optional) – Largest Contentful Paint in milliseconds.

• url (str, optional) – URL attached to the metrics.

datadog_api_client.v1.model.synthetics_delete_tests_payload module

class SyntheticsDeleteTestsPayload(arg: None)

class SyntheticsDeleteTestsPayload(arg: ModelComposed)

class SyntheticsDeleteTestsPayload(*args, **kwargs)

Bases: ModelNormal

A JSON list of the ID or IDs of the Synthetic tests that you want to delete.

Parameters:

• force_delete_dependencies (bool, optional) – Delete the Synthetic test even if it’s referenced by other resources (for example, SLOs and composite monitors).

• public_ids ([str], optional) – An array of Synthetic test IDs you want to delete.

datadog_api_client.v1.model.synthetics_delete_tests_response module

class SyntheticsDeleteTestsResponse(arg: None)

class SyntheticsDeleteTestsResponse(arg: ModelComposed)

class SyntheticsDeleteTestsResponse(*args, **kwargs)

Bases: ModelNormal

Response object for deleting Synthetic tests.

Parameters:

deleted_tests ([SyntheticsDeletedTest], optional) – Array of objects containing a deleted Synthetic test ID with the associated deletion timestamp.

datadog_api_client.v1.model.synthetics_deleted_test module

class SyntheticsDeletedTest(arg: None)

class SyntheticsDeletedTest(arg: ModelComposed)

class SyntheticsDeletedTest(*args, **kwargs)

Bases: ModelNormal

Object containing a deleted Synthetic test ID with the associated deletion timestamp.

Parameters:

• deleted_at (datetime, optional) – Deletion timestamp of the Synthetic test ID.

• public_id (str, optional) – The Synthetic test ID deleted.

datadog_api_client.v1.model.synthetics_device module

class SyntheticsDevice(arg: None)

class SyntheticsDevice(arg: ModelComposed)

class SyntheticsDevice(*args, **kwargs)

Bases: ModelNormal

Object describing the device used to perform the Synthetic test.

Parameters:

• height (int) – Screen height of the device.

• id (str) – The device ID.

• is_mobile (bool, optional) – Whether or not the device is a mobile.

• name (str) – The device name.

• width (int) – Screen width of the device.

datadog_api_client.v1.model.synthetics_fetch_uptimes_payload module

class SyntheticsFetchUptimesPayload(arg: None)

class SyntheticsFetchUptimesPayload(arg: ModelComposed)

class SyntheticsFetchUptimesPayload(*args, **kwargs)

Bases: ModelNormal

Object containing IDs of Synthetic tests and a timeframe.

Parameters:

• from_ts (int) – Timestamp in seconds (Unix epoch) for the start of uptime.

• public_ids ([str]) – An array of Synthetic test IDs you want uptimes for.

• to_ts (int) – Timestamp in seconds (Unix epoch) for the end of uptime.

datadog_api_client.v1.model.synthetics_get_api_test_latest_results_response module

class SyntheticsGetAPITestLatestResultsResponse(arg: None)

class SyntheticsGetAPITestLatestResultsResponse(arg: ModelComposed)

class SyntheticsGetAPITestLatestResultsResponse(*args, **kwargs)

Bases: ModelNormal

Object with the latest Synthetic API test run.

Parameters:

• last_timestamp_fetched (int, optional) – Timestamp of the latest API test run.

• results ([SyntheticsAPITestResultShort], optional) – Result of the latest API test run.

datadog_api_client.v1.model.synthetics_get_browser_test_latest_results_response module

class SyntheticsGetBrowserTestLatestResultsResponse(arg: None)

class SyntheticsGetBrowserTestLatestResultsResponse(arg: ModelComposed)

class SyntheticsGetBrowserTestLatestResultsResponse(*args, **kwargs)

Bases: ModelNormal

Object with the latest Synthetic browser test run.

Parameters:

• last_timestamp_fetched (int, optional) – Timestamp of the latest browser test run.

• results ([SyntheticsBrowserTestResultShort], optional) – Result of the latest browser test run.

datadog_api_client.v1.model.synthetics_global_variable module

class SyntheticsGlobalVariable(arg: None)

class SyntheticsGlobalVariable(arg: ModelComposed)

class SyntheticsGlobalVariable(*args, **kwargs)

Bases: ModelNormal

Synthetic global variable.

Parameters:

• attributes (SyntheticsGlobalVariableAttributes, optional) – Attributes of the global variable.

• description (str) – Description of the global variable.

• id (str, optional) – Unique identifier of the global variable.

• is_fido (bool, optional) – Determines if the global variable is a FIDO variable.

• is_totp (bool, optional) – Determines if the global variable is a TOTP/MFA variable.

• name (str) – Name of the global variable. Unique across Synthetic global variables.

• parse_test_options (SyntheticsGlobalVariableParseTestOptions, optional) – Parser options to use for retrieving a Synthetic global variable from a Synthetic test. Used in conjunction with parse_test_public_id.

• parse_test_public_id (str, optional) – A Synthetic test ID to use as a test to generate the variable value.

• tags ([str]) – Tags of the global variable.

• value (SyntheticsGlobalVariableValue) – Value of the global variable.

datadog_api_client.v1.model.synthetics_global_variable_attributes module

class SyntheticsGlobalVariableAttributes(arg: None)

class SyntheticsGlobalVariableAttributes(arg: ModelComposed)

class SyntheticsGlobalVariableAttributes(*args, **kwargs)

Bases: ModelNormal

Attributes of the global variable.

Parameters:

restricted_roles (SyntheticsRestrictedRoles, optional) – A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

datadog_api_client.v1.model.synthetics_global_variable_options module

class SyntheticsGlobalVariableOptions(arg: None)

class SyntheticsGlobalVariableOptions(arg: ModelComposed)

class SyntheticsGlobalVariableOptions(*args, **kwargs)

Bases: ModelNormal

Options for the Global Variable for MFA.

Parameters:

totp_parameters (SyntheticsGlobalVariableTOTPParameters, optional) – Parameters for the TOTP/MFA variable

datadog_api_client.v1.model.synthetics_global_variable_parse_test_options module

class SyntheticsGlobalVariableParseTestOptions(arg: None)

class SyntheticsGlobalVariableParseTestOptions(arg: ModelComposed)

class SyntheticsGlobalVariableParseTestOptions(*args, **kwargs)

Bases: ModelNormal

Parser options to use for retrieving a Synthetic global variable from a Synthetic test. Used in conjunction with parse_test_public_id.

Parameters:

• field (str, optional) – When type is http_header , name of the header to use to extract the value.

• local_variable_name (str, optional) – When type is local_variable , name of the local variable to use to extract the value.

• parser (SyntheticsVariableParser, optional) – Details of the parser to use for the global variable.

• type (SyntheticsGlobalVariableParseTestOptionsType) – Type of value to extract from a test for a Synthetic global variable.

datadog_api_client.v1.model.synthetics_global_variable_parse_test_options_type module

class SyntheticsGlobalVariableParseTestOptionsType(arg: None)

class SyntheticsGlobalVariableParseTestOptionsType(arg: ModelComposed)

class SyntheticsGlobalVariableParseTestOptionsType(*args, **kwargs)

Bases: ModelSimple

Type of value to extract from a test for a Synthetic global variable.

Parameters:

• value (str) – Must be one of [“http_body”, “http_header”, “http_status_code”, “local_variable”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_global_variable_parser_type module

class SyntheticsGlobalVariableParserType(arg: None)

class SyntheticsGlobalVariableParserType(arg: ModelComposed)

class SyntheticsGlobalVariableParserType(*args, **kwargs)

Bases: ModelSimple

Type of parser for a Synthetic global variable from a synthetics test.

Parameters:

• value (str) – Must be one of [“raw”, “json_path”, “regex”, “x_path”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_global_variable_request module

class SyntheticsGlobalVariableRequest(arg: None)

class SyntheticsGlobalVariableRequest(arg: ModelComposed)

class SyntheticsGlobalVariableRequest(*args, **kwargs)

Bases: ModelNormal

Details of the global variable to create.

Parameters:

• attributes (SyntheticsGlobalVariableAttributes, optional) – Attributes of the global variable.

• description (str) – Description of the global variable.

• id (str, optional) – Unique identifier of the global variable.

• is_fido (bool, optional) – Determines if the global variable is a FIDO variable.

• is_totp (bool, optional) – Determines if the global variable is a TOTP/MFA variable.

• name (str) – Name of the global variable. Unique across Synthetic global variables.

• parse_test_options (SyntheticsGlobalVariableParseTestOptions, optional) – Parser options to use for retrieving a Synthetic global variable from a Synthetic test. Used in conjunction with parse_test_public_id.

• parse_test_public_id (str, optional) – A Synthetic test ID to use as a test to generate the variable value.

• tags ([str]) – Tags of the global variable.

• value (SyntheticsGlobalVariableValue, optional) – Value of the global variable.

datadog_api_client.v1.model.synthetics_global_variable_totp_parameters module

class SyntheticsGlobalVariableTOTPParameters(arg: None)

class SyntheticsGlobalVariableTOTPParameters(arg: ModelComposed)

class SyntheticsGlobalVariableTOTPParameters(*args, **kwargs)

Bases: ModelNormal

Parameters for the TOTP/MFA variable

Parameters:

• digits (int, optional) – Number of digits for the OTP code.

• refresh_interval (int, optional) – Interval for which to refresh the token (in seconds).

datadog_api_client.v1.model.synthetics_global_variable_value module

class SyntheticsGlobalVariableValue(arg: None)

class SyntheticsGlobalVariableValue(arg: ModelComposed)

class SyntheticsGlobalVariableValue(*args, **kwargs)

Bases: ModelNormal

Value of the global variable.

Parameters:

• options (SyntheticsGlobalVariableOptions, optional) – Options for the Global Variable for MFA.

• secure (bool, optional) – Determines if the value of the variable is hidden.

• value (str, optional) – Value of the global variable. When reading a global variable, the value will not be present if the variable is hidden with the secure property.

datadog_api_client.v1.model.synthetics_list_global_variables_response module

class SyntheticsListGlobalVariablesResponse(arg: None)

class SyntheticsListGlobalVariablesResponse(arg: ModelComposed)

class SyntheticsListGlobalVariablesResponse(*args, **kwargs)

Bases: ModelNormal

Object containing an array of Synthetic global variables.

Parameters:

variables ([SyntheticsGlobalVariable], optional) – Array of Synthetic global variables.

datadog_api_client.v1.model.synthetics_list_tests_response module

class SyntheticsListTestsResponse(arg: None)

class SyntheticsListTestsResponse(arg: ModelComposed)

class SyntheticsListTestsResponse(*args, **kwargs)

Bases: ModelNormal

Object containing an array of Synthetic tests configuration.

Parameters:

tests ([SyntheticsTestDetails], optional) – Array of Synthetic tests configuration.

datadog_api_client.v1.model.synthetics_local_variable_parsing_options_type module

class SyntheticsLocalVariableParsingOptionsType(arg: None)

class SyntheticsLocalVariableParsingOptionsType(arg: ModelComposed)

class SyntheticsLocalVariableParsingOptionsType(*args, **kwargs)

Bases: ModelSimple

Property of the Synthetic Test Response to extract into a local variable.

Parameters:

• value (str) – Must be one of [“grpc_message”, “grpc_metadata”, “http_body”, “http_header”, “http_status_code”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_location module

class SyntheticsLocation(arg: None)

class SyntheticsLocation(arg: ModelComposed)

class SyntheticsLocation(*args, **kwargs)

Bases: ModelNormal

Synthetic location that can be used when creating or editing a test.

Parameters:

• id (str, optional) – Unique identifier of the location.

• name (str, optional) – Name of the location.

datadog_api_client.v1.model.synthetics_locations module

class SyntheticsLocations(arg: None)

class SyntheticsLocations(arg: ModelComposed)

class SyntheticsLocations(*args, **kwargs)

Bases: ModelNormal

List of Synthetic locations.

Parameters:

locations ([SyntheticsLocation], optional) – List of Synthetic locations.

datadog_api_client.v1.model.synthetics_mobile_step module

class SyntheticsMobileStep(arg: None)

class SyntheticsMobileStep(arg: ModelComposed)

class SyntheticsMobileStep(*args, **kwargs)

Bases: ModelNormal

The steps used in a Synthetic mobile test.

Parameters:

• allow_failure (bool, optional) – A boolean set to allow this step to fail.

• has_new_step_element (bool, optional) – A boolean set to determine if the step has a new step element.

• is_critical (bool, optional) – A boolean to use in addition to allowFailure to determine if the test should be marked as failed when the step fails.

• name (str) – The name of the step.

• no_screenshot (bool, optional) – A boolean set to not take a screenshot for the step.

• params (SyntheticsMobileStepParams) – The parameters of a mobile step.

• public_id (str, optional) – The public ID of the step.

• timeout (int, optional) – The time before declaring a step failed.

• type (SyntheticsMobileStepType) – Step type used in your mobile Synthetic test.

datadog_api_client.v1.model.synthetics_mobile_step_params module

class SyntheticsMobileStepParams(arg: None)

class SyntheticsMobileStepParams(arg: ModelComposed)

class SyntheticsMobileStepParams(*args, **kwargs)

Bases: ModelNormal

The parameters of a mobile step.

Parameters:

• check (SyntheticsCheckType, optional) – Type of assertion to apply in an API test.

• delay (int, optional) – Number of milliseconds to wait between inputs in a typeText step type.

• direction (SyntheticsMobileStepParamsDirection, optional) – The direction of the scroll for a scrollToElement step type.

• element (SyntheticsMobileStepParamsElement, optional) – Information about the element used for a step.

• enabled (bool, optional) – Boolean to change the state of the wifi for a toggleWiFi step type.

• max_scrolls (int, optional) – Maximum number of scrolls to do for a scrollToElement step type.

• positions ([SyntheticsMobileStepParamsPositionsItems], optional) – List of positions for the flick step type. The maximum is 10 flicks per step

• subtest_public_id (str, optional) – Public ID of the test to be played as part of a playSubTest step type.

• value (SyntheticsMobileStepParamsValue, optional) – Values used in the step for in multiple step types.

• variable (SyntheticsMobileStepParamsVariable, optional) – Variable object for extractVariable step type.

• with_enter (bool, optional) – Boolean to indicate if Enter should be pressed at the end of the typeText step type.

• x (float, optional) – Amount to scroll by on the x axis for a scroll step type.

• y (float, optional) – Amount to scroll by on the y axis for a scroll step type.

datadog_api_client.v1.model.synthetics_mobile_step_params_direction module

class SyntheticsMobileStepParamsDirection(arg: None)

class SyntheticsMobileStepParamsDirection(arg: ModelComposed)

class SyntheticsMobileStepParamsDirection(*args, **kwargs)

Bases: ModelSimple

The direction of the scroll for a scrollToElement step type.

Parameters:

• value (str) – Must be one of [“up”, “down”, “left”, “right”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_mobile_step_params_element module

class SyntheticsMobileStepParamsElement(arg: None)

class SyntheticsMobileStepParamsElement(arg: ModelComposed)

class SyntheticsMobileStepParamsElement(*args, **kwargs)

Bases: ModelNormal

Information about the element used for a step.

Parameters:

• context (str, optional) – Context of the element.

• context_type (SyntheticsMobileStepParamsElementContextType, optional) – Type of the context that the element is in.

• element_description (str, optional) – Description of the element.

• multi_locator (dict, optional) – Multi-locator to find the element.

• relative_position (SyntheticsMobileStepParamsElementRelativePosition, optional) – Position of the action relative to the element.

• text_content (str, optional) – Text content of the element.

• user_locator (SyntheticsMobileStepParamsElementUserLocator, optional) – User locator to find the element.

• view_name (str, optional) – Name of the view of the element.

datadog_api_client.v1.model.synthetics_mobile_step_params_element_context_type module

class SyntheticsMobileStepParamsElementContextType(arg: None)

class SyntheticsMobileStepParamsElementContextType(arg: ModelComposed)

class SyntheticsMobileStepParamsElementContextType(*args, **kwargs)

Bases: ModelSimple

Type of the context that the element is in.

Parameters:

• value (str) – Must be one of [“native”, “web”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_mobile_step_params_element_relative_position module

class SyntheticsMobileStepParamsElementRelativePosition(arg: None)

class SyntheticsMobileStepParamsElementRelativePosition(arg: ModelComposed)

class SyntheticsMobileStepParamsElementRelativePosition(*args, **kwargs)

Bases: ModelNormal

Position of the action relative to the element.

Parameters:

• x (float, optional) – The relativePosition on the x axis for the element.

• y (float, optional) – The relativePosition on the y axis for the element.

datadog_api_client.v1.model.synthetics_mobile_step_params_element_user_locator module

class SyntheticsMobileStepParamsElementUserLocator(arg: None)

class SyntheticsMobileStepParamsElementUserLocator(arg: ModelComposed)

class SyntheticsMobileStepParamsElementUserLocator(*args, **kwargs)

Bases: ModelNormal

User locator to find the element.

Parameters:

• fail_test_on_cannot_locate (bool, optional) – Whether if the test should fail if the element cannot be found.

• values ([SyntheticsMobileStepParamsElementUserLocatorValuesItems], optional) – Values of the user locator.

datadog_api_client.v1.model.synthetics_mobile_step_params_element_user_locator_values_items module

class SyntheticsMobileStepParamsElementUserLocatorValuesItems(arg: None)

class SyntheticsMobileStepParamsElementUserLocatorValuesItems(arg: ModelComposed)

class SyntheticsMobileStepParamsElementUserLocatorValuesItems(*args, **kwargs)

Bases: ModelNormal

A single user locator object.

Parameters:

• type (SyntheticsMobileStepParamsElementUserLocatorValuesItemsType, optional) – Type of a user locator.

• value (str, optional) – Value of a user locator.

datadog_api_client.v1.model.synthetics_mobile_step_params_element_user_locator_values_items_type module

class SyntheticsMobileStepParamsElementUserLocatorValuesItemsType(arg: None)

class SyntheticsMobileStepParamsElementUserLocatorValuesItemsType(arg: ModelComposed)

class SyntheticsMobileStepParamsElementUserLocatorValuesItemsType(*args, **kwargs)

Bases: ModelSimple

Type of a user locator.

Parameters:

• value (str) – Must be one of [“accessibility-id”, “id”, “ios-predicate-string”, “ios-class-chain”, “xpath”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_mobile_step_params_positions_items module

class SyntheticsMobileStepParamsPositionsItems(arg: None)

class SyntheticsMobileStepParamsPositionsItems(arg: ModelComposed)

class SyntheticsMobileStepParamsPositionsItems(*args, **kwargs)

Bases: ModelNormal

A description of a single position for a flick step type.

Parameters:

• x (float, optional) – The x position for the flick.

• y (float, optional) – The y position for the flick.

datadog_api_client.v1.model.synthetics_mobile_step_params_value module

class SyntheticsMobileStepParamsValue(arg: None)

class SyntheticsMobileStepParamsValue(arg: ModelComposed)

class SyntheticsMobileStepParamsValue(*args, **kwargs)

Bases: ModelComposed

Values used in the step for in multiple step types.

datadog_api_client.v1.model.synthetics_mobile_step_params_variable module

class SyntheticsMobileStepParamsVariable(arg: None)

class SyntheticsMobileStepParamsVariable(arg: ModelComposed)

class SyntheticsMobileStepParamsVariable(*args, **kwargs)

Bases: ModelNormal

Variable object for extractVariable step type.

Parameters:

• example (str) – An example for the variable.

• name (str) – The variable name.

datadog_api_client.v1.model.synthetics_mobile_step_type module

class SyntheticsMobileStepType(arg: None)

class SyntheticsMobileStepType(arg: ModelComposed)

class SyntheticsMobileStepType(*args, **kwargs)

Bases: ModelSimple

Step type used in your mobile Synthetic test.

Parameters:

• value (str) – Must be one of [“assertElementContent”, “assertScreenContains”, “assertScreenLacks”, “doubleTap”, “extractVariable”, “flick”, “openDeeplink”, “playSubTest”, “pressBack”, “restartApplication”, “rotate”, “scroll”, “scrollToElement”, “tap”, “toggleWiFi”, “typeText”, “wait”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_mobile_test module

class SyntheticsMobileTest(arg: None)

class SyntheticsMobileTest(arg: ModelComposed)

class SyntheticsMobileTest(*args, **kwargs)

Bases: ModelNormal

Object containing details about a Synthetic mobile test.

Parameters:

• config (SyntheticsMobileTestConfig) – Configuration object for a Synthetic mobile test.

• device_ids ([str], optional) – Array with the different device IDs used to run the test.

• message (str) – Notification message associated with the test.

• monitor_id (int, optional) – The associated monitor ID.

• name (str) – Name of the test.

• options (SyntheticsMobileTestOptions) – Object describing the extra options for a Synthetic test.

• public_id (str, optional) – The public ID of the test.

• status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.

• steps ([SyntheticsMobileStep], optional) – Array of steps for the test.

• tags ([str], optional) – Array of tags attached to the test.

• type (SyntheticsMobileTestType) – Type of the Synthetic test, mobile.

datadog_api_client.v1.model.synthetics_mobile_test_config module

class SyntheticsMobileTestConfig(arg: None)

class SyntheticsMobileTestConfig(arg: ModelComposed)

class SyntheticsMobileTestConfig(*args, **kwargs)

Bases: ModelNormal

Configuration object for a Synthetic mobile test.

Parameters:

• initial_application_arguments (SyntheticsMobileTestInitialApplicationArguments, optional) – Initial application arguments for a mobile test.

• variables ([SyntheticsConfigVariable], optional) – Array of variables used for the test steps.

datadog_api_client.v1.model.synthetics_mobile_test_initial_application_arguments module

class SyntheticsMobileTestInitialApplicationArguments(arg: None)

class SyntheticsMobileTestInitialApplicationArguments(arg: ModelComposed)

class SyntheticsMobileTestInitialApplicationArguments(*args, **kwargs)

Bases: ModelNormal

Initial application arguments for a mobile test.

datadog_api_client.v1.model.synthetics_mobile_test_options module

class SyntheticsMobileTestOptions(arg: None)

class SyntheticsMobileTestOptions(arg: ModelComposed)

class SyntheticsMobileTestOptions(*args, **kwargs)

Bases: ModelNormal

Object describing the extra options for a Synthetic test.

Parameters:

• allow_application_crash (bool, optional) – A boolean to set if an application crash would mark the test as failed.

• bindings ([SyntheticsTestRestrictionPolicyBinding], optional) – Array of bindings used for the mobile test.

• ci (SyntheticsTestCiOptions, optional) – CI/CD options for a Synthetic test.

• default_step_timeout (int, optional) – The default timeout for steps in the test (in seconds).

• device_ids ([str]) – For mobile test, array with the different device IDs used to run the test.

• disable_auto_accept_alert (bool, optional) – A boolean to disable auto accepting alerts.

• min_failure_duration (int, optional) – Minimum amount of time in failure required to trigger an alert.

• mobile_application (SyntheticsMobileTestsMobileApplication) – Mobile application for mobile synthetics test.

• monitor_name (str, optional) – The monitor name is used for the alert title as well as for all monitor dashboard widgets and SLOs.

• monitor_options (SyntheticsTestOptionsMonitorOptions, optional) – Object containing the options for a Synthetic test as a monitor (for example, renotification).

• monitor_priority (int, optional) – Integer from 1 (high) to 5 (low) indicating alert severity.

• no_screenshot (bool, optional) – A boolean set to not take a screenshot for the step.

• restricted_roles (SyntheticsRestrictedRoles, optional) – A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

• retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.

• scheduling (SyntheticsTestOptionsScheduling, optional) – Object containing timeframes and timezone used for advanced scheduling.

• tick_every (int) – The frequency at which to run the Synthetic test (in seconds).

• verbosity (int, optional) – The level of verbosity for the mobile test. This field can not be set by a user.

datadog_api_client.v1.model.synthetics_mobile_test_type module

class SyntheticsMobileTestType(arg: None)

class SyntheticsMobileTestType(arg: ModelComposed)

class SyntheticsMobileTestType(*args, **kwargs)

Bases: ModelSimple

Type of the Synthetic test, mobile.

Parameters:

• value (str) – If omitted defaults to “mobile”. Must be one of [“mobile”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_mobile_tests_mobile_application module

class SyntheticsMobileTestsMobileApplication(arg: None)

class SyntheticsMobileTestsMobileApplication(arg: ModelComposed)

class SyntheticsMobileTestsMobileApplication(*args, **kwargs)

Bases: ModelNormal

Mobile application for mobile synthetics test.

Parameters:

• application_id (str) – Application ID of the mobile application.

• reference_id (str) – Reference ID of the mobile application.

• reference_type (SyntheticsMobileTestsMobileApplicationReferenceType) – Reference type for the mobile application for a mobile synthetics test.

datadog_api_client.v1.model.synthetics_mobile_tests_mobile_application_reference_type module

class SyntheticsMobileTestsMobileApplicationReferenceType(arg: None)

class SyntheticsMobileTestsMobileApplicationReferenceType(arg: ModelComposed)

class SyntheticsMobileTestsMobileApplicationReferenceType(*args, **kwargs)

Bases: ModelSimple

Reference type for the mobile application for a mobile synthetics test.

Parameters:

• value (str) – Must be one of [“latest”, “version”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_parsing_options module

class SyntheticsParsingOptions(arg: None)

class SyntheticsParsingOptions(arg: ModelComposed)

class SyntheticsParsingOptions(*args, **kwargs)

Bases: ModelNormal

Parsing options for variables to extract.

Parameters:

• field (str, optional) – When type is http_header or grpc_metadata , name of the header or metadatum to extract.

• name (str, optional) – Name of the variable to extract.

• parser (SyntheticsVariableParser, optional) – Details of the parser to use for the global variable.

• secure (bool, optional) – Determines whether or not the extracted value will be obfuscated.

• type (SyntheticsLocalVariableParsingOptionsType, optional) – Property of the Synthetic Test Response to extract into a local variable.

datadog_api_client.v1.model.synthetics_patch_test_body module

class SyntheticsPatchTestBody(arg: None)

class SyntheticsPatchTestBody(arg: ModelComposed)

class SyntheticsPatchTestBody(*args, **kwargs)

Bases: ModelNormal

Wrapper around an array of JSON Patch operations to perform on the test

Parameters:

data ([SyntheticsPatchTestOperation], optional) –

Array of JSON Patch operations to perform on the test

datadog_api_client.v1.model.synthetics_patch_test_operation module

class SyntheticsPatchTestOperation(arg: None)

class SyntheticsPatchTestOperation(arg: ModelComposed)

class SyntheticsPatchTestOperation(*args, **kwargs)

Bases: ModelNormal

A single JSON Patch operation to perform on the test

Parameters:

• op (SyntheticsPatchTestOperationName, optional) – The operation to perform

• path (str, optional) – The path to the value to modify

• value (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) –

  A value to use in a JSON Patch operation

datadog_api_client.v1.model.synthetics_patch_test_operation_name module

class SyntheticsPatchTestOperationName(arg: None)

class SyntheticsPatchTestOperationName(arg: ModelComposed)

class SyntheticsPatchTestOperationName(*args, **kwargs)

Bases: ModelSimple

The operation to perform

Parameters:

• value (str) – Must be one of [“add”, “remove”, “replace”, “move”, “copy”, “test”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_playing_tab module

class SyntheticsPlayingTab(arg: None)

class SyntheticsPlayingTab(arg: ModelComposed)

class SyntheticsPlayingTab(*args, **kwargs)

Bases: ModelSimple

Navigate between different tabs for your browser test.

Parameters:

• value (int) – Must be one of [-1, 0, 1, 2, 3].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_private_location module

class SyntheticsPrivateLocation(arg: None)

class SyntheticsPrivateLocation(arg: ModelComposed)

class SyntheticsPrivateLocation(*args, **kwargs)

Bases: ModelNormal

Object containing information about the private location to create.

Parameters:

• description (str) – Description of the private location.

• id (str, optional) – Unique identifier of the private location.

• metadata (SyntheticsPrivateLocationMetadata, optional) – Object containing metadata about the private location.

• name (str) – Name of the private location.

• secrets (SyntheticsPrivateLocationSecrets, optional) – Secrets for the private location. Only present in the response when creating the private location.

• tags ([str]) – Array of tags attached to the private location.

datadog_api_client.v1.model.synthetics_private_location_creation_response module

class SyntheticsPrivateLocationCreationResponse(arg: None)

class SyntheticsPrivateLocationCreationResponse(arg: ModelComposed)

class SyntheticsPrivateLocationCreationResponse(*args, **kwargs)

Bases: ModelNormal

Object that contains the new private location, the public key for result encryption, and the configuration skeleton.

Parameters:

• config (dict, optional) – Configuration skeleton for the private location. See installation instructions of the private location on how to use this configuration.

• private_location (SyntheticsPrivateLocation, optional) – Object containing information about the private location to create.

• result_encryption (SyntheticsPrivateLocationCreationResponseResultEncryption, optional) – Public key for the result encryption.

datadog_api_client.v1.model.synthetics_private_location_creation_response_result_encryption module

class SyntheticsPrivateLocationCreationResponseResultEncryption(arg: None)

class SyntheticsPrivateLocationCreationResponseResultEncryption(arg: ModelComposed)

class SyntheticsPrivateLocationCreationResponseResultEncryption(*args, **kwargs)

Bases: ModelNormal

Public key for the result encryption.

Parameters:

• id (str, optional) – Fingerprint for the encryption key.

• key (str, optional) – Public key for result encryption.

datadog_api_client.v1.model.synthetics_private_location_metadata module

class SyntheticsPrivateLocationMetadata(arg: None)

class SyntheticsPrivateLocationMetadata(arg: ModelComposed)

class SyntheticsPrivateLocationMetadata(*args, **kwargs)

Bases: ModelNormal

Object containing metadata about the private location.

Parameters:

restricted_roles (SyntheticsRestrictedRoles, optional) – A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

datadog_api_client.v1.model.synthetics_private_location_secrets module

class SyntheticsPrivateLocationSecrets(arg: None)

class SyntheticsPrivateLocationSecrets(arg: ModelComposed)

class SyntheticsPrivateLocationSecrets(*args, **kwargs)

Bases: ModelNormal

Secrets for the private location. Only present in the response when creating the private location.

Parameters:

• authentication (SyntheticsPrivateLocationSecretsAuthentication, optional) – Authentication part of the secrets.

• config_decryption (SyntheticsPrivateLocationSecretsConfigDecryption, optional) – Private key for the private location.

datadog_api_client.v1.model.synthetics_private_location_secrets_authentication module

class SyntheticsPrivateLocationSecretsAuthentication(arg: None)

class SyntheticsPrivateLocationSecretsAuthentication(arg: ModelComposed)

class SyntheticsPrivateLocationSecretsAuthentication(*args, **kwargs)

Bases: ModelNormal

Authentication part of the secrets.

Parameters:

• id (str, optional) – Access key for the private location.

• key (str, optional) – Secret access key for the private location.

datadog_api_client.v1.model.synthetics_private_location_secrets_config_decryption module

class SyntheticsPrivateLocationSecretsConfigDecryption(arg: None)

class SyntheticsPrivateLocationSecretsConfigDecryption(arg: ModelComposed)

class SyntheticsPrivateLocationSecretsConfigDecryption(*args, **kwargs)

Bases: ModelNormal

Private key for the private location.

Parameters:

key (str, optional) – Private key for the private location.

datadog_api_client.v1.model.synthetics_restricted_roles module

class SyntheticsRestrictedRoles(arg: None)

class SyntheticsRestrictedRoles(arg: ModelComposed)

class SyntheticsRestrictedRoles(*args, **kwargs)

Bases: ModelSimple

A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_ssl_certificate module

class SyntheticsSSLCertificate(arg: None)

class SyntheticsSSLCertificate(arg: ModelComposed)

class SyntheticsSSLCertificate(*args, **kwargs)

Bases: ModelNormal

Object describing the SSL certificate used for a Synthetic test.

Parameters:

• cipher (str, optional) – Cipher used for the connection.

• exponent (float, optional) – Exponent associated to the certificate.

• ext_key_usage ([str], optional) – Array of extensions and details used for the certificate.

• fingerprint (str, optional) – MD5 digest of the DER-encoded Certificate information.

• fingerprint256 (str, optional) – SHA-1 digest of the DER-encoded Certificate information.

• issuer (SyntheticsSSLCertificateIssuer, optional) – Object describing the issuer of a SSL certificate.

• modulus (str, optional) – Modulus associated to the SSL certificate private key.

• protocol (str, optional) – TLS protocol used for the test.

• serial_number (str, optional) – Serial Number assigned by Symantec to the SSL certificate.

• subject (SyntheticsSSLCertificateSubject, optional) – Object describing the SSL certificate used for the test.

• valid_from (datetime, optional) – Date from which the SSL certificate is valid.

• valid_to (datetime, optional) – Date until which the SSL certificate is valid.

datadog_api_client.v1.model.synthetics_ssl_certificate_issuer module

class SyntheticsSSLCertificateIssuer(arg: None)

class SyntheticsSSLCertificateIssuer(arg: ModelComposed)

class SyntheticsSSLCertificateIssuer(*args, **kwargs)

Bases: ModelNormal

Object describing the issuer of a SSL certificate.

Parameters:

• c (str, optional) – Country Name that issued the certificate.

• cn (str, optional) – Common Name that issued certificate.

• l (str, optional) – Locality that issued the certificate.

• o (str, optional) – Organization that issued the certificate.

• ou (str, optional) – Organizational Unit that issued the certificate.

• st (str, optional) – State Or Province Name that issued the certificate.

datadog_api_client.v1.model.synthetics_ssl_certificate_subject module

class SyntheticsSSLCertificateSubject(arg: None)

class SyntheticsSSLCertificateSubject(arg: ModelComposed)

class SyntheticsSSLCertificateSubject(*args, **kwargs)

Bases: ModelNormal

Object describing the SSL certificate used for the test.

Parameters:

• c (str, optional) – Country Name associated with the certificate.

• cn (str, optional) – Common Name that associated with the certificate.

• l (str, optional) – Locality associated with the certificate.

• o (str, optional) – Organization associated with the certificate.

• ou (str, optional) – Organizational Unit associated with the certificate.

• st (str, optional) – State Or Province Name associated with the certificate.

• alt_name (str, optional) – Subject Alternative Name associated with the certificate.

datadog_api_client.v1.model.synthetics_step module

class SyntheticsStep(arg: None)

class SyntheticsStep(arg: ModelComposed)

class SyntheticsStep(*args, **kwargs)

Bases: ModelNormal

The steps used in a Synthetic browser test.

Parameters:

• allow_failure (bool, optional) – A boolean set to allow this step to fail.

• always_execute (bool, optional) – A boolean set to always execute this step even if the previous step failed or was skipped.

• exit_if_succeed (bool, optional) – A boolean set to exit the test if the step succeeds.

• is_critical (bool, optional) – A boolean to use in addition to allowFailure to determine if the test should be marked as failed when the step fails.

• name (str, optional) – The name of the step.

• no_screenshot (bool, optional) – A boolean set to skip taking a screenshot for the step.

• params (dict, optional) – The parameters of the step.

• public_id (str, optional) – The public ID of the step.

• timeout (int, optional) – The time before declaring a step failed.

• type (SyntheticsStepType, optional) – Step type used in your Synthetic test.

datadog_api_client.v1.model.synthetics_step_detail module

class SyntheticsStepDetail(arg: None)

class SyntheticsStepDetail(arg: ModelComposed)

class SyntheticsStepDetail(*args, **kwargs)

Bases: ModelNormal

Object describing a step for a Synthetic test.

Parameters:

• allow_failure (bool, optional) – Whether or not the step was allowed to fail.

• browser_errors ([SyntheticsBrowserError], optional) – Array of errors collected for a browser test.

• check_type (SyntheticsCheckType, optional) – Type of assertion to apply in an API test.

• description (str, optional) – Description of the test.

• duration (float, optional) – Total duration in millisecond of the test.

• error (str, optional) – Error returned by the test.

• failure (SyntheticsBrowserTestResultFailure, optional) – The browser test failure details.

• playing_tab (SyntheticsPlayingTab, optional) – Navigate between different tabs for your browser test.

• screenshot_bucket_key (bool, optional) – Whether or not screenshots where collected by the test.

• skipped (bool, optional) – Whether or not to skip this step.

• snapshot_bucket_key (bool, optional) – Whether or not snapshots where collected by the test.

• step_id (int, optional) – The step ID.

• sub_test_step_details ([SyntheticsStepDetail], optional) – If this step includes a sub-test. Subtests documentation.

• time_to_interactive (float, optional) – Time before starting the step.

• type (SyntheticsStepType, optional) – Step type used in your Synthetic test.

• url (str, optional) – URL to perform the step against.

• value (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) – Value for the step.

• vitals_metrics ([SyntheticsCoreWebVitals], optional) – Array of Core Web Vitals metrics for the step.

• warnings ([SyntheticsStepDetailWarning], optional) – Warning collected that didn’t failed the step.

datadog_api_client.v1.model.synthetics_step_detail_warning module

class SyntheticsStepDetailWarning(arg: None)

class SyntheticsStepDetailWarning(arg: ModelComposed)

class SyntheticsStepDetailWarning(*args, **kwargs)

Bases: ModelNormal

Object collecting warnings for a given step.

Parameters:

• message (str) – Message for the warning.

• type (SyntheticsWarningType) – User locator used.

datadog_api_client.v1.model.synthetics_step_type module

class SyntheticsStepType(arg: None)

class SyntheticsStepType(arg: ModelComposed)

class SyntheticsStepType(*args, **kwargs)

Bases: ModelSimple

Step type used in your Synthetic test.

Parameters:

• value (str) – Must be one of [“assertCurrentUrl”, “assertElementAttribute”, “assertElementContent”, “assertElementPresent”, “assertEmail”, “assertFileDownload”, “assertFromJavascript”, “assertPageContains”, “assertPageLacks”, “assertRequests”, “click”, “extractFromJavascript”, “extractFromEmailBody”, “extractVariable”, “goToEmailLink”, “goToUrl”, “goToUrlAndMeasureTti”, “hover”, “playSubTest”, “pressKey”, “refresh”, “runApiTest”, “scroll”, “selectOption”, “typeText”, “uploadFiles”, “wait”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_call_type module

class SyntheticsTestCallType(arg: None)

class SyntheticsTestCallType(arg: ModelComposed)

class SyntheticsTestCallType(*args, **kwargs)

Bases: ModelSimple

The type of gRPC call to perform.

Parameters:

• value (str) – Must be one of [“healthcheck”, “unary”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_ci_options module

class SyntheticsTestCiOptions(arg: None)

class SyntheticsTestCiOptions(arg: ModelComposed)

class SyntheticsTestCiOptions(*args, **kwargs)

Bases: ModelNormal

CI/CD options for a Synthetic test.

Parameters:

execution_rule (SyntheticsTestExecutionRule) – Execution rule for a Synthetic test.

datadog_api_client.v1.model.synthetics_test_config module

class SyntheticsTestConfig(arg: None)

class SyntheticsTestConfig(arg: ModelComposed)

class SyntheticsTestConfig(*args, **kwargs)

Bases: ModelNormal

Configuration object for a Synthetic test.

Parameters:

• assertions ([SyntheticsAssertion], optional) – Array of assertions used for the test. Required for single API tests.

• config_variables ([SyntheticsConfigVariable], optional) – Array of variables used for the test.

• request (SyntheticsTestRequest, optional) – Object describing the Synthetic test request.

• variables ([SyntheticsBrowserVariable], optional) – Browser tests only - array of variables used for the test steps.

datadog_api_client.v1.model.synthetics_test_details module

class SyntheticsTestDetails(arg: None)

class SyntheticsTestDetails(arg: ModelComposed)

class SyntheticsTestDetails(*args, **kwargs)

Bases: ModelNormal

Object containing details about your Synthetic test.

Parameters:

• config (SyntheticsTestConfig, optional) – Configuration object for a Synthetic test.

• creator (Creator, optional) – Object describing the creator of the shared element.

• locations ([str], optional) – Array of locations used to run the test.

• message (str, optional) – Notification message associated with the test.

• monitor_id (int, optional) – The associated monitor ID.

• name (str, optional) – Name of the test.

• options (SyntheticsTestOptions, optional) – Object describing the extra options for a Synthetic test.

• public_id (str, optional) – The test public ID.

• status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.

• steps ([SyntheticsStep], optional) – For browser test, the steps of the test.

• subtype (SyntheticsTestDetailsSubType, optional) – The subtype of the Synthetic API test, http , ssl , tcp , dns , icmp , udp , websocket , grpc or multi.

• tags ([str], optional) – Array of tags attached to the test.

• type (SyntheticsTestDetailsType, optional) – Type of the Synthetic test, either api or browser.

datadog_api_client.v1.model.synthetics_test_details_sub_type module

class SyntheticsTestDetailsSubType(arg: None)

class SyntheticsTestDetailsSubType(arg: ModelComposed)

class SyntheticsTestDetailsSubType(*args, **kwargs)

Bases: ModelSimple

The subtype of the Synthetic API test, http, ssl, tcp,

dns, icmp, udp, websocket, grpc or multi.

Parameters:

• value (str) – Must be one of [“http”, “ssl”, “tcp”, “dns”, “multi”, “icmp”, “udp”, “websocket”, “grpc”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_details_type module

class SyntheticsTestDetailsType(arg: None)

class SyntheticsTestDetailsType(arg: ModelComposed)

class SyntheticsTestDetailsType(*args, **kwargs)

Bases: ModelSimple

Type of the Synthetic test, either api or browser.

Parameters:

• value (str) – Must be one of [“api”, “browser”, “mobile”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_execution_rule module

class SyntheticsTestExecutionRule(arg: None)

class SyntheticsTestExecutionRule(arg: ModelComposed)

class SyntheticsTestExecutionRule(*args, **kwargs)

Bases: ModelSimple

Execution rule for a Synthetic test.

Parameters:

• value (str) – Must be one of [“blocking”, “non_blocking”, “skipped”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_headers module

class SyntheticsTestHeaders(arg: None)

class SyntheticsTestHeaders(arg: ModelComposed)

class SyntheticsTestHeaders(*args, **kwargs)

Bases: ModelNormal

Headers to include when performing the test.

datadog_api_client.v1.model.synthetics_test_metadata module

class SyntheticsTestMetadata(arg: None)

class SyntheticsTestMetadata(arg: ModelComposed)

class SyntheticsTestMetadata(*args, **kwargs)

Bases: ModelNormal

Metadata to include when performing the gRPC test.

datadog_api_client.v1.model.synthetics_test_monitor_status module

class SyntheticsTestMonitorStatus(arg: None)

class SyntheticsTestMonitorStatus(arg: ModelComposed)

class SyntheticsTestMonitorStatus(*args, **kwargs)

Bases: ModelSimple

The status of your Synthetic monitor.

• O for not triggered

• 1 for triggered

• 2 for no data

Parameters:

• value (int) – Must be one of [0, 1, 2].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_options module

class SyntheticsTestOptions(arg: None)

class SyntheticsTestOptions(arg: ModelComposed)

class SyntheticsTestOptions(*args, **kwargs)

Bases: ModelNormal

Object describing the extra options for a Synthetic test.

Parameters:

• accept_self_signed (bool, optional) – For SSL tests, whether or not the test should allow self signed certificates.

• allow_insecure (bool, optional) – Allows loading insecure content for an HTTP request in an API test.

• blocked_request_patterns ([str], optional) – Array of URL patterns to block.

• check_certificate_revocation (bool, optional) – For SSL tests, whether or not the test should fail on revoked certificate in stapled OCSP.

• ci (SyntheticsTestCiOptions, optional) – CI/CD options for a Synthetic test.

• device_ids ([str], optional) – For browser test, array with the different device IDs used to run the test.

• disable_aia_intermediate_fetching (bool, optional) – For SSL tests, whether or not the test should disable fetching intermediate certificates from AIA.

• disable_cors (bool, optional) – Whether or not to disable CORS mechanism.

• disable_csp (bool, optional) – Disable Content Security Policy for browser tests.

• enable_profiling (bool, optional) – Enable profiling for browser tests.

• enable_security_testing (bool, optional) – Enable security testing for browser tests. Security testing is not available anymore. This field is deprecated and won’t be used. Deprecated.

• follow_redirects (bool, optional) – For API HTTP test, whether or not the test should follow redirects.

• http_version (SyntheticsTestOptionsHTTPVersion, optional) – HTTP version to use for a Synthetic test.

• ignore_server_certificate_error (bool, optional) – Ignore server certificate error for browser tests.

• initial_navigation_timeout (int, optional) – Timeout before declaring the initial step as failed (in seconds) for browser tests.

• min_failure_duration (int, optional) – Minimum amount of time in failure required to trigger an alert.

• min_location_failed (int, optional) – Minimum number of locations in failure required to trigger an alert.

• monitor_name (str, optional) – The monitor name is used for the alert title as well as for all monitor dashboard widgets and SLOs.

• monitor_options (SyntheticsTestOptionsMonitorOptions, optional) – Object containing the options for a Synthetic test as a monitor (for example, renotification).

• monitor_priority (int, optional) – Integer from 1 (high) to 5 (low) indicating alert severity.

• no_screenshot (bool, optional) – Prevents saving screenshots of the steps.

• restricted_roles (SyntheticsRestrictedRoles, optional) – A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

• retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.

• rum_settings (SyntheticsBrowserTestRumSettings, optional) –

  The RUM data collection settings for the Synthetic browser test. Note: There are 3 ways to format RUM settings:

  { isEnabled: false } RUM data is not collected.

  { isEnabled: true } RUM data is collected from the Synthetic test’s default application.

  { isEnabled: true, applicationId: "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx", clientTokenId: 12345 } RUM data is collected using the specified application.

• scheduling (SyntheticsTestOptionsScheduling, optional) – Object containing timeframes and timezone used for advanced scheduling.

• tick_every (int, optional) – The frequency at which to run the Synthetic test (in seconds).

datadog_api_client.v1.model.synthetics_test_options_monitor_options module

class SyntheticsTestOptionsMonitorOptions(arg: None)

class SyntheticsTestOptionsMonitorOptions(arg: ModelComposed)

class SyntheticsTestOptionsMonitorOptions(*args, **kwargs)

Bases: ModelNormal

Object containing the options for a Synthetic test as a monitor (for example, renotification).

Parameters:

• escalation_message (str, optional) – Message to include in the escalation notification.

• notification_preset_name (SyntheticsTestOptionsMonitorOptionsNotificationPresetName, optional) – The name of the preset for the notification for the monitor.

• renotify_interval (int, optional) – Time interval before renotifying if the test is still failing (in minutes).

• renotify_occurrences (int, optional) – The number of times to renotify if the test is still failing.

datadog_api_client.v1.model.synthetics_test_options_monitor_options_notification_preset_name module

class SyntheticsTestOptionsMonitorOptionsNotificationPresetName(arg: None)

class SyntheticsTestOptionsMonitorOptionsNotificationPresetName(arg: ModelComposed)

class SyntheticsTestOptionsMonitorOptionsNotificationPresetName(*args, **kwargs)

Bases: ModelSimple

The name of the preset for the notification for the monitor.

Parameters:

• value (str) – Must be one of [“show_all”, “hide_all”, “hide_query”, “hide_handles”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_options_retry module

class SyntheticsTestOptionsRetry(arg: None)

class SyntheticsTestOptionsRetry(arg: ModelComposed)

class SyntheticsTestOptionsRetry(*args, **kwargs)

Bases: ModelNormal

Object describing the retry strategy to apply to a Synthetic test.

Parameters:

• count (int, optional) – Number of times a test needs to be retried before marking a location as failed. Defaults to 0.

• interval (float, optional) – Time interval between retries (in milliseconds). Defaults to 300ms.

datadog_api_client.v1.model.synthetics_test_options_scheduling module

class SyntheticsTestOptionsScheduling(arg: None)

class SyntheticsTestOptionsScheduling(arg: ModelComposed)

class SyntheticsTestOptionsScheduling(*args, **kwargs)

Bases: ModelNormal

Object containing timeframes and timezone used for advanced scheduling.

Parameters:

• timeframes ([SyntheticsTestOptionsSchedulingTimeframe]) – Array containing objects describing the scheduling pattern to apply to each day.

• timezone (str) – Timezone in which the timeframe is based.

datadog_api_client.v1.model.synthetics_test_options_scheduling_timeframe module

class SyntheticsTestOptionsSchedulingTimeframe(arg: None)

class SyntheticsTestOptionsSchedulingTimeframe(arg: ModelComposed)

class SyntheticsTestOptionsSchedulingTimeframe(*args, **kwargs)

Bases: ModelNormal

Object describing a timeframe.

Parameters:

• day (int) – Number representing the day of the week.

• _from (str) – The hour of the day on which scheduling starts.

• to (str) – The hour of the day on which scheduling ends.

datadog_api_client.v1.model.synthetics_test_pause_status module

class SyntheticsTestPauseStatus(arg: None)

class SyntheticsTestPauseStatus(arg: ModelComposed)

class SyntheticsTestPauseStatus(*args, **kwargs)

Bases: ModelSimple

Define whether you want to start (live) or pause (paused) a

Synthetic test.

Parameters:

• value (str) – Must be one of [“live”, “paused”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_process_status module

class SyntheticsTestProcessStatus(arg: None)

class SyntheticsTestProcessStatus(arg: ModelComposed)

class SyntheticsTestProcessStatus(*args, **kwargs)

Bases: ModelSimple

Status of a Synthetic test.

Parameters:

• value (str) – Must be one of [“not_scheduled”, “scheduled”, “finished”, “finished_with_error”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_request module

class SyntheticsTestRequest(arg: None)

class SyntheticsTestRequest(arg: ModelComposed)

class SyntheticsTestRequest(*args, **kwargs)

Bases: ModelNormal

Object describing the Synthetic test request.

Parameters:

• allow_insecure (bool, optional) – Allows loading insecure content for an HTTP request in a multistep test step.

• basic_auth (SyntheticsBasicAuth, optional) – Object to handle basic authentication when performing the test.

• body (str, optional) – Body to include in the test.

• body_type (SyntheticsTestRequestBodyType, optional) – Type of the request body.

• call_type (SyntheticsTestCallType, optional) – The type of gRPC call to perform.

• certificate (SyntheticsTestRequestCertificate, optional) – Client certificate to use when performing the test request.

• certificate_domains ([str], optional) – By default, the client certificate is applied on the domain of the starting URL for browser tests. If you want your client certificate to be applied on other domains instead, add them in certificateDomains.

• check_certificate_revocation (bool, optional) – Check for certificate revocation.

• compressed_json_descriptor (str, optional) – A protobuf JSON descriptor that needs to be gzipped first then base64 encoded.

• compressed_proto_file (str, optional) – A protobuf file that needs to be gzipped first then base64 encoded.

• disable_aia_intermediate_fetching (bool, optional) – Disable fetching intermediate certificates from AIA.

• dns_server (str, optional) – DNS server to use for DNS tests.

• dns_server_port (SyntheticsTestRequestDNSServerPort, optional) – DNS server port to use for DNS tests.

• files ([SyntheticsTestRequestBodyFile], optional) – Files to be used as part of the request in the test. Only valid if bodyType is multipart/form-data.

• follow_redirects (bool, optional) – Specifies whether or not the request follows redirects.

• form ({str: (str,)}, optional) – Form to be used as part of the request in the test. Only valid if bodyType is multipart/form-data.

• headers (SyntheticsTestHeaders, optional) – Headers to include when performing the test.

• host (str, optional) – Host name to perform the test with.

• http_version (SyntheticsTestOptionsHTTPVersion, optional) – HTTP version to use for a Synthetic test.

• is_message_base64_encoded (bool, optional) – Whether the message is base64 encoded.

• message (str, optional) – Message to send for UDP or WebSocket tests.

• metadata (SyntheticsTestMetadata, optional) – Metadata to include when performing the gRPC test.

• method (str, optional) – Either the HTTP method/verb to use or a gRPC method available on the service set in the service field. Required if subtype is HTTP or if subtype is grpc and callType is unary.

• no_saving_response_body (bool, optional) – Determines whether or not to save the response body.

• number_of_packets (int, optional) – Number of pings to use per test.

• persist_cookies (bool, optional) – Persist cookies across redirects.

• port (SyntheticsTestRequestPort, optional) – Port to use when performing the test.

• proxy (SyntheticsTestRequestProxy, optional) – The proxy to perform the test.

• query (dict, optional) – Query to use for the test.

• servername (str, optional) – For SSL tests, it specifies on which server you want to initiate the TLS handshake, allowing the server to present one of multiple possible certificates on the same IP address and TCP port number.

• service (str, optional) – The gRPC service on which you want to perform the gRPC call.

• should_track_hops (bool, optional) – Turns on a traceroute probe to discover all gateways along the path to the host destination.

• timeout (float, optional) – Timeout in seconds for the test.

• url (str, optional) – URL to perform the test with.

datadog_api_client.v1.model.synthetics_test_request_body_file module

class SyntheticsTestRequestBodyFile(arg: None)

class SyntheticsTestRequestBodyFile(arg: ModelComposed)

class SyntheticsTestRequestBodyFile(*args, **kwargs)

Bases: ModelNormal

Object describing a file to be used as part of the request in the test.

Parameters:

• bucket_key (str, optional) – Bucket key of the file.

• content (str, optional) – Content of the file.

• name (str, optional) – Name of the file.

• original_file_name (str, optional) – Original name of the file.

• size (int, optional) – Size of the file.

• type (str, optional) – Type of the file.

datadog_api_client.v1.model.synthetics_test_request_body_type module

class SyntheticsTestRequestBodyType(arg: None)

class SyntheticsTestRequestBodyType(arg: ModelComposed)

class SyntheticsTestRequestBodyType(*args, **kwargs)

Bases: ModelSimple

Type of the request body.

Parameters:

• value (str) – Must be one of [“text/plain”, “application/json”, “text/xml”, “text/html”, “application/x-www-form-urlencoded”, “graphql”, “application/octet-stream”, “multipart/form-data”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_request_certificate module

class SyntheticsTestRequestCertificate(arg: None)

class SyntheticsTestRequestCertificate(arg: ModelComposed)

class SyntheticsTestRequestCertificate(*args, **kwargs)

Bases: ModelNormal

Client certificate to use when performing the test request.

Parameters:

• cert (SyntheticsTestRequestCertificateItem, optional) – Define a request certificate.

• key (SyntheticsTestRequestCertificateItem, optional) – Define a request certificate.

datadog_api_client.v1.model.synthetics_test_request_certificate_item module

class SyntheticsTestRequestCertificateItem(arg: None)

class SyntheticsTestRequestCertificateItem(arg: ModelComposed)

class SyntheticsTestRequestCertificateItem(*args, **kwargs)

Bases: ModelNormal

Define a request certificate.

Parameters:

• content (str, optional) – Content of the certificate or key.

• filename (str, optional) – File name for the certificate or key.

• updated_at (str, optional) – Date of update of the certificate or key, ISO format.

datadog_api_client.v1.model.synthetics_test_request_dns_server_port module

class SyntheticsTestRequestDNSServerPort(arg: None)

class SyntheticsTestRequestDNSServerPort(arg: ModelComposed)

class SyntheticsTestRequestDNSServerPort(*args, **kwargs)

Bases: ModelComposed

DNS server port to use for DNS tests.

datadog_api_client.v1.model.synthetics_test_request_port module

class SyntheticsTestRequestPort(arg: None)

class SyntheticsTestRequestPort(arg: ModelComposed)

class SyntheticsTestRequestPort(*args, **kwargs)

Bases: ModelComposed

Port to use when performing the test.

datadog_api_client.v1.model.synthetics_test_request_proxy module

class SyntheticsTestRequestProxy(arg: None)

class SyntheticsTestRequestProxy(arg: ModelComposed)

class SyntheticsTestRequestProxy(*args, **kwargs)

Bases: ModelNormal

The proxy to perform the test.

Parameters:

• headers (SyntheticsTestHeaders, optional) – Headers to include when performing the test.

• url (str) – URL of the proxy to perform the test.

datadog_api_client.v1.model.synthetics_test_restriction_policy_binding module

class SyntheticsTestRestrictionPolicyBinding(arg: None)

class SyntheticsTestRestrictionPolicyBinding(arg: ModelComposed)

class SyntheticsTestRestrictionPolicyBinding(*args, **kwargs)

Bases: ModelNormal

Objects describing the binding used for a mobile test.

Parameters:

• principals ([str], optional) – List of principals for a mobile test binding.

• relation (SyntheticsTestRestrictionPolicyBindingRelation, optional) – The type of relation for the binding.

datadog_api_client.v1.model.synthetics_test_restriction_policy_binding_relation module

class SyntheticsTestRestrictionPolicyBindingRelation(arg: None)

class SyntheticsTestRestrictionPolicyBindingRelation(arg: ModelComposed)

class SyntheticsTestRestrictionPolicyBindingRelation(*args, **kwargs)

Bases: ModelSimple

The type of relation for the binding.

Parameters:

• value (str) – Must be one of [“editor”, “viewer”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.synthetics_test_uptime module

class SyntheticsTestUptime(arg: None)

class SyntheticsTestUptime(arg: ModelComposed)

class SyntheticsTestUptime(*args, **kwargs)

Bases: ModelNormal

Object containing the uptime for a Synthetic test ID.

Parameters:

• from_ts (int, optional) – Timestamp in seconds for the start of uptime.

• overall (SyntheticsUptime, optional) – Object containing the uptime information.

• public_id (str, optional) – A Synthetic test ID.

• to_ts (int, optional) – Timestamp in seconds for the end of uptime.

datadog_api_client.v1.model.synthetics_timing module

class SyntheticsTiming(arg: None)

class SyntheticsTiming(arg: ModelComposed)

class SyntheticsTiming(*args, **kwargs)

Bases: ModelNormal

Object containing all metrics and their values collected for a Synthetic API test. See the Synthetic Monitoring Metrics documentation.

Parameters:

• dns (float, optional) – The duration in millisecond of the DNS lookup.

• download (float, optional) – The time in millisecond to download the response.

• first_byte (float, optional) – The time in millisecond to first byte.

• handshake (float, optional) – The duration in millisecond of the TLS handshake.

• redirect (float, optional) – The time in millisecond spent during redirections.

• ssl (float, optional) – The duration in millisecond of the TLS handshake.

• tcp (float, optional) – Time in millisecond to establish the TCP connection.

• total (float, optional) – The overall time in millisecond the request took to be processed.

• wait (float, optional) – Time spent in millisecond waiting for a response.

datadog_api_client.v1.model.synthetics_trigger_body module

class SyntheticsTriggerBody(arg: None)

class SyntheticsTriggerBody(arg: ModelComposed)

class SyntheticsTriggerBody(*args, **kwargs)

Bases: ModelNormal

Object describing the Synthetic tests to trigger.

Parameters:

tests ([SyntheticsTriggerTest]) – List of Synthetic tests.

datadog_api_client.v1.model.synthetics_trigger_ci_test_location module

class SyntheticsTriggerCITestLocation(arg: None)

class SyntheticsTriggerCITestLocation(arg: ModelComposed)

class SyntheticsTriggerCITestLocation(*args, **kwargs)

Bases: ModelNormal

Synthetic location.

Parameters:

• id (int, optional) – Unique identifier of the location.

• name (str, optional) – Name of the location.

datadog_api_client.v1.model.synthetics_trigger_ci_test_run_result module

class SyntheticsTriggerCITestRunResult(arg: None)

class SyntheticsTriggerCITestRunResult(arg: ModelComposed)

class SyntheticsTriggerCITestRunResult(*args, **kwargs)

Bases: ModelNormal

Information about a single test run.

Parameters:

• device (str, optional) – The device ID.

• location (int, optional) – The location ID of the test run.

• public_id (str, optional) – The public ID of the Synthetic test.

• result_id (str, optional) – ID of the result.

datadog_api_client.v1.model.synthetics_trigger_ci_tests_response module

class SyntheticsTriggerCITestsResponse(arg: None)

class SyntheticsTriggerCITestsResponse(arg: ModelComposed)

class SyntheticsTriggerCITestsResponse(*args, **kwargs)

Bases: ModelNormal

Object containing information about the tests triggered.

Parameters:

• batch_id (str, none_type, optional) – The public ID of the batch triggered.

• locations ([SyntheticsTriggerCITestLocation], optional) – List of Synthetic locations.

• results ([SyntheticsTriggerCITestRunResult], optional) – Information about the tests runs.

• triggered_check_ids ([str], optional) – The public IDs of the Synthetic test triggered.

datadog_api_client.v1.model.synthetics_trigger_test module

class SyntheticsTriggerTest(arg: None)

class SyntheticsTriggerTest(arg: ModelComposed)

class SyntheticsTriggerTest(*args, **kwargs)

Bases: ModelNormal

Test configuration for Synthetics

Parameters:

• metadata (SyntheticsCIBatchMetadata, optional) – Metadata for the Synthetic tests run.

• public_id (str) – The public ID of the Synthetic test to trigger.

datadog_api_client.v1.model.synthetics_update_test_pause_status_payload module

class SyntheticsUpdateTestPauseStatusPayload(arg: None)

class SyntheticsUpdateTestPauseStatusPayload(arg: ModelComposed)

class SyntheticsUpdateTestPauseStatusPayload(*args, **kwargs)

Bases: ModelNormal

Object to start or pause an existing Synthetic test.

Parameters:

new_status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.

datadog_api_client.v1.model.synthetics_uptime module

class SyntheticsUptime(arg: None)

class SyntheticsUptime(arg: ModelComposed)

class SyntheticsUptime(*args, **kwargs)

Bases: ModelNormal

Object containing the uptime information.

Parameters:

• errors ([SLOHistoryResponseErrorWithType], none_type, optional) – An array of error objects returned while querying the history data for the service level objective.

• group (str, optional) – The location name

• history ([[float]], optional) – The state transition history for the monitor, represented as an array of pairs. Each pair is an array where the first element is the transition timestamp in Unix epoch format (integer) and the second element is the state (integer). For the state, an integer value of 0 indicates uptime, 1 indicates downtime, and 2 indicates no data.

• span_precision (float, optional) – The number of decimal places to which the SLI value is accurate for the given from-to timestamps.

• uptime (float, optional) – The overall uptime.

datadog_api_client.v1.model.synthetics_variable_parser module

class SyntheticsVariableParser(arg: None)

class SyntheticsVariableParser(arg: ModelComposed)

class SyntheticsVariableParser(*args, **kwargs)

Bases: ModelNormal

Details of the parser to use for the global variable.

Parameters:

• type (SyntheticsGlobalVariableParserType) – Type of parser for a Synthetic global variable from a synthetics test.

• value (str, optional) – Regex or JSON path used for the parser. Not used with type raw.

datadog_api_client.v1.model.synthetics_warning_type module

class SyntheticsWarningType(arg: None)

class SyntheticsWarningType(arg: ModelComposed)

class SyntheticsWarningType(*args, **kwargs)

Bases: ModelSimple

User locator used.

Parameters:

• value (str) – If omitted defaults to “user_locator”. Must be one of [“user_locator”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_cell_display_mode module

class TableWidgetCellDisplayMode(arg: None)

class TableWidgetCellDisplayMode(arg: ModelComposed)

class TableWidgetCellDisplayMode(*args, **kwargs)

Bases: ModelSimple

Define a display mode for the table cell.

Parameters:

• value (str) – Must be one of [“number”, “bar”, “trend”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_definition module

class TableWidgetDefinition(arg: None)

class TableWidgetDefinition(arg: ModelComposed)

class TableWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The table visualization is available on timeboards and screenboards. It displays columns of metrics grouped by tag key.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• has_search_bar (TableWidgetHasSearchBar, optional) – Controls the display of the search bar.

• requests ([TableWidgetRequest]) – Widget definition.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (TableWidgetDefinitionType) – Type of the table widget.

datadog_api_client.v1.model.table_widget_definition_type module

class TableWidgetDefinitionType(arg: None)

class TableWidgetDefinitionType(arg: ModelComposed)

class TableWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the table widget.

Parameters:

• value (str) – If omitted defaults to “query_table”. Must be one of [“query_table”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_has_search_bar module

class TableWidgetHasSearchBar(arg: None)

class TableWidgetHasSearchBar(arg: ModelComposed)

class TableWidgetHasSearchBar(*args, **kwargs)

Bases: ModelSimple

Controls the display of the search bar.

Parameters:

• value (str) – Must be one of [“always”, “never”, “auto”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_request module

class TableWidgetRequest(arg: None)

class TableWidgetRequest(arg: ModelComposed)

class TableWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated table widget.

Parameters:

• aggregator (WidgetAggregator, optional) – Aggregator used for the request.

• alias (str, optional) – The column name (defaults to the metric name).

• apm_query (LogQueryDefinition, optional) – The log query.

• apm_stats_query (ApmStatsQueryDefinition, optional) – The APM stats query for table and distributions widgets.

• cell_display_mode ([TableWidgetCellDisplayMode], optional) – A list of display modes for each table cell.

• conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.

• event_query (LogQueryDefinition, optional) – The log query.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• limit (int, optional) – For metric queries, the number of lines to show in the table. Only one request should have this property.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• order (WidgetSort, optional) – Widget sorting methods.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Query definition.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• sort (WidgetSortBy, optional) – The controls for sorting the widget.

• text_formats ([[TableWidgetTextFormatRule]], optional) – List of text formats for columns produced by tags.

datadog_api_client.v1.model.table_widget_text_format_match module

class TableWidgetTextFormatMatch(arg: None)

class TableWidgetTextFormatMatch(arg: ModelComposed)

class TableWidgetTextFormatMatch(*args, **kwargs)

Bases: ModelNormal

Match rule for the table widget text format.

Parameters:

• type (TableWidgetTextFormatMatchType) – Match or compare option.

• value (str) – Table Widget Match String.

datadog_api_client.v1.model.table_widget_text_format_match_type module

class TableWidgetTextFormatMatchType(arg: None)

class TableWidgetTextFormatMatchType(arg: ModelComposed)

class TableWidgetTextFormatMatchType(*args, **kwargs)

Bases: ModelSimple

Match or compare option.

Parameters:

• value (str) – Must be one of [“is”, “is_not”, “contains”, “does_not_contain”, “starts_with”, “ends_with”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_text_format_palette module

class TableWidgetTextFormatPalette(arg: None)

class TableWidgetTextFormatPalette(arg: ModelComposed)

class TableWidgetTextFormatPalette(*args, **kwargs)

Bases: ModelSimple

Color-on-color palette to highlight replaced text.

Parameters:

• value (str) – If omitted defaults to “white_on_green”. Must be one of [“white_on_red”, “white_on_yellow”, “white_on_green”, “black_on_light_red”, “black_on_light_yellow”, “black_on_light_green”, “red_on_white”, “yellow_on_white”, “green_on_white”, “custom_bg”, “custom_text”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_text_format_replace module

class TableWidgetTextFormatReplace(arg: None)

class TableWidgetTextFormatReplace(arg: ModelComposed)

class TableWidgetTextFormatReplace(*args, **kwargs)

Bases: ModelComposed

Replace rule for the table widget text format.

Parameters:

• type (TableWidgetTextFormatReplaceAllType) – Table widget text format replace all type.

• _with (str) – Replace All type.

• substring (str) – Text that will be replaced.

datadog_api_client.v1.model.table_widget_text_format_replace_all module

class TableWidgetTextFormatReplaceAll(arg: None)

class TableWidgetTextFormatReplaceAll(arg: ModelComposed)

class TableWidgetTextFormatReplaceAll(*args, **kwargs)

Bases: ModelNormal

Match All definition.

Parameters:

• type (TableWidgetTextFormatReplaceAllType) – Table widget text format replace all type.

• _with (str) – Replace All type.

datadog_api_client.v1.model.table_widget_text_format_replace_all_type module

class TableWidgetTextFormatReplaceAllType(arg: None)

class TableWidgetTextFormatReplaceAllType(arg: ModelComposed)

class TableWidgetTextFormatReplaceAllType(*args, **kwargs)

Bases: ModelSimple

Table widget text format replace all type.

Parameters:

• value (str) – If omitted defaults to “all”. Must be one of [“all”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_text_format_replace_substring module

class TableWidgetTextFormatReplaceSubstring(arg: None)

class TableWidgetTextFormatReplaceSubstring(arg: ModelComposed)

class TableWidgetTextFormatReplaceSubstring(*args, **kwargs)

Bases: ModelNormal

Match Sub-string definition.

Parameters:

• substring (str) – Text that will be replaced.

• type (TableWidgetTextFormatReplaceSubstringType) – Table widget text format replace sub-string type.

• _with (str) – Text that will replace original sub-string.

datadog_api_client.v1.model.table_widget_text_format_replace_substring_type module

class TableWidgetTextFormatReplaceSubstringType(arg: None)

class TableWidgetTextFormatReplaceSubstringType(arg: ModelComposed)

class TableWidgetTextFormatReplaceSubstringType(*args, **kwargs)

Bases: ModelSimple

Table widget text format replace sub-string type.

Parameters:

• value (str) – If omitted defaults to “substring”. Must be one of [“substring”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.table_widget_text_format_rule module

class TableWidgetTextFormatRule(arg: None)

class TableWidgetTextFormatRule(arg: ModelComposed)

class TableWidgetTextFormatRule(*args, **kwargs)

Bases: ModelNormal

Text format rules.

Parameters:

• custom_bg_color (str, optional) – Hex representation of the custom background color. Used with custom background palette option.

• custom_fg_color (str, optional) – Hex representation of the custom text color. Used with custom text palette option.

• match (TableWidgetTextFormatMatch) – Match rule for the table widget text format.

• palette (TableWidgetTextFormatPalette, optional) – Color-on-color palette to highlight replaced text.

• replace (TableWidgetTextFormatReplace, optional) – Replace rule for the table widget text format.

datadog_api_client.v1.model.tag_to_hosts module

class TagToHosts(arg: None)

class TagToHosts(arg: ModelComposed)

class TagToHosts(*args, **kwargs)

Bases: ModelNormal

In this object, the key is the tag, the value is a list of host names that are reporting that tag.

Parameters:

tags ({str: ([str],)}, optional) – A list of tags to apply to the host.

datadog_api_client.v1.model.target_format_type module

class TargetFormatType(arg: None)

class TargetFormatType(arg: ModelComposed)

class TargetFormatType(*args, **kwargs)

Bases: ModelSimple

If the target_type of the remapper is attribute, try to cast the value to a new specific type.

If the cast is not possible, the original type is kept. string, integer, or double are the possible types. If the target_type is tag, this parameter may not be specified.

Parameters:

• value (str) – Must be one of [“auto”, “string”, “integer”, “double”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.timeseries_background module

class TimeseriesBackground(arg: None)

class TimeseriesBackground(arg: ModelComposed)

class TimeseriesBackground(*args, **kwargs)

Bases: ModelNormal

Set a timeseries on the widget background.

Parameters:

• type (TimeseriesBackgroundType) – Timeseries is made using an area or bars.

• yaxis (WidgetAxis, optional) – Axis controls for the widget.

datadog_api_client.v1.model.timeseries_background_type module

class TimeseriesBackgroundType(arg: None)

class TimeseriesBackgroundType(arg: ModelComposed)

class TimeseriesBackgroundType(*args, **kwargs)

Bases: ModelSimple

Timeseries is made using an area or bars.

Parameters:

• value (str) – If omitted defaults to “area”. Must be one of [“bars”, “area”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.timeseries_widget_definition module

class TimeseriesWidgetDefinition(arg: None)

class TimeseriesWidgetDefinition(arg: ModelComposed)

class TimeseriesWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The timeseries visualization allows you to display the evolution of one or more metrics, log events, or Indexed Spans over time.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• events ([WidgetEvent], optional) – List of widget events.

• legend_columns ([TimeseriesWidgetLegendColumn], optional) – Columns displayed in the legend.

• legend_layout (TimeseriesWidgetLegendLayout, optional) – Layout of the legend.

• legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.

• markers ([WidgetMarker], optional) – List of markers.

• requests ([TimeseriesWidgetRequest]) – List of timeseries widget requests.

• right_yaxis (WidgetAxis, optional) – Axis controls for the widget.

• show_legend (bool, optional) – (screenboard only) Show the legend for this widget.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (TimeseriesWidgetDefinitionType) – Type of the timeseries widget.

• yaxis (WidgetAxis, optional) – Axis controls for the widget.

datadog_api_client.v1.model.timeseries_widget_definition_type module

class TimeseriesWidgetDefinitionType(arg: None)

class TimeseriesWidgetDefinitionType(arg: ModelComposed)

class TimeseriesWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the timeseries widget.

Parameters:

• value (str) – If omitted defaults to “timeseries”. Must be one of [“timeseries”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.timeseries_widget_expression_alias module

class TimeseriesWidgetExpressionAlias(arg: None)

class TimeseriesWidgetExpressionAlias(arg: ModelComposed)

class TimeseriesWidgetExpressionAlias(*args, **kwargs)

Bases: ModelNormal

Define an expression alias.

Parameters:

• alias_name (str, optional) – Expression alias.

• expression (str) – Expression name.

datadog_api_client.v1.model.timeseries_widget_legend_column module

class TimeseriesWidgetLegendColumn(arg: None)

class TimeseriesWidgetLegendColumn(arg: ModelComposed)

class TimeseriesWidgetLegendColumn(*args, **kwargs)

Bases: ModelSimple

Legend column.

Parameters:

• value (str) – Must be one of [“value”, “avg”, “sum”, “min”, “max”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.timeseries_widget_legend_layout module

class TimeseriesWidgetLegendLayout(arg: None)

class TimeseriesWidgetLegendLayout(arg: ModelComposed)

class TimeseriesWidgetLegendLayout(*args, **kwargs)

Bases: ModelSimple

Layout of the legend.

Parameters:

• value (str) – Must be one of [“auto”, “horizontal”, “vertical”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.timeseries_widget_request module

class TimeseriesWidgetRequest(arg: None)

class TimeseriesWidgetRequest(arg: ModelComposed)

class TimeseriesWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated timeseries widget.

Parameters:

• apm_query (LogQueryDefinition, optional) – The log query.

• audit_query (LogQueryDefinition, optional) – The log query.

• display_type (WidgetDisplayType, optional) – Type of display to use for the request.

• event_query (LogQueryDefinition, optional) – The log query.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• log_query (LogQueryDefinition, optional) – The log query.

• metadata ([TimeseriesWidgetExpressionAlias], optional) – Used to define expression aliases.

• network_query (LogQueryDefinition, optional) – The log query.

• on_right_yaxis (bool, optional) – Whether or not to display a second y-axis on the right.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Widget query.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• style (WidgetRequestStyle, optional) – Define request widget style.

datadog_api_client.v1.model.toplist_widget_definition module

class ToplistWidgetDefinition(arg: None)

class ToplistWidgetDefinition(arg: ModelComposed)

class ToplistWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The top list visualization enables you to display a list of Tag value like hostname or service with the most or least of any metric value, such as highest consumers of CPU, hosts with the least disk space, etc.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• requests ([ToplistWidgetRequest]) – List of top list widget requests.

• style (ToplistWidgetStyle, optional) – Style customization for a top list widget.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (ToplistWidgetDefinitionType) – Type of the top list widget.

datadog_api_client.v1.model.toplist_widget_definition_type module

class ToplistWidgetDefinitionType(arg: None)

class ToplistWidgetDefinitionType(arg: ModelComposed)

class ToplistWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the top list widget.

Parameters:

• value (str) – If omitted defaults to “toplist”. Must be one of [“toplist”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.toplist_widget_display module

class ToplistWidgetDisplay(arg: None)

class ToplistWidgetDisplay(arg: ModelComposed)

class ToplistWidgetDisplay(*args, **kwargs)

Bases: ModelComposed

Top list widget display options.

Parameters:

• legend (ToplistWidgetLegend, optional) – Top list widget stacked legend behavior.

• type (ToplistWidgetStackedType) – Top list widget stacked display type.

datadog_api_client.v1.model.toplist_widget_flat module

class ToplistWidgetFlat(arg: None)

class ToplistWidgetFlat(arg: ModelComposed)

class ToplistWidgetFlat(*args, **kwargs)

Bases: ModelNormal

Top list widget flat display.

Parameters:

type (ToplistWidgetFlatType) – Top list widget flat display type.

datadog_api_client.v1.model.toplist_widget_flat_type module

class ToplistWidgetFlatType(arg: None)

class ToplistWidgetFlatType(arg: ModelComposed)

class ToplistWidgetFlatType(*args, **kwargs)

Bases: ModelSimple

Top list widget flat display type.

Parameters:

• value (str) – If omitted defaults to “flat”. Must be one of [“flat”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.toplist_widget_legend module

class ToplistWidgetLegend(arg: None)

class ToplistWidgetLegend(arg: ModelComposed)

class ToplistWidgetLegend(*args, **kwargs)

Bases: ModelSimple

Top list widget stacked legend behavior.

Parameters:

• value (str) – Must be one of [“automatic”, “inline”, “none”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.toplist_widget_request module

class ToplistWidgetRequest(arg: None)

class ToplistWidgetRequest(arg: ModelComposed)

class ToplistWidgetRequest(*args, **kwargs)

Bases: ModelNormal

Updated top list widget.

Parameters:

• apm_query (LogQueryDefinition, optional) – The log query.

• audit_query (LogQueryDefinition, optional) – The log query.

• conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.

• event_query (LogQueryDefinition, optional) – The log query.

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• log_query (LogQueryDefinition, optional) – The log query.

• network_query (LogQueryDefinition, optional) – The log query.

• process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.

• profile_metrics_query (LogQueryDefinition, optional) – The log query.

• q (str, optional) – Widget query.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

• rum_query (LogQueryDefinition, optional) – The log query.

• security_query (LogQueryDefinition, optional) – The log query.

• sort (WidgetSortBy, optional) – The controls for sorting the widget.

• style (WidgetRequestStyle, optional) – Define request widget style.

datadog_api_client.v1.model.toplist_widget_scaling module

class ToplistWidgetScaling(arg: None)

class ToplistWidgetScaling(arg: ModelComposed)

class ToplistWidgetScaling(*args, **kwargs)

Bases: ModelSimple

Top list widget scaling definition.

Parameters:

• value (str) – Must be one of [“absolute”, “relative”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.toplist_widget_stacked module

class ToplistWidgetStacked(arg: None)

class ToplistWidgetStacked(arg: ModelComposed)

class ToplistWidgetStacked(*args, **kwargs)

Bases: ModelNormal

Top list widget stacked display options.

Parameters:

• legend (ToplistWidgetLegend, optional) – Top list widget stacked legend behavior.

• type (ToplistWidgetStackedType) – Top list widget stacked display type.

datadog_api_client.v1.model.toplist_widget_stacked_type module

class ToplistWidgetStackedType(arg: None)

class ToplistWidgetStackedType(arg: ModelComposed)

class ToplistWidgetStackedType(*args, **kwargs)

Bases: ModelSimple

Top list widget stacked display type.

Parameters:

• value (str) – If omitted defaults to “stacked”. Must be one of [“stacked”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.toplist_widget_style module

class ToplistWidgetStyle(arg: None)

class ToplistWidgetStyle(arg: ModelComposed)

class ToplistWidgetStyle(*args, **kwargs)

Bases: ModelNormal

Style customization for a top list widget.

Parameters:

• display (ToplistWidgetDisplay, optional) – Top list widget display options.

• palette (str, optional) – Color palette to apply to the widget.

• scaling (ToplistWidgetScaling, optional) – Top list widget scaling definition.

datadog_api_client.v1.model.topology_map_widget_definition module

class TopologyMapWidgetDefinition(arg: None)

class TopologyMapWidgetDefinition(arg: ModelComposed)

class TopologyMapWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

This widget displays a topology of nodes and edges for different data sources. It replaces the service map widget.

Parameters:

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• requests ([TopologyRequest]) – One or more Topology requests.

• title (str, optional) – Title of your widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (TopologyMapWidgetDefinitionType) – Type of the topology map widget.

datadog_api_client.v1.model.topology_map_widget_definition_type module

class TopologyMapWidgetDefinitionType(arg: None)

class TopologyMapWidgetDefinitionType(arg: ModelComposed)

class TopologyMapWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the topology map widget.

Parameters:

• value (str) – If omitted defaults to “topology_map”. Must be one of [“topology_map”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.topology_query module

class TopologyQuery(arg: None)

class TopologyQuery(arg: ModelComposed)

class TopologyQuery(*args, **kwargs)

Bases: ModelNormal

Query to service-based topology data sources like the service map or data streams.

Parameters:

• data_source (TopologyQueryDataSource, optional) – Name of the data source

• filters ([str], optional) – Your environment and primary tag (or * if enabled for your account).

• service (str, optional) – Name of the service

datadog_api_client.v1.model.topology_query_data_source module

class TopologyQueryDataSource(arg: None)

class TopologyQueryDataSource(arg: ModelComposed)

class TopologyQueryDataSource(*args, **kwargs)

Bases: ModelSimple

Name of the data source

Parameters:

• value (str) – Must be one of [“data_streams”, “service_map”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.topology_request module

class TopologyRequest(arg: None)

class TopologyRequest(arg: ModelComposed)

class TopologyRequest(*args, **kwargs)

Bases: ModelNormal

Request that will return nodes and edges to be used by topology map.

Parameters:

• query (TopologyQuery, optional) – Query to service-based topology data sources like the service map or data streams.

• request_type (TopologyRequestType, optional) – Widget request type.

datadog_api_client.v1.model.topology_request_type module

class TopologyRequestType(arg: None)

class TopologyRequestType(arg: ModelComposed)

class TopologyRequestType(*args, **kwargs)

Bases: ModelSimple

Widget request type.

Parameters:

• value (str) – If omitted defaults to “topology”. Must be one of [“topology”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.tree_map_color_by module

class TreeMapColorBy(arg: None)

class TreeMapColorBy(arg: ModelComposed)

class TreeMapColorBy(*args, **kwargs)

Bases: ModelSimple

(deprecated) The attribute formerly used to determine color in the widget.

Parameters:

• value (str) – If omitted defaults to “user”. Must be one of [“user”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.tree_map_group_by module

class TreeMapGroupBy(arg: None)

class TreeMapGroupBy(arg: ModelComposed)

class TreeMapGroupBy(*args, **kwargs)

Bases: ModelSimple

(deprecated) The attribute formerly used to group elements in the widget.

Parameters:

• value (str) – Must be one of [“user”, “family”, “process”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.tree_map_size_by module

class TreeMapSizeBy(arg: None)

class TreeMapSizeBy(arg: ModelComposed)

class TreeMapSizeBy(*args, **kwargs)

Bases: ModelSimple

(deprecated) The attribute formerly used to determine size in the widget.

Parameters:

• value (str) – Must be one of [“pct_cpu”, “pct_mem”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.tree_map_widget_definition module

class TreeMapWidgetDefinition(arg: None)

class TreeMapWidgetDefinition(arg: ModelComposed)

class TreeMapWidgetDefinition(*args, **kwargs)

Bases: ModelNormal

The treemap visualization enables you to display hierarchical and nested data. It is well suited for queries that describe part-whole relationships, such as resource usage by availability zone, data center, or team.

Parameters:

• color_by (TreeMapColorBy, optional) – (deprecated) The attribute formerly used to determine color in the widget. Deprecated.

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• group_by (TreeMapGroupBy, optional) – (deprecated) The attribute formerly used to group elements in the widget. Deprecated.

• requests ([TreeMapWidgetRequest]) – List of treemap widget requests.

• size_by (TreeMapSizeBy, optional) – (deprecated) The attribute formerly used to determine size in the widget. Deprecated.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – Title of your widget.

• type (TreeMapWidgetDefinitionType) – Type of the treemap widget.

datadog_api_client.v1.model.tree_map_widget_definition_type module

class TreeMapWidgetDefinitionType(arg: None)

class TreeMapWidgetDefinitionType(arg: ModelComposed)

class TreeMapWidgetDefinitionType(*args, **kwargs)

Bases: ModelSimple

Type of the treemap widget.

Parameters:

• value (str) – If omitted defaults to “treemap”. Must be one of [“treemap”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.tree_map_widget_request module

class TreeMapWidgetRequest(arg: None)

class TreeMapWidgetRequest(arg: ModelComposed)

class TreeMapWidgetRequest(*args, **kwargs)

Bases: ModelNormal

An updated treemap widget.

Parameters:

• formulas ([WidgetFormula], optional) – List of formulas that operate on queries.

• q (str, optional) – The widget metrics query.

• queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.

• response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

datadog_api_client.v1.model.usage_analyzed_logs_hour module

class UsageAnalyzedLogsHour(arg: None)

class UsageAnalyzedLogsHour(arg: ModelComposed)

class UsageAnalyzedLogsHour(*args, **kwargs)

Bases: ModelNormal

The number of analyzed logs for each hour for a given organization.

Parameters:

• analyzed_logs (int, none_type, optional) – Contains the number of analyzed logs.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_analyzed_logs_response module

class UsageAnalyzedLogsResponse(arg: None)

class UsageAnalyzedLogsResponse(arg: ModelComposed)

class UsageAnalyzedLogsResponse(*args, **kwargs)

Bases: ModelNormal

A response containing the number of analyzed logs for each hour for a given organization.

Parameters:

usage ([UsageAnalyzedLogsHour], optional) – Get hourly usage for analyzed logs.

datadog_api_client.v1.model.usage_attribution_aggregates module

class UsageAttributionAggregates(arg: None)

class UsageAttributionAggregates(arg: ModelComposed)

class UsageAttributionAggregates(*args, **kwargs)

Bases: ModelSimple

An array of available aggregates.

Parameters:

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.usage_attribution_aggregates_body module

class UsageAttributionAggregatesBody(arg: None)

class UsageAttributionAggregatesBody(arg: ModelComposed)

class UsageAttributionAggregatesBody(*args, **kwargs)

Bases: ModelNormal

The object containing the aggregates.

Parameters:

• agg_type (str, optional) – The aggregate type.

• field (str, optional) – The field.

• value (float, optional) – The value for a given field.

datadog_api_client.v1.model.usage_attribution_tag_names module

class UsageAttributionTagNames(arg: None)

class UsageAttributionTagNames(arg: ModelComposed)

class UsageAttributionTagNames(*args, **kwargs)

Bases: ModelNormal

Tag keys and values.

A null value here means that the requested tag breakdown cannot be applied because it does not match the tags configured for usage attribution. In this scenario the API returns the total usage, not broken down by tags.

datadog_api_client.v1.model.usage_audit_logs_hour module

class UsageAuditLogsHour(arg: None)

class UsageAuditLogsHour(arg: ModelComposed)

class UsageAuditLogsHour(*args, **kwargs)

Bases: ModelNormal

Audit logs usage for a given organization for a given hour.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• lines_indexed (int, none_type, optional) – The total number of audit logs lines indexed during a given hour.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_audit_logs_response module

class UsageAuditLogsResponse(arg: None)

class UsageAuditLogsResponse(arg: ModelComposed)

class UsageAuditLogsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the audit logs usage for each hour for a given organization.

Parameters:

usage ([UsageAuditLogsHour], optional) – Get hourly usage for audit logs.

datadog_api_client.v1.model.usage_billable_summary_body module

class UsageBillableSummaryBody(arg: None)

class UsageBillableSummaryBody(arg: ModelComposed)

class UsageBillableSummaryBody(*args, **kwargs)

Bases: ModelNormal

Response with properties for each aggregated usage type.

Parameters:

• account_billable_usage (int, optional) – The total account usage.

• account_committed_usage (int, optional) – The total account committed usage.

• account_on_demand_usage (int, optional) – The total account on-demand usage.

• elapsed_usage_hours (int, optional) – Elapsed usage hours for some billable product.

• first_billable_usage_hour (datetime, optional) – The first billable hour for the org.

• last_billable_usage_hour (datetime, optional) – The last billable hour for the org.

• org_billable_usage (int, optional) – The number of units used within the billable timeframe.

• percentage_in_account (float, optional) – The percentage of account usage the org represents.

• usage_unit (str, optional) – Units pertaining to the usage.

datadog_api_client.v1.model.usage_billable_summary_hour module

class UsageBillableSummaryHour(arg: None)

class UsageBillableSummaryHour(arg: ModelComposed)

class UsageBillableSummaryHour(*args, **kwargs)

Bases: ModelNormal

Response with monthly summary of data billed by Datadog.

Parameters:

• account_name (str, optional) – The account name.

• account_public_id (str, optional) – The account public ID.

• billing_plan (str, optional) – The billing plan.

• end_date (datetime, optional) – Shows the last date of usage.

• num_orgs (int, optional) – The number of organizations.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• ratio_in_month (float, optional) – Shows usage aggregation for a billing period.

• region (str, optional) – The region of the organization.

• start_date (datetime, optional) – Shows the first date of usage.

• usage (UsageBillableSummaryKeys, optional) – Response with aggregated usage types.

datadog_api_client.v1.model.usage_billable_summary_keys module

class UsageBillableSummaryKeys(arg: None)

class UsageBillableSummaryKeys(arg: ModelComposed)

class UsageBillableSummaryKeys(*args, **kwargs)

Bases: ModelNormal

Response with aggregated usage types.

Parameters:

• apm_fargate_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• apm_fargate_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• apm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• apm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• apm_profiler_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• apm_profiler_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• apm_trace_search_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• application_security_fargate_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• application_security_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• application_security_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ci_pipeline_indexed_spans_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ci_pipeline_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ci_pipeline_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ci_test_indexed_spans_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ci_testing_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ci_testing_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cloud_cost_management_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cloud_cost_management_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cspm_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cspm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cspm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• custom_event_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cws_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cws_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• cws_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• dbm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• dbm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• dbm_normalized_queries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• dbm_normalized_queries_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• fargate_container_apm_and_profiler_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• fargate_container_apm_and_profiler_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• fargate_container_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• fargate_container_profiler_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• fargate_container_profiler_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• fargate_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• incident_management_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• incident_management_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• infra_and_apm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• infra_and_apm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• infra_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• infra_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• infra_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ingested_spans_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ingested_timeseries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• ingested_timeseries_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• iot_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• iot_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• lambda_function_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• lambda_function_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_forwarding_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_15day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_180day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_1day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_30day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_360day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_3day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_45day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_60day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_7day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_90day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_custom_retention_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_indexed_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• logs_ingested_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• network_device_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• network_device_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• npm_flow_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• npm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• npm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• observability_pipeline_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• online_archive_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• prof_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• prof_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• prof_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• rum_lite_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• rum_replay_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• rum_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• rum_units_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• sensitive_data_scanner_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• serverless_apm_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• serverless_infra_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• serverless_infra_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• serverless_invocation_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• siem_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• standard_timeseries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• synthetics_api_tests_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• synthetics_app_testing_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• synthetics_browser_checks_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• timeseries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

• timeseries_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

datadog_api_client.v1.model.usage_billable_summary_response module

class UsageBillableSummaryResponse(arg: None)

class UsageBillableSummaryResponse(arg: ModelComposed)

class UsageBillableSummaryResponse(*args, **kwargs)

Bases: ModelNormal

Response with monthly summary of data billed by Datadog.

Parameters:

usage ([UsageBillableSummaryHour], optional) – An array of objects regarding usage of billable summary.

datadog_api_client.v1.model.usage_ci_visibility_hour module

class UsageCIVisibilityHour(arg: None)

class UsageCIVisibilityHour(arg: ModelComposed)

class UsageCIVisibilityHour(*args, **kwargs)

Bases: ModelNormal

CI visibility usage in a given hour.

Parameters:

• ci_pipeline_indexed_spans (int, none_type, optional) – The number of spans for pipelines in the queried hour.

• ci_test_indexed_spans (int, none_type, optional) – The number of spans for tests in the queried hour.

• ci_visibility_itr_committers (int, none_type, optional) – Shows the total count of all active Git committers for Intelligent Test Runner in the current month. A committer is active if they commit at least 3 times in a given month.

• ci_visibility_pipeline_committers (int, none_type, optional) – Shows the total count of all active Git committers for Pipelines in the current month. A committer is active if they commit at least 3 times in a given month.

• ci_visibility_test_committers (int, none_type, optional) – The total count of all active Git committers for tests in the current month. A committer is active if they commit at least 3 times in a given month.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_ci_visibility_response module

class UsageCIVisibilityResponse(arg: None)

class UsageCIVisibilityResponse(arg: ModelComposed)

class UsageCIVisibilityResponse(*args, **kwargs)

Bases: ModelNormal

CI visibility usage response

Parameters:

usage ([UsageCIVisibilityHour], optional) – Response containing CI visibility usage.

datadog_api_client.v1.model.usage_cloud_security_posture_management_hour module

class UsageCloudSecurityPostureManagementHour(arg: None)

class UsageCloudSecurityPostureManagementHour(arg: ModelComposed)

class UsageCloudSecurityPostureManagementHour(*args, **kwargs)

Bases: ModelNormal

Cloud Security Management Pro usage for a given organization for a given hour.

Parameters:

• aas_host_count (float, none_type, optional) – The number of Cloud Security Management Pro Azure app services hosts during a given hour.

• aws_host_count (float, none_type, optional) – The number of Cloud Security Management Pro AWS hosts during a given hour.

• azure_host_count (float, none_type, optional) – The number of Cloud Security Management Pro Azure hosts during a given hour.

• compliance_host_count (float, none_type, optional) – The number of Cloud Security Management Pro hosts during a given hour.

• container_count (float, none_type, optional) – The total number of Cloud Security Management Pro containers during a given hour.

• gcp_host_count (float, none_type, optional) – The number of Cloud Security Management Pro GCP hosts during a given hour.

• host_count (float, none_type, optional) – The total number of Cloud Security Management Pro hosts during a given hour.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_cloud_security_posture_management_response module

class UsageCloudSecurityPostureManagementResponse(arg: None)

class UsageCloudSecurityPostureManagementResponse(arg: ModelComposed)

class UsageCloudSecurityPostureManagementResponse(*args, **kwargs)

Bases: ModelNormal

The response containing the Cloud Security Management Pro usage for each hour for a given organization.

Parameters:

usage ([UsageCloudSecurityPostureManagementHour], optional) – Get hourly usage for Cloud Security Management Pro.

datadog_api_client.v1.model.usage_custom_reports_attributes module

class UsageCustomReportsAttributes(arg: None)

class UsageCustomReportsAttributes(arg: ModelComposed)

class UsageCustomReportsAttributes(*args, **kwargs)

Bases: ModelNormal

The response containing attributes for custom reports.

Parameters:

• computed_on (str, optional) – The date the specified custom report was computed.

• end_date (str, optional) – The ending date of custom report.

• size (int, optional) – size

• start_date (str, optional) – The starting date of custom report.

• tags ([str], optional) – A list of tags to apply to custom reports.

datadog_api_client.v1.model.usage_custom_reports_data module

class UsageCustomReportsData(arg: None)

class UsageCustomReportsData(arg: ModelComposed)

class UsageCustomReportsData(*args, **kwargs)

Bases: ModelNormal

The response containing the date and type for custom reports.

Parameters:

• attributes (UsageCustomReportsAttributes, optional) – The response containing attributes for custom reports.

• id (str, optional) – The date for specified custom reports.

• type (UsageReportsType, optional) – The type of reports.

datadog_api_client.v1.model.usage_custom_reports_meta module

class UsageCustomReportsMeta(arg: None)

class UsageCustomReportsMeta(arg: ModelComposed)

class UsageCustomReportsMeta(*args, **kwargs)

Bases: ModelNormal

The object containing document metadata.

Parameters:

page (UsageCustomReportsPage, optional) – The object containing page total count.

datadog_api_client.v1.model.usage_custom_reports_page module

class UsageCustomReportsPage(arg: None)

class UsageCustomReportsPage(arg: ModelComposed)

class UsageCustomReportsPage(*args, **kwargs)

Bases: ModelNormal

The object containing page total count.

Parameters:

total_count (int, optional) – Total page count.

datadog_api_client.v1.model.usage_custom_reports_response module

class UsageCustomReportsResponse(arg: None)

class UsageCustomReportsResponse(arg: ModelComposed)

class UsageCustomReportsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing available custom reports.

Parameters:

• data ([UsageCustomReportsData], optional) – An array of available custom reports.

• meta (UsageCustomReportsMeta, optional) – The object containing document metadata.

datadog_api_client.v1.model.usage_cws_hour module

class UsageCWSHour(arg: None)

class UsageCWSHour(arg: ModelComposed)

class UsageCWSHour(*args, **kwargs)

Bases: ModelNormal

Cloud Workload Security usage for a given organization for a given hour.

Parameters:

• cws_container_count (int, none_type, optional) – The total number of Cloud Workload Security container hours from the start of the given hour’s month until the given hour.

• cws_host_count (int, none_type, optional) – The total number of Cloud Workload Security host hours from the start of the given hour’s month until the given hour.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_cws_response module

class UsageCWSResponse(arg: None)

class UsageCWSResponse(arg: ModelComposed)

class UsageCWSResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the Cloud Workload Security usage for each hour for a given organization.

Parameters:

usage ([UsageCWSHour], optional) – Get hourly usage for Cloud Workload Security.

datadog_api_client.v1.model.usage_dbm_hour module

class UsageDBMHour(arg: None)

class UsageDBMHour(arg: ModelComposed)

class UsageDBMHour(*args, **kwargs)

Bases: ModelNormal

Database Monitoring usage for a given organization for a given hour.

Parameters:

• dbm_host_count (int, none_type, optional) – The total number of Database Monitoring host hours from the start of the given hour’s month until the given hour.

• dbm_queries_count (int, none_type, optional) – The total number of normalized Database Monitoring queries from the start of the given hour’s month until the given hour.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_dbm_response module

class UsageDBMResponse(arg: None)

class UsageDBMResponse(arg: ModelComposed)

class UsageDBMResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the Database Monitoring usage for each hour for a given organization.

Parameters:

usage ([UsageDBMHour], optional) – Get hourly usage for Database Monitoring

datadog_api_client.v1.model.usage_fargate_hour module

class UsageFargateHour(arg: None)

class UsageFargateHour(arg: ModelComposed)

class UsageFargateHour(*args, **kwargs)

Bases: ModelNormal

Number of Fargate tasks run and hourly usage.

Parameters:

• apm_fargate_count (int, none_type, optional) – The high-water mark of APM ECS Fargate tasks during the given hour.

• appsec_fargate_count (int, none_type, optional) – The Application Security Monitoring ECS Fargate tasks during the given hour.

• avg_profiled_fargate_tasks (int, none_type, optional) – The average profiled task count for Fargate Profiling.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• tasks_count (int, none_type, optional) – The number of Fargate tasks run.

datadog_api_client.v1.model.usage_fargate_response module

class UsageFargateResponse(arg: None)

class UsageFargateResponse(arg: ModelComposed)

class UsageFargateResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of Fargate tasks run and hourly usage.

Parameters:

usage ([UsageFargateHour], optional) – Array with the number of hourly Fargate tasks recorded for a given organization.

datadog_api_client.v1.model.usage_host_hour module

class UsageHostHour(arg: None)

class UsageHostHour(arg: ModelComposed)

class UsageHostHour(*args, **kwargs)

Bases: ModelNormal

Number of hosts/containers recorded for each hour for a given organization.

Parameters:

• agent_host_count (int, none_type, optional) – Contains the total number of infrastructure hosts reporting during a given hour that were running the Datadog Agent.

• alibaba_host_count (int, none_type, optional) – Contains the total number of hosts that reported through Alibaba integration (and were NOT running the Datadog Agent).

• apm_azure_app_service_host_count (int, none_type, optional) – Contains the total number of Azure App Services hosts using APM.

• apm_host_count (int, none_type, optional) – Shows the total number of hosts using APM during the hour, these are counted as billable (except during trial periods).

• aws_host_count (int, none_type, optional) – Contains the total number of hosts that reported through the AWS integration (and were NOT running the Datadog Agent).

• azure_host_count (int, none_type, optional) – Contains the total number of hosts that reported through Azure integration (and were NOT running the Datadog Agent).

• container_count (int, none_type, optional) – Shows the total number of containers reported by the Docker integration during the hour.

• gcp_host_count (int, none_type, optional) – Contains the total number of hosts that reported through the Google Cloud integration (and were NOT running the Datadog Agent).

• heroku_host_count (int, none_type, optional) – Contains the total number of Heroku dynos reported by the Datadog Agent.

• host_count (int, none_type, optional) – Contains the total number of billable infrastructure hosts reporting during a given hour. This is the sum of agent_host_count , aws_host_count , and gcp_host_count.

• hour (datetime, none_type, optional) – The hour for the usage.

• infra_azure_app_service (int, none_type, optional) – Contains the total number of hosts that reported through the Azure App Services integration (and were NOT running the Datadog Agent).

• opentelemetry_apm_host_count (int, none_type, optional) – Contains the total number of hosts using APM reported by Datadog exporter for the OpenTelemetry Collector.

• opentelemetry_host_count (int, none_type, optional) – Contains the total number of hosts reported by Datadog exporter for the OpenTelemetry Collector.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• vsphere_host_count (int, none_type, optional) – Contains the total number of hosts that reported through vSphere integration (and were NOT running the Datadog Agent).

datadog_api_client.v1.model.usage_hosts_response module

class UsageHostsResponse(arg: None)

class UsageHostsResponse(arg: ModelComposed)

class UsageHostsResponse(*args, **kwargs)

Bases: ModelNormal

Host usage response.

Parameters:

usage ([UsageHostHour], optional) – An array of objects related to host usage.

datadog_api_client.v1.model.usage_incident_management_hour module

class UsageIncidentManagementHour(arg: None)

class UsageIncidentManagementHour(arg: ModelComposed)

class UsageIncidentManagementHour(*args, **kwargs)

Bases: ModelNormal

Incident management usage for a given organization for a given hour.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• monthly_active_users (int, none_type, optional) – Contains the total number monthly active users from the start of the given hour’s month until the given hour.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_incident_management_response module

class UsageIncidentManagementResponse(arg: None)

class UsageIncidentManagementResponse(arg: ModelComposed)

class UsageIncidentManagementResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the incident management usage for each hour for a given organization.

Parameters:

usage ([UsageIncidentManagementHour], optional) – Get hourly usage for incident management.

datadog_api_client.v1.model.usage_indexed_spans_hour module

class UsageIndexedSpansHour(arg: None)

class UsageIndexedSpansHour(arg: ModelComposed)

class UsageIndexedSpansHour(*args, **kwargs)

Bases: ModelNormal

The hours of indexed spans usage.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• indexed_events_count (int, none_type, optional) – Contains the number of spans indexed.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_indexed_spans_response module

class UsageIndexedSpansResponse(arg: None)

class UsageIndexedSpansResponse(arg: ModelComposed)

class UsageIndexedSpansResponse(*args, **kwargs)

Bases: ModelNormal

A response containing indexed spans usage.

Parameters:

usage ([UsageIndexedSpansHour], optional) – Array with the number of hourly traces indexed for a given organization.

datadog_api_client.v1.model.usage_ingested_spans_hour module

class UsageIngestedSpansHour(arg: None)

class UsageIngestedSpansHour(arg: ModelComposed)

class UsageIngestedSpansHour(*args, **kwargs)

Bases: ModelNormal

Ingested spans usage for a given organization for a given hour.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• ingested_events_bytes (int, none_type, optional) – Contains the total number of bytes ingested for APM spans during a given hour.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_ingested_spans_response module

class UsageIngestedSpansResponse(arg: None)

class UsageIngestedSpansResponse(arg: ModelComposed)

class UsageIngestedSpansResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the ingested spans usage for each hour for a given organization.

Parameters:

usage ([UsageIngestedSpansHour], optional) – Get hourly usage for ingested spans.

datadog_api_client.v1.model.usage_iot_hour module

class UsageIoTHour(arg: None)

class UsageIoTHour(arg: ModelComposed)

class UsageIoTHour(*args, **kwargs)

Bases: ModelNormal

IoT usage for a given organization for a given hour.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• iot_device_count (int, none_type, optional) – The total number of IoT devices during a given hour.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_iot_response module

class UsageIoTResponse(arg: None)

class UsageIoTResponse(arg: ModelComposed)

class UsageIoTResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the IoT usage for each hour for a given organization.

Parameters:

usage ([UsageIoTHour], optional) – Get hourly usage for IoT.

datadog_api_client.v1.model.usage_lambda_hour module

class UsageLambdaHour(arg: None)

class UsageLambdaHour(arg: ModelComposed)

class UsageLambdaHour(*args, **kwargs)

Bases: ModelNormal

Number of Lambda functions and sum of the invocations of all Lambda functions for each hour for a given organization.

Parameters:

• func_count (int, none_type, optional) – Contains the number of different functions for each region and AWS account.

• hour (datetime, optional) – The hour for the usage.

• invocations_sum (int, none_type, optional) – Contains the sum of invocations of all functions.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_lambda_response module

class UsageLambdaResponse(arg: None)

class UsageLambdaResponse(arg: ModelComposed)

class UsageLambdaResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of Lambda functions and sum of the invocations of all Lambda functions for each hour for a given organization.

Parameters:

usage ([UsageLambdaHour], optional) – Get hourly usage for Lambda.

datadog_api_client.v1.model.usage_logs_by_index_hour module

class UsageLogsByIndexHour(arg: None)

class UsageLogsByIndexHour(arg: ModelComposed)

class UsageLogsByIndexHour(*args, **kwargs)

Bases: ModelNormal

Number of indexed logs for each hour and index for a given organization.

Parameters:

• event_count (int, optional) – The total number of indexed logs for the queried hour.

• hour (datetime, optional) – The hour for the usage.

• index_id (str, optional) – The index ID for this usage.

• index_name (str, optional) – The user specified name for this index ID.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• retention (int, optional) – The retention period (in days) for this index ID.

datadog_api_client.v1.model.usage_logs_by_index_response module

class UsageLogsByIndexResponse(arg: None)

class UsageLogsByIndexResponse(arg: ModelComposed)

class UsageLogsByIndexResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of indexed logs for each hour and index for a given organization.

Parameters:

usage ([UsageLogsByIndexHour], optional) – An array of objects regarding hourly usage of logs by index response.

datadog_api_client.v1.model.usage_logs_by_retention_hour module

class UsageLogsByRetentionHour(arg: None)

class UsageLogsByRetentionHour(arg: ModelComposed)

class UsageLogsByRetentionHour(*args, **kwargs)

Bases: ModelNormal

The number of indexed logs for each hour for a given organization broken down by retention period.

Parameters:

• indexed_events_count (int, none_type, optional) – Total logs indexed with this retention period during a given hour.

• live_indexed_events_count (int, none_type, optional) – Live logs indexed with this retention period during a given hour.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• rehydrated_indexed_events_count (int, none_type, optional) – Rehydrated logs indexed with this retention period during a given hour.

• retention (str, none_type, optional) – The retention period in days or “custom” for all custom retention usage.

datadog_api_client.v1.model.usage_logs_by_retention_response module

class UsageLogsByRetentionResponse(arg: None)

class UsageLogsByRetentionResponse(arg: ModelComposed)

class UsageLogsByRetentionResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the indexed logs usage broken down by retention period for an organization during a given hour.

Parameters:

usage ([UsageLogsByRetentionHour], optional) – Get hourly usage for indexed logs by retention period.

datadog_api_client.v1.model.usage_logs_hour module

class UsageLogsHour(arg: None)

class UsageLogsHour(arg: ModelComposed)

class UsageLogsHour(*args, **kwargs)

Bases: ModelNormal

Hour usage for logs.

Parameters:

• billable_ingested_bytes (int, none_type, optional) – Contains the number of billable log bytes ingested.

• hour (datetime, optional) – The hour for the usage.

• indexed_events_count (int, none_type, optional) – Contains the number of log events indexed.

• ingested_events_bytes (int, none_type, optional) – Contains the number of log bytes ingested.

• logs_forwarding_events_bytes (int, none_type, optional) – Contains the number of logs forwarded bytes (data available as of April 1st 2023)

• logs_live_indexed_count (int, none_type, optional) – Contains the number of live log events indexed (data available as of December 1, 2020).

• logs_live_ingested_bytes (int, none_type, optional) – Contains the number of live log bytes ingested (data available as of December 1, 2020).

• logs_rehydrated_indexed_count (int, none_type, optional) – Contains the number of rehydrated log events indexed (data available as of December 1, 2020).

• logs_rehydrated_ingested_bytes (int, none_type, optional) – Contains the number of rehydrated log bytes ingested (data available as of December 1, 2020).

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_logs_response module

class UsageLogsResponse(arg: None)

class UsageLogsResponse(arg: ModelComposed)

class UsageLogsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of logs for each hour.

Parameters:

usage ([UsageLogsHour], optional) – An array of objects regarding hourly usage of logs.

datadog_api_client.v1.model.usage_metric_category module

class UsageMetricCategory(arg: None)

class UsageMetricCategory(arg: ModelComposed)

class UsageMetricCategory(*args, **kwargs)

Bases: ModelSimple

Contains the metric category.

Parameters:

• value (str) – Must be one of [“standard”, “custom”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.usage_network_flows_hour module

class UsageNetworkFlowsHour(arg: None)

class UsageNetworkFlowsHour(arg: ModelComposed)

class UsageNetworkFlowsHour(*args, **kwargs)

Bases: ModelNormal

Number of netflow events indexed for each hour for a given organization.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• indexed_events_count (int, none_type, optional) – Contains the number of netflow events indexed.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_network_flows_response module

class UsageNetworkFlowsResponse(arg: None)

class UsageNetworkFlowsResponse(arg: ModelComposed)

class UsageNetworkFlowsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of netflow events indexed for each hour for a given organization.

Parameters:

usage ([UsageNetworkFlowsHour], optional) – Get hourly usage for Network Flows.

datadog_api_client.v1.model.usage_network_hosts_hour module

class UsageNetworkHostsHour(arg: None)

class UsageNetworkHostsHour(arg: ModelComposed)

class UsageNetworkHostsHour(*args, **kwargs)

Bases: ModelNormal

Number of active NPM hosts for each hour for a given organization.

Parameters:

• host_count (int, none_type, optional) – Contains the number of active NPM hosts.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_network_hosts_response module

class UsageNetworkHostsResponse(arg: None)

class UsageNetworkHostsResponse(arg: ModelComposed)

class UsageNetworkHostsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of active NPM hosts for each hour for a given organization.

Parameters:

usage ([UsageNetworkHostsHour], optional) – Get hourly usage for NPM hosts.

datadog_api_client.v1.model.usage_online_archive_hour module

class UsageOnlineArchiveHour(arg: None)

class UsageOnlineArchiveHour(arg: ModelComposed)

class UsageOnlineArchiveHour(*args, **kwargs)

Bases: ModelNormal

Online Archive usage in a given hour.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• online_archive_events_count (int, none_type, optional) – Total count of online archived events within the hour.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_online_archive_response module

class UsageOnlineArchiveResponse(arg: None)

class UsageOnlineArchiveResponse(arg: ModelComposed)

class UsageOnlineArchiveResponse(*args, **kwargs)

Bases: ModelNormal

Online Archive usage response.

Parameters:

usage ([UsageOnlineArchiveHour], optional) – Response containing Online Archive usage.

datadog_api_client.v1.model.usage_profiling_hour module

class UsageProfilingHour(arg: None)

class UsageProfilingHour(arg: ModelComposed)

class UsageProfilingHour(*args, **kwargs)

Bases: ModelNormal

The number of profiled hosts for each hour for a given organization.

Parameters:

• aas_count (int, none_type, optional) – Contains the total number of profiled Azure app services reporting during a given hour.

• avg_container_agent_count (int, none_type, optional) – Get average number of container agents for that hour.

• host_count (int, none_type, optional) – Contains the total number of profiled hosts reporting during a given hour.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_profiling_response module

class UsageProfilingResponse(arg: None)

class UsageProfilingResponse(arg: ModelComposed)

class UsageProfilingResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of profiled hosts for each hour for a given organization.

Parameters:

usage ([UsageProfilingHour], optional) – Get hourly usage for profiled hosts.

datadog_api_client.v1.model.usage_reports_type module

class UsageReportsType(arg: None)

class UsageReportsType(arg: ModelComposed)

class UsageReportsType(*args, **kwargs)

Bases: ModelSimple

The type of reports.

Parameters:

• value (str) – If omitted defaults to “reports”. Must be one of [“reports”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.usage_rum_sessions_hour module

class UsageRumSessionsHour(arg: None)

class UsageRumSessionsHour(arg: ModelComposed)

class UsageRumSessionsHour(*args, **kwargs)

Bases: ModelNormal

Number of RUM sessions recorded for each hour for a given organization.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• replay_session_count (int, optional) – Contains the number of RUM Session Replay counts (data available beginning November 1, 2021).

• session_count (int, none_type, optional) – Contains the number of browser RUM lite Sessions.

• session_count_android (int, none_type, optional) – Contains the number of mobile RUM sessions on Android (data available beginning December 1, 2020).

• session_count_flutter (int, none_type, optional) – Contains the number of mobile RUM sessions on Flutter (data available beginning March 1, 2023).

• session_count_ios (int, none_type, optional) – Contains the number of mobile RUM sessions on iOS (data available beginning December 1, 2020).

• session_count_reactnative (int, none_type, optional) – Contains the number of mobile RUM sessions on React Native (data available beginning May 1, 2022).

datadog_api_client.v1.model.usage_rum_sessions_response module

class UsageRumSessionsResponse(arg: None)

class UsageRumSessionsResponse(arg: ModelComposed)

class UsageRumSessionsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of RUM sessions for each hour for a given organization.

Parameters:

usage ([UsageRumSessionsHour], optional) – Get hourly usage for RUM sessions.

datadog_api_client.v1.model.usage_rum_units_hour module

class UsageRumUnitsHour(arg: None)

class UsageRumUnitsHour(arg: ModelComposed)

class UsageRumUnitsHour(*args, **kwargs)

Bases: ModelNormal

Number of RUM Units used for each hour for a given organization (data available as of November 1, 2021).

Parameters:

• browser_rum_units (int, none_type, optional) – The number of browser RUM units.

• mobile_rum_units (int, none_type, optional) – The number of mobile RUM units.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• rum_units (int, none_type, optional) – Total RUM units across mobile and browser RUM.

datadog_api_client.v1.model.usage_rum_units_response module

class UsageRumUnitsResponse(arg: None)

class UsageRumUnitsResponse(arg: ModelComposed)

class UsageRumUnitsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of RUM Units for each hour for a given organization.

Parameters:

usage ([UsageRumUnitsHour], optional) – Get hourly usage for RUM Units.

datadog_api_client.v1.model.usage_sds_hour module

class UsageSDSHour(arg: None)

class UsageSDSHour(arg: ModelComposed)

class UsageSDSHour(*args, **kwargs)

Bases: ModelNormal

Sensitive Data Scanner usage for a given organization for a given hour.

Parameters:

• apm_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of APM usage across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.

• events_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of Events usage across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.

• hour (datetime, optional) – The hour for the usage.

• logs_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of logs usage by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• rum_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of RUM usage across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.

• total_scanned_bytes (int, none_type, optional) – The total number of bytes scanned across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.

datadog_api_client.v1.model.usage_sds_response module

class UsageSDSResponse(arg: None)

class UsageSDSResponse(arg: ModelComposed)

class UsageSDSResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the Sensitive Data Scanner usage for each hour for a given organization.

Parameters:

usage ([UsageSDSHour], optional) – Get hourly usage for Sensitive Data Scanner.

datadog_api_client.v1.model.usage_snmp_hour module

class UsageSNMPHour(arg: None)

class UsageSNMPHour(arg: ModelComposed)

class UsageSNMPHour(*args, **kwargs)

Bases: ModelNormal

The number of SNMP devices for each hour for a given organization.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

• snmp_devices (int, none_type, optional) – Contains the number of SNMP devices.

datadog_api_client.v1.model.usage_snmp_response module

class UsageSNMPResponse(arg: None)

class UsageSNMPResponse(arg: ModelComposed)

class UsageSNMPResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of SNMP devices for each hour for a given organization.

Parameters:

usage ([UsageSNMPHour], optional) – Get hourly usage for SNMP devices.

datadog_api_client.v1.model.usage_sort module

class UsageSort(arg: None)

class UsageSort(arg: ModelComposed)

class UsageSort(*args, **kwargs)

Bases: ModelSimple

The field to sort by.

Parameters:

• value (str) – If omitted defaults to “start_date”. Must be one of [“computed_on”, “size”, “start_date”, “end_date”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.usage_sort_direction module

class UsageSortDirection(arg: None)

class UsageSortDirection(arg: ModelComposed)

class UsageSortDirection(*args, **kwargs)

Bases: ModelSimple

The direction to sort by.

Parameters:

• value (str) – If omitted defaults to “desc”. Must be one of [“desc”, “asc”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.usage_specified_custom_reports_attributes module

class UsageSpecifiedCustomReportsAttributes(arg: None)

class UsageSpecifiedCustomReportsAttributes(arg: ModelComposed)

class UsageSpecifiedCustomReportsAttributes(*args, **kwargs)

Bases: ModelNormal

The response containing attributes for specified custom reports.

Parameters:

• computed_on (str, optional) – The date the specified custom report was computed.

• end_date (str, optional) – The ending date of specified custom report.

• location (str, optional) – A downloadable file for the specified custom reporting file.

• size (int, optional) – size

• start_date (str, optional) – The starting date of specified custom report.

• tags ([str], optional) – A list of tags to apply to specified custom reports.

datadog_api_client.v1.model.usage_specified_custom_reports_data module

class UsageSpecifiedCustomReportsData(arg: None)

class UsageSpecifiedCustomReportsData(arg: ModelComposed)

class UsageSpecifiedCustomReportsData(*args, **kwargs)

Bases: ModelNormal

Response containing date and type for specified custom reports.

Parameters:

• attributes (UsageSpecifiedCustomReportsAttributes, optional) – The response containing attributes for specified custom reports.

• id (str, optional) – The date for specified custom reports.

• type (UsageReportsType, optional) – The type of reports.

datadog_api_client.v1.model.usage_specified_custom_reports_meta module

class UsageSpecifiedCustomReportsMeta(arg: None)

class UsageSpecifiedCustomReportsMeta(arg: ModelComposed)

class UsageSpecifiedCustomReportsMeta(*args, **kwargs)

Bases: ModelNormal

The object containing document metadata.

Parameters:

page (UsageSpecifiedCustomReportsPage, optional) – The object containing page total count for specified ID.

datadog_api_client.v1.model.usage_specified_custom_reports_page module

class UsageSpecifiedCustomReportsPage(arg: None)

class UsageSpecifiedCustomReportsPage(arg: ModelComposed)

class UsageSpecifiedCustomReportsPage(*args, **kwargs)

Bases: ModelNormal

The object containing page total count for specified ID.

Parameters:

total_count (int, optional) – Total page count.

datadog_api_client.v1.model.usage_specified_custom_reports_response module

class UsageSpecifiedCustomReportsResponse(arg: None)

class UsageSpecifiedCustomReportsResponse(arg: ModelComposed)

class UsageSpecifiedCustomReportsResponse(*args, **kwargs)

Bases: ModelNormal

Returns available specified custom reports.

Parameters:

• data (UsageSpecifiedCustomReportsData, optional) – Response containing date and type for specified custom reports.

• meta (UsageSpecifiedCustomReportsMeta, optional) – The object containing document metadata.

datadog_api_client.v1.model.usage_summary_date module

class UsageSummaryDate(arg: None)

class UsageSummaryDate(arg: ModelComposed)

class UsageSummaryDate(*args, **kwargs)

Bases: ModelNormal

Response with hourly report of all data billed by Datadog all organizations.

Parameters:

• agent_host_top99p (int, optional) – Shows the 99th percentile of all agent hosts over all hours in the current date for all organizations.

• apm_azure_app_service_host_top99p (int, optional) – Shows the 99th percentile of all Azure app services using APM over all hours in the current date all organizations.

• apm_devsecops_host_top99p (int, optional) – Shows the 99th percentile of all APM DevSecOps hosts over all hours in the current date for the given org.

• apm_fargate_count_avg (int, optional) – Shows the average of all APM ECS Fargate tasks over all hours in the current date for all organizations.

• apm_host_top99p (int, optional) – Shows the 99th percentile of all distinct APM hosts over all hours in the current date for all organizations.

• appsec_fargate_count_avg (int, optional) – Shows the average of all Application Security Monitoring ECS Fargate tasks over all hours in the current date for all organizations.

• asm_serverless_sum (int, optional) – Shows the sum of all Application Security Monitoring Serverless invocations over all hours in the current date for all organizations.

• audit_logs_lines_indexed_sum (int, optional) – Shows the sum of audit logs lines indexed over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• audit_trail_enabled_hwm (int, optional) – Shows the number of organizations that had Audit Trail enabled in the current date.

• avg_profiled_fargate_tasks (int, optional) – The average total count for Fargate Container Profiler over all hours in the current date for all organizations.

• aws_host_top99p (int, optional) – Shows the 99th percentile of all AWS hosts over all hours in the current date for all organizations.

• aws_lambda_func_count (int, optional) – Shows the average of the number of functions that executed 1 or more times each hour in the current date for all organizations.

• aws_lambda_invocations_sum (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current date for all organizations.

• azure_app_service_top99p (int, optional) – Shows the 99th percentile of all Azure app services over all hours in the current date for all organizations.

• billable_ingested_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for all organizations.

• browser_rum_lite_session_count_sum (int, optional) – Shows the sum of all browser lite sessions over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• browser_rum_replay_session_count_sum (int, optional) – Shows the sum of all browser replay sessions over all hours in the current date for all organizations (To be deprecated on October 1st, 2024).

• browser_rum_units_sum (int, optional) – Shows the sum of all browser RUM units over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• ci_pipeline_indexed_spans_sum (int, optional) – Shows the sum of all CI pipeline indexed spans over all hours in the current month for all organizations.

• ci_test_indexed_spans_sum (int, optional) – Shows the sum of all CI test indexed spans over all hours in the current month for all organizations.

• ci_visibility_itr_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility intelligent test runner committers over all hours in the current month for all organizations.

• ci_visibility_pipeline_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility pipeline committers over all hours in the current month for all organizations.

• ci_visibility_test_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility test committers over all hours in the current month for all organizations.

• cloud_cost_management_aws_host_count_avg (int, optional) – Host count average of Cloud Cost Management for AWS for the given date and given organization.

• cloud_cost_management_azure_host_count_avg (int, optional) – Host count average of Cloud Cost Management for Azure for the given date and given organization.

• cloud_cost_management_gcp_host_count_avg (int, optional) – Host count average of Cloud Cost Management for GCP for the given date and given organization.

• cloud_cost_management_host_count_avg (int, optional) – Host count average of Cloud Cost Management for all cloud providers for the given date and given organization.

• cloud_siem_events_sum (int, optional) – Shows the sum of all Cloud Security Information and Event Management events over all hours in the current date for the given org.

• code_analysis_sa_committers_hwm (int, optional) – Shows the high-water mark of all Static Analysis committers over all hours in the current date for the given org.

• code_analysis_sca_committers_hwm (int, optional) – Shows the high-water mark of all static Software Composition Analysis committers over all hours in the current date for the given org.

• code_security_host_top99p (int, optional) – Shows the 99th percentile of all Code Security hosts over all hours in the current date for the given org.

• container_avg (int, optional) – Shows the average of all distinct containers over all hours in the current date for all organizations.

• container_excl_agent_avg (int, optional) – Shows the average of containers without the Datadog Agent over all hours in the current date for all organizations.

• container_hwm (int, optional) – Shows the high-water mark of all distinct containers over all hours in the current date for all organizations.

• csm_container_enterprise_compliance_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise compliance containers over all hours in the current date for the given org.

• csm_container_enterprise_cws_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise Cloud Workload Security containers over all hours in the current date for the given org.

• csm_container_enterprise_total_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise containers over all hours in the current date for the given org.

• csm_host_enterprise_aas_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure app services hosts over all hours in the current date for the given org.

• csm_host_enterprise_aws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise AWS hosts over all hours in the current date for the given org.

• csm_host_enterprise_azure_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure hosts over all hours in the current date for the given org.

• csm_host_enterprise_compliance_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise compliance hosts over all hours in the current date for the given org.

• csm_host_enterprise_cws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Cloud Workload Security hosts over all hours in the current date for the given org.

• csm_host_enterprise_gcp_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise GCP hosts over all hours in the current date for the given org.

• csm_host_enterprise_total_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise hosts over all hours in the current date for the given org.

• cspm_aas_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure app services hosts over all hours in the current date for all organizations.

• cspm_aws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro AWS hosts over all hours in the current date for all organizations.

• cspm_azure_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure hosts over all hours in the current date for all organizations.

• cspm_container_avg (int, optional) – Shows the average number of Cloud Security Management Pro containers over all hours in the current date for all organizations.

• cspm_container_hwm (int, optional) – Shows the high-water mark of Cloud Security Management Pro containers over all hours in the current date for all organizations.

• cspm_gcp_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro GCP hosts over all hours in the current date for all organizations.

• cspm_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro hosts over all hours in the current date for all organizations.

• custom_ts_avg (int, optional) – Shows the average number of distinct custom metrics over all hours in the current date for all organizations.

• cws_container_count_avg (int, optional) – Shows the average of all distinct Cloud Workload Security containers over all hours in the current date for all organizations.

• cws_fargate_task_avg (int, optional) – Shows the average of all distinct Cloud Workload Security Fargate tasks over all hours in the current date for all organizations.

• cws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Workload Security hosts over all hours in the current date for all organizations.

• data_jobs_monitoring_host_hr_sum (int, optional) – Shows the sum of all Data Jobs Monitoring hosts over all hours in the current date for the given org.

• date (datetime, optional) – The date for the usage.

• dbm_host_top99p (int, optional) – Shows the 99th percentile of all Database Monitoring hosts over all hours in the current date for all organizations.

• dbm_queries_count_avg (int, optional) – Shows the average of all normalized Database Monitoring queries over all hours in the current date for all organizations.

• eph_infra_host_agent_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with the Datadog Agent over all hours in the current date for the given org.

• eph_infra_host_alibaba_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Alibaba over all hours in the current date for the given org.

• eph_infra_host_aws_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on AWS over all hours in the current date for the given org.

• eph_infra_host_azure_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Azure over all hours in the current date for the given org.

• eph_infra_host_ent_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Enterprise over all hours in the current date for the given org.

• eph_infra_host_gcp_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on GCP over all hours in the current date for the given org.

• eph_infra_host_heroku_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Heroku over all hours in the current date for the given org.

• eph_infra_host_only_aas_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with only Azure App Services over all hours in the current date for the given org.

• eph_infra_host_only_vsphere_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with only vSphere over all hours in the current date for the given org.

• eph_infra_host_opentelemetry_apm_sum (int, optional) – Shows the sum of all ephemeral APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.

• eph_infra_host_opentelemetry_sum (int, optional) – Shows the sum of all ephemeral hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.

• eph_infra_host_pro_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Pro over all hours in the current date for the given org.

• eph_infra_host_proplus_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Pro Plus over all hours in the current date for the given org.

• error_tracking_apm_error_events_sum (int, optional) – Shows the sum of all Error Tracking APM error events over all hours in the current date for the given org.

• error_tracking_error_events_sum (int, optional) – Shows the sum of all Error Tracking error events over all hours in the current date for the given org.

• error_tracking_events_sum (int, optional) – Shows the sum of all Error Tracking events over all hours in the current date for the given org.

• error_tracking_rum_error_events_sum (int, optional) – Shows the sum of all Error Tracking RUM error events over all hours in the current date for the given org.

• event_management_correlation_correlated_events_sum (int, optional) – Shows the sum of all Event Management correlated events over all hours in the current date for all organizations.

• event_management_correlation_correlated_related_events_sum (int, optional) – Shows the sum of all Event Management correlated related events over all hours in the current date for all organizations.

• event_management_correlation_sum (int, optional) – Shows the sum of all Event Management correlations over all hours in the current date for all organizations.

• fargate_container_profiler_profiling_fargate_avg (int, optional) – The average number of Profiling Fargate tasks over all hours in the current date for all organizations.

• fargate_container_profiler_profiling_fargate_eks_avg (int, optional) – The average number of Profiling Fargate Elastic Kubernetes Service tasks over all hours in the current date for all organizations.

• fargate_tasks_count_avg (int, optional) – Shows the high-watermark of all Fargate tasks over all hours in the current date for all organizations.

• fargate_tasks_count_hwm (int, optional) – Shows the average of all Fargate tasks over all hours in the current date for all organizations.

• flex_logs_compute_large_avg (int, optional) – Shows the average number of Flex Logs Compute Large Instances over all hours in the current date for the given org.

• flex_logs_compute_medium_avg (int, optional) – Shows the average number of Flex Logs Compute Medium Instances over all hours in the current date for the given org.

• flex_logs_compute_small_avg (int, optional) – Shows the average number of Flex Logs Compute Small Instances over all hours in the current date for the given org.

• flex_logs_compute_xlarge_avg (int, optional) – Shows the average number of Flex Logs Compute Extra Large Instances over all hours in the current date for the given org.

• flex_logs_compute_xsmall_avg (int, optional) – Shows the average number of Flex Logs Compute Extra Small Instances over all hours in the current date for the given org.

• flex_logs_starter_avg (int, optional) – Shows the average number of Flex Logs Starter Instances over all hours in the current date for the given org.

• flex_logs_starter_storage_index_avg (int, optional) – Shows the average number of Flex Logs Starter Storage Index Instances over all hours in the current date for the given org.

• flex_logs_starter_storage_retention_adjustment_avg (int, optional) – Shows the average number of Flex Logs Starter Storage Retention Adjustment Instances over all hours in the current date for the given org.

• flex_stored_logs_avg (int, optional) – Shows the average of all Flex Stored Logs over all hours in the current date for the given org.

• forwarding_events_bytes_sum (int, optional) – Shows the sum of all log bytes forwarded over all hours in the current date for all organizations.

• gcp_host_top99p (int, optional) – Shows the 99th percentile of all GCP hosts over all hours in the current date for all organizations.

• heroku_host_top99p (int, optional) – Shows the 99th percentile of all Heroku dynos over all hours in the current date for all organizations.

• incident_management_monthly_active_users_hwm (int, optional) – Shows the high-water mark of incident management monthly active users over all hours in the current date for all organizations.

• indexed_events_count_sum (int, optional) – Shows the sum of all log events indexed over all hours in the current date for all organizations.

• infra_host_top99p (int, optional) – Shows the 99th percentile of all distinct infrastructure hosts over all hours in the current date for all organizations.

• ingested_events_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for all organizations.

• iot_device_sum (int, optional) – Shows the sum of all IoT devices over all hours in the current date for all organizations.

• iot_device_top99p (int, optional) – Shows the 99th percentile of all IoT devices over all hours in the current date all organizations.

• llm_observability_min_spend_sum (int, optional) – Sum of all LLM observability minimum spend over all hours in the current date for all organizations.

• llm_observability_sum (int, optional) – Sum of all LLM observability sessions over all hours in the current date for all organizations.

• mobile_rum_lite_session_count_sum (int, optional) – Shows the sum of all mobile lite sessions over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM sessions on Android over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM sessions on Flutter over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM sessions on iOS over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM sessions on React Native over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM sessions on Roku over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_sum (int, optional) – Shows the sum of all mobile RUM sessions over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_units_sum (int, optional) – Shows the sum of all mobile RUM units over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• ndm_netflow_events_sum (int, optional) – Shows the sum of all Network Device Monitoring NetFlow events over all hours in the current date for the given org.

• netflow_indexed_events_count_sum (int, optional) – Shows the sum of all Network flows indexed over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• network_device_wireless_top99p (int, optional) – Shows the 99th percentile of all Network Device Monitoring wireless devices over all hours in the current date for all organizations.

• npm_host_top99p (int, optional) – Shows the 99th percentile of all distinct Cloud Network Monitoring hosts (formerly known as Network hosts) over all hours in the current date for all organizations.

• observability_pipelines_bytes_processed_sum (int, optional) – Sum of all observability pipelines bytes processed over all hours in the current date for the given org.

• oci_host_sum (int, optional) – Shows the sum of all Oracle Cloud Infrastructure hosts over all hours in the current date for the given org.

• oci_host_top99p (int, optional) – Shows the 99th percentile of all Oracle Cloud Infrastructure hosts over all hours in the current date for the given org.

• online_archive_events_count_sum (int, optional) – Sum of all online archived events over all hours in the current date for all organizations.

• opentelemetry_apm_host_top99p (int, optional) – Shows the 99th percentile of APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for all organizations.

• opentelemetry_host_top99p (int, optional) – Shows the 99th percentile of all hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for all organizations.

• orgs ([UsageSummaryDateOrg], optional) – Organizations associated with a user.

• product_analytics_sum (int, optional) – Sum of all product analytics sessions over all hours in the current date for all organizations.

• profiling_aas_count_top99p (int, optional) – Shows the 99th percentile of all profiled Azure app services over all hours in the current date for all organizations.

• profiling_host_top99p (int, optional) – Shows the 99th percentile of all profiled hosts over all hours within the current date for all organizations.

• published_app_hwm (int, optional) – Shows the high-water mark of all published applications over all hours in the current date for all organizations.

• rum_browser_and_mobile_session_count (int, optional) – Shows the sum of all mobile sessions and all browser lite and legacy sessions over all hours in the current month for all organizations (To be deprecated on October 1st, 2024).

• rum_browser_legacy_session_count_sum (int, optional) – Shows the sum of all browser RUM legacy sessions over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_browser_lite_session_count_sum (int, optional) – Shows the sum of all browser RUM lite sessions over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_browser_replay_session_count_sum (int, optional) – Shows the sum of all browser RUM Session Replay counts over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_indexed_sessions_sum (int, optional) – Sum of all RUM indexed sessions over all hours in the current date for all organizations.

• rum_ingested_sessions_sum (int, optional) – Sum of all RUM ingested sessions over all hours in the current date for all organizations.

• rum_lite_session_count_sum (int, optional) – Shows the sum of all RUM lite sessions (browser and mobile) over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Android over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM legacy Sessions on Flutter over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on iOS over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on React Native over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Roku over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Android over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Flutter over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on iOS over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_kotlinmultiplatform_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Kotlin Multiplatform over all hours within the current date for all organizations.

• rum_mobile_lite_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on React Native over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Roku over all hours within the current date for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_unity_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Unity over all hours within the current date for all organizations.

• rum_mobile_replay_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on Android over all hours within the current date for the given org.

• rum_mobile_replay_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on iOS over all hours within the current date for the given org.

• rum_mobile_replay_session_count_kotlinmultiplatform_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on Kotlin Multiplatform over all hours within the current date for all organizations.

• rum_mobile_replay_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on React Native over all hours within the current date for the given org.

• rum_replay_session_count_sum (int, optional) – Shows the sum of all RUM Session Replay counts over all hours in the current date for all organizations (To be introduced on October 1st, 2024).

• rum_session_count_sum (int, optional) – Shows the sum of all browser RUM lite sessions over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• rum_session_replay_add_on_sum (int, optional) – Sum of all RUM session replay add-on sessions over all hours in the current date for all organizations.

• rum_total_session_count_sum (int, optional) – Shows the sum of RUM sessions (browser and mobile) over all hours in the current date for all organizations.

• rum_units_sum (int, optional) – Shows the sum of all browser and mobile RUM units over all hours in the current date for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• sca_fargate_count_avg (int, optional) – Shows the average of all Software Composition Analysis Fargate tasks over all hours in the current date for the given org.

• sca_fargate_count_hwm (int, optional) – Shows the sum of the high-water marks of all Software Composition Analysis Fargate tasks over all hours in the current date for the given org.

• sds_apm_scanned_bytes_sum (int, optional) – Sum of all APM bytes scanned with sensitive data scanner over all hours in the current date for all organizations.

• sds_events_scanned_bytes_sum (int, optional) – Sum of all event stream events bytes scanned with sensitive data scanner over all hours in the current date for all organizations.

• sds_logs_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned of logs usage by the Sensitive Data Scanner over all hours in the current month for all organizations.

• sds_rum_scanned_bytes_sum (int, optional) – Sum of all RUM bytes scanned with sensitive data scanner over all hours in the current date for all organizations.

• sds_total_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned across all usage types by the Sensitive Data Scanner over all hours in the current month for all organizations.

• serverless_apps_apm_apm_azure_appservice_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Azure App Service instances for the current date for all organizations.

• serverless_apps_apm_apm_azure_azurefunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Azure Function instances for the current date for all organizations.

• serverless_apps_apm_apm_azure_containerapp_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Azure Container App instances for the current date for all organizations.

• serverless_apps_apm_apm_fargate_ecs_tasks_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Fargate Elastic Container Service tasks for the current date for all organizations.

• serverless_apps_apm_apm_gcp_cloudfunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Google Cloud Platform Cloud Function instances for the current date for all organizations.

• serverless_apps_apm_apm_gcp_cloudrun_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Google Cloud Platform Cloud Run instances for the current date for all organizations.

• serverless_apps_apm_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for the current date for all organizations.

• serverless_apps_apm_excl_fargate_apm_azure_appservice_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure App Service instances for the current date for all organizations.

• serverless_apps_apm_excl_fargate_apm_azure_azurefunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure Function instances for the current date for all organizations.

• serverless_apps_apm_excl_fargate_apm_azure_containerapp_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure Container App instances for the current date for all organizations.

• serverless_apps_apm_excl_fargate_apm_gcp_cloudfunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Google Cloud Platform Cloud Function instances for the current date for all organizations.

• serverless_apps_apm_excl_fargate_apm_gcp_cloudrun_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Google Cloud Platform Cloud Run instances for the current date for all organizations.

• serverless_apps_apm_excl_fargate_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for the current date for all organizations.

• serverless_apps_azure_container_app_instances_avg (int, optional) – Shows the average number of Serverless Apps for Azure Container App instances for the current date for all organizations.

• serverless_apps_azure_count_avg (int, optional) – Shows the average number of Serverless Apps for Azure for the given date and given org.

• serverless_apps_azure_function_app_instances_avg (int, optional) – Shows the average number of Serverless Apps for Azure Function App instances for the current date for all organizations.

• serverless_apps_azure_web_app_instances_avg (int, optional) – Shows the average number of Serverless Apps for Azure Web App instances for the current date for all organizations.

• serverless_apps_ecs_avg (int, optional) – Shows the average number of Serverless Apps for Elastic Container Service for the current date for all organizations.

• serverless_apps_eks_avg (int, optional) – Shows the average number of Serverless Apps for Elastic Kubernetes Service for the current date for all organizations.

• serverless_apps_excl_fargate_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for the current date for all organizations.

• serverless_apps_excl_fargate_azure_container_app_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Azure Container App instances for the current date for all organizations.

• serverless_apps_excl_fargate_azure_function_app_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Azure Function App instances for the current date for all organizations.

• serverless_apps_excl_fargate_azure_web_app_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Azure Web App instances for the current date for all organizations.

• serverless_apps_excl_fargate_google_cloud_functions_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Google Cloud Platform Cloud Functions instances for the current date for all organizations.

• serverless_apps_excl_fargate_google_cloud_run_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Google Cloud Platform Cloud Run instances for the current date for all organizations.

• serverless_apps_google_cloud_functions_instances_avg (int, optional) – Shows the average number of Serverless Apps for Google Cloud Platform Cloud Functions instances for the current date for all organizations.

• serverless_apps_google_cloud_run_instances_avg (int, optional) – Shows the average number of Serverless Apps for Google Cloud Platform Cloud Run instances for the current date for all organizations.

• serverless_apps_google_count_avg (int, optional) – Shows the average number of Serverless Apps for Google Cloud for the given date and given org.

• serverless_apps_total_count_avg (int, optional) – Shows the average number of Serverless Apps for Azure and Google Cloud for the given date and given org.

• siem_analyzed_logs_add_on_count_sum (int, optional) – Shows the sum of all log events analyzed by Cloud SIEM over all hours in the current date for the given org.

• synthetics_browser_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic browser tests over all hours in the current date for all organizations.

• synthetics_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic API tests over all hours in the current date for all organizations.

• synthetics_mobile_test_runs_sum (int, optional) – Shows the sum of all Synthetic mobile application tests over all hours in the current date for all organizations.

• synthetics_parallel_testing_max_slots_hwm (int, optional) – Shows the high-water mark of used synthetics parallel testing slots over all hours in the current date for all organizations.

• trace_search_indexed_events_count_sum (int, optional) – Shows the sum of all Indexed Spans indexed over all hours in the current date for all organizations.

• twol_ingested_events_bytes_sum (int, optional) – Shows the sum of all ingested APM span bytes over all hours in the current date for all organizations.

• universal_service_monitoring_host_top99p (int, optional) – Shows the 99th percentile of all universal service management hosts over all hours in the current date for the given org.

• vsphere_host_top99p (int, optional) – Shows the 99th percentile of all vSphere hosts over all hours in the current date for all organizations.

• vuln_management_host_count_top99p (int, optional) – Shows the 99th percentile of all Application Vulnerability Management hosts over all hours in the current date for the given org.

• workflow_executions_usage_sum (int, optional) – Sum of all workflows executed over all hours in the current date for all organizations.

datadog_api_client.v1.model.usage_summary_date_org module

class UsageSummaryDateOrg(arg: None)

class UsageSummaryDateOrg(arg: ModelComposed)

class UsageSummaryDateOrg(*args, **kwargs)

Bases: ModelNormal

Global hourly report of all data billed by Datadog for a given organization.

Parameters:

• account_name (str, optional) – The account name.

• account_public_id (str, optional) – The account public id.

• agent_host_top99p (int, optional) – Shows the 99th percentile of all agent hosts over all hours in the current date for the given org.

• apm_azure_app_service_host_top99p (int, optional) – Shows the 99th percentile of all Azure app services using APM over all hours in the current date for the given org.

• apm_devsecops_host_top99p (int, optional) – Shows the 99th percentile of all APM DevSecOps hosts over all hours in the current date for the given org.

• apm_fargate_count_avg (int, optional) – Shows the average of all APM ECS Fargate tasks over all hours in the current month for the given org.

• apm_host_top99p (int, optional) – Shows the 99th percentile of all distinct APM hosts over all hours in the current date for the given org.

• appsec_fargate_count_avg (int, optional) – Shows the average of all Application Security Monitoring ECS Fargate tasks over all hours in the current month for the given org.

• asm_serverless_sum (int, optional) – Shows the sum of all Application Security Monitoring Serverless invocations over all hours in the current month for the given org.

• audit_logs_lines_indexed_sum (int, optional) – Shows the sum of all audit logs lines indexed over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• audit_trail_enabled_hwm (int, optional) – Shows whether Audit Trail is enabled for the current date for the given org.

• avg_profiled_fargate_tasks (int, optional) – The average total count for Fargate Container Profiler over all hours in the current month for the given org.

• aws_host_top99p (int, optional) – Shows the 99th percentile of all AWS hosts over all hours in the current date for the given org.

• aws_lambda_func_count (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current date for the given org.

• aws_lambda_invocations_sum (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current date for the given org.

• azure_app_service_top99p (int, optional) – Shows the 99th percentile of all Azure app services over all hours in the current date for the given org.

• billable_ingested_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for the given org.

• browser_rum_lite_session_count_sum (int, optional) – Shows the sum of all browser lite sessions over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• browser_rum_replay_session_count_sum (int, optional) – Shows the sum of all browser replay sessions over all hours in the current date for the given org (To be deprecated on October 1st, 2024).

• browser_rum_units_sum (int, optional) – Shows the sum of all browser RUM units over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• ci_pipeline_indexed_spans_sum (int, optional) – Shows the sum of all CI pipeline indexed spans over all hours in the current date for the given org.

• ci_test_indexed_spans_sum (int, optional) – Shows the sum of all CI test indexed spans over all hours in the current date for the given org.

• ci_visibility_itr_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility intelligent test runner committers over all hours in the current date for the given org.

• ci_visibility_pipeline_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility pipeline committers over all hours in the current date for the given org.

• ci_visibility_test_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility test committers over all hours in the current date for the given org.

• cloud_cost_management_aws_host_count_avg (int, optional) – Host count average of Cloud Cost Management for AWS for the given date and given org.

• cloud_cost_management_azure_host_count_avg (int, optional) – Host count average of Cloud Cost Management for Azure for the given date and given org.

• cloud_cost_management_gcp_host_count_avg (int, optional) – Host count average of Cloud Cost Management for GCP for the given date and given org.

• cloud_cost_management_host_count_avg (int, optional) – Host count average of Cloud Cost Management for all cloud providers for the given date and given org.

• cloud_siem_events_sum (int, optional) – Shows the sum of all Cloud Security Information and Event Management events over all hours in the current date for the given org.

• code_analysis_sa_committers_hwm (int, optional) – Shows the high-water mark of all Static Analysis committers over all hours in the current date for the given org.

• code_analysis_sca_committers_hwm (int, optional) – Shows the high-water mark of all static Software Composition Analysis committers over all hours in the current date for the given org.

• code_security_host_top99p (int, optional) – Shows the 99th percentile of all Code Security hosts over all hours in the current date for the given org.

• container_avg (int, optional) – Shows the average of all distinct containers over all hours in the current date for the given org.

• container_excl_agent_avg (int, optional) – Shows the average of containers without the Datadog Agent over all hours in the current date for the given organization.

• container_hwm (int, optional) – Shows the high-water mark of all distinct containers over all hours in the current date for the given org.

• csm_container_enterprise_compliance_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise compliance containers over all hours in the current date for the given org.

• csm_container_enterprise_cws_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise Cloud Workload Security containers over all hours in the current date for the given org.

• csm_container_enterprise_total_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise containers over all hours in the current date for the given org.

• csm_host_enterprise_aas_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure app services hosts over all hours in the current date for the given org.

• csm_host_enterprise_aws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise AWS hosts over all hours in the current date for the given org.

• csm_host_enterprise_azure_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure hosts over all hours in the current date for the given org.

• csm_host_enterprise_compliance_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise compliance hosts over all hours in the current date for the given org.

• csm_host_enterprise_cws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Cloud Workload Security hosts over all hours in the current date for the given org.

• csm_host_enterprise_gcp_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise GCP hosts over all hours in the current date for the given org.

• csm_host_enterprise_total_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise hosts over all hours in the current date for the given org.

• cspm_aas_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure app services hosts over all hours in the current date for the given org.

• cspm_aws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro AWS hosts over all hours in the current date for the given org.

• cspm_azure_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure hosts over all hours in the current date for the given org.

• cspm_container_avg (int, optional) – Shows the average number of Cloud Security Management Pro containers over all hours in the current date for the given org.

• cspm_container_hwm (int, optional) – Shows the high-water mark of Cloud Security Management Pro containers over all hours in the current date for the given org.

• cspm_gcp_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro GCP hosts over all hours in the current date for the given org.

• cspm_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro hosts over all hours in the current date for the given org.

• custom_historical_ts_avg (int, optional) – Shows the average number of distinct historical custom metrics over all hours in the current date for the given org.

• custom_live_ts_avg (int, optional) – Shows the average number of distinct live custom metrics over all hours in the current date for the given org.

• custom_ts_avg (int, optional) – Shows the average number of distinct custom metrics over all hours in the current date for the given org.

• cws_container_count_avg (int, optional) – Shows the average of all distinct Cloud Workload Security containers over all hours in the current date for the given org.

• cws_fargate_task_avg (int, optional) – Shows the average of all distinct Cloud Workload Security Fargate tasks over all hours in the current date for the given org.

• cws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Workload Security hosts over all hours in the current date for the given org.

• data_jobs_monitoring_host_hr_sum (int, optional) – Shows the sum of all Data Jobs Monitoring hosts over all hours in the current date for the given org.

• dbm_host_top99p_sum (int, optional) – Shows the 99th percentile of all Database Monitoring hosts over all hours in the current month for the given org.

• dbm_queries_avg_sum (int, optional) – Shows the average of all distinct Database Monitoring normalized queries over all hours in the current month for the given org.

• eph_infra_host_agent_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with the Datadog Agent over all hours in the current date for the given org.

• eph_infra_host_alibaba_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Alibaba over all hours in the current date for the given org.

• eph_infra_host_aws_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on AWS over all hours in the current date for the given org.

• eph_infra_host_azure_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Azure over all hours in the current date for the given org.

• eph_infra_host_ent_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Enterprise over all hours in the current date for the given org.

• eph_infra_host_gcp_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on GCP over all hours in the current date for the given org.

• eph_infra_host_heroku_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Heroku over all hours in the current date for the given org.

• eph_infra_host_only_aas_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with only Azure App Services over all hours in the current date for the given org.

• eph_infra_host_only_vsphere_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with only vSphere over all hours in the current date for the given org.

• eph_infra_host_opentelemetry_apm_sum (int, optional) – Shows the sum of all ephemeral APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.

• eph_infra_host_opentelemetry_sum (int, optional) – Shows the sum of all ephemeral hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.

• eph_infra_host_pro_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Pro over all hours in the current date for the given org.

• eph_infra_host_proplus_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Pro Plus over all hours in the current date for the given org.

• error_tracking_apm_error_events_sum (int, optional) – Shows the sum of all Error Tracking APM error events over all hours in the current date for the given org.

• error_tracking_error_events_sum (int, optional) – Shows the sum of all Error Tracking error events over all hours in the current date for the given org.

• error_tracking_events_sum (int, optional) – Shows the sum of all Error Tracking events over all hours in the current date for the given org.

• error_tracking_rum_error_events_sum (int, optional) – Shows the sum of all Error Tracking RUM error events over all hours in the current date for the given org.

• event_management_correlation_correlated_events_sum (int, optional) – Shows the sum of all Event Management correlated events over all hours in the current date for the given org.

• event_management_correlation_correlated_related_events_sum (int, optional) – Shows the sum of all Event Management correlated related events over all hours in the current date for the given org.

• event_management_correlation_sum (int, optional) – Shows the sum of all Event Management correlations over all hours in the current date for the given org.

• fargate_container_profiler_profiling_fargate_avg (int, optional) – The average number of Profiling Fargate tasks over all hours in the current month for the given org.

• fargate_container_profiler_profiling_fargate_eks_avg (int, optional) – The average number of Profiling Fargate Elastic Kubernetes Service tasks over all hours in the current month for the given org.

• fargate_tasks_count_avg (int, optional) – The average task count for Fargate.

• fargate_tasks_count_hwm (int, optional) – Shows the high-water mark of all Fargate tasks over all hours in the current date for the given org.

• flex_logs_compute_large_avg (int, optional) – Shows the average number of Flex Logs Compute Large Instances over all hours in the current date for the given org.

• flex_logs_compute_medium_avg (int, optional) – Shows the average number of Flex Logs Compute Medium Instances over all hours in the current date for the given org.

• flex_logs_compute_small_avg (int, optional) – Shows the average number of Flex Logs Compute Small Instances over all hours in the current date for the given org.

• flex_logs_compute_xlarge_avg (int, optional) – Shows the average number of Flex Logs Compute Extra Large Instances over all hours in the current date for the given org.

• flex_logs_compute_xsmall_avg (int, optional) – Shows the average number of Flex Logs Compute Extra Small Instances over all hours in the current date for the given org.

• flex_logs_starter_avg (int, optional) – Shows the average number of Flex Logs Starter Instances over all hours in the current date for the given org.

• flex_logs_starter_storage_index_avg (int, optional) – Shows the average number of Flex Logs Starter Storage Index Instances over all hours in the current date for the given org.

• flex_logs_starter_storage_retention_adjustment_avg (int, optional) – Shows the average number of Flex Logs Starter Storage Retention Adjustment Instances over all hours in the current date for the given org.

• flex_stored_logs_avg (int, optional) – Shows the average of all Flex Stored Logs over all hours in the current date for the given org.

• forwarding_events_bytes_sum (int, optional) – Shows the sum of all log bytes forwarded over all hours in the current date for the given org.

• gcp_host_top99p (int, optional) – Shows the 99th percentile of all GCP hosts over all hours in the current date for the given org.

• heroku_host_top99p (int, optional) – Shows the 99th percentile of all Heroku dynos over all hours in the current date for the given org.

• id (str, optional) – The organization id.

• incident_management_monthly_active_users_hwm (int, optional) – Shows the high-water mark of incident management monthly active users over all hours in the current date for the given org.

• indexed_events_count_sum (int, optional) – Shows the sum of all log events indexed over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• infra_host_top99p (int, optional) – Shows the 99th percentile of all distinct infrastructure hosts over all hours in the current date for the given org.

• ingested_events_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for the given org.

• iot_device_agg_sum (int, optional) – Shows the sum of all IoT devices over all hours in the current date for the given org.

• iot_device_top99p_sum (int, optional) – Shows the 99th percentile of all IoT devices over all hours in the current date for the given org.

• llm_observability_min_spend_sum (int, optional) – Shows the sum of all LLM Observability minimum spend over all hours in the current date for the given org.

• llm_observability_sum (int, optional) – Shows the sum of all LLM observability sessions over all hours in the current date for the given org.

• mobile_rum_lite_session_count_sum (int, optional) – Shows the sum of all mobile lite sessions over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM sessions on Android over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM sessions on Flutter over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM sessions on iOS over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM sessions on React Native over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM sessions on Roku over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_sum (int, optional) – Shows the sum of all mobile RUM sessions over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_units_sum (int, optional) – Shows the sum of all mobile RUM units over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• name (str, optional) – The organization name.

• ndm_netflow_events_sum (int, optional) – Shows the sum of all Network Device Monitoring NetFlow events over all hours in the current date for the given org.

• netflow_indexed_events_count_sum (int, optional) – Shows the sum of all Network flows indexed over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• network_device_wireless_top99p (int, optional) – Shows the 99th percentile of all Network Device Monitoring wireless devices over all hours in the current date for the given org.

• npm_host_top99p (int, optional) – Shows the 99th percentile of all distinct Cloud Network Monitoring hosts (formerly known as Network hosts) over all hours in the current date for the given org.

• observability_pipelines_bytes_processed_sum (int, optional) – Sum of all observability pipelines bytes processed over all hours in the current date for the given org.

• oci_host_sum (int, optional) – Shows the sum of all Oracle Cloud Infrastructure hosts over all hours in the current date for the given org.

• oci_host_top99p (int, optional) – Shows the 99th percentile of all Oracle Cloud Infrastructure hosts over all hours in the current date for the given org.

• online_archive_events_count_sum (int, optional) – Sum of all online archived events over all hours in the current date for the given org.

• opentelemetry_apm_host_top99p (int, optional) – Shows the 99th percentile of APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.

• opentelemetry_host_top99p (int, optional) – Shows the 99th percentile of all hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.

• product_analytics_sum (int, optional) – Shows the sum of all product analytics sessions over all hours in the current date for the given org.

• profiling_aas_count_top99p (int, optional) – Shows the 99th percentile of all profiled Azure app services over all hours in the current date for all organizations.

• profiling_host_top99p (int, optional) – Shows the 99th percentile of all profiled hosts over all hours within the current date for the given org.

• public_id (str, optional) – The organization public id.

• published_app_hwm (int, optional) – Shows the high-water mark of all published applications over all hours in the current date for the given org.

• region (str, optional) – The region of the organization.

• rum_browser_and_mobile_session_count (int, optional) – Shows the sum of all mobile sessions and all browser lite and legacy sessions over all hours in the current date for the given org (To be deprecated on October 1st, 2024).

• rum_browser_legacy_session_count_sum (int, optional) – Shows the sum of all browser RUM legacy sessions over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_browser_lite_session_count_sum (int, optional) – Shows the sum of all browser RUM lite sessions over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_browser_replay_session_count_sum (int, optional) – Shows the sum of all browser RUM Session Replay counts over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_indexed_sessions_sum (int, optional) – Shows the sum of all RUM indexed sessions over all hours in the current date for the given org.

• rum_ingested_sessions_sum (int, optional) – Shows the sum of all RUM ingested sessions over all hours in the current date for the given org.

• rum_lite_session_count_sum (int, optional) – Shows the sum of all RUM lite sessions (browser and mobile) over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Android over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Flutter over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on iOS over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on React Native over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Roku over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Android over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Flutter over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on iOS over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_kotlinmultiplatform_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Kotlin Multiplatform over all hours within the current date for the given org.

• rum_mobile_lite_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on React Native over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Roku over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_unity_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Unity over all hours within the current date for the given org.

• rum_mobile_replay_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on Android over all hours within the current date for the given org.

• rum_mobile_replay_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on iOS over all hours within the current date for the given org.

• rum_mobile_replay_session_count_kotlinmultiplatform_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on Kotlin Multiplatform over all hours within the current date for the given org.

• rum_mobile_replay_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on React Native over all hours within the current date for the given org.

• rum_replay_session_count_sum (int, optional) – Shows the sum of all RUM Session Replay counts over all hours in the current date for the given org (To be introduced on October 1st, 2024).

• rum_session_count_sum (int, optional) – Shows the sum of all browser RUM lite sessions over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• rum_session_replay_add_on_sum (int, optional) – Shows the sum of all RUM session replay add-on sessions over all hours in the current date for the given org.

• rum_total_session_count_sum (int, optional) – Shows the sum of RUM sessions (browser and mobile) over all hours in the current date for the given org.

• rum_units_sum (int, optional) – Shows the sum of all browser and mobile RUM units over all hours in the current date for the given org (To be deprecated on October 1st, 2024). Deprecated.

• sca_fargate_count_avg (int, optional) – Shows the average of all Software Composition Analysis Fargate tasks over all hours in the current date for the given org.

• sca_fargate_count_hwm (int, optional) – Shows the sum of the high-water marks of all Software Composition Analysis Fargate tasks over all hours in the current date for the given org.

• sds_apm_scanned_bytes_sum (int, optional) – Sum of all APM bytes scanned with sensitive data scanner over all hours in the current date for the given org.

• sds_events_scanned_bytes_sum (int, optional) – Sum of all event stream events bytes scanned with sensitive data scanner over all hours in the current date for the given org.

• sds_logs_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned of logs usage by the Sensitive Data Scanner over all hours in the current month for the given org.

• sds_rum_scanned_bytes_sum (int, optional) – Sum of all RUM bytes scanned with sensitive data scanner over all hours in the current date for the given org.

• sds_total_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned across all usage types by the Sensitive Data Scanner over all hours in the current month for the given org.

• serverless_apps_apm_apm_azure_appservice_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Azure App Service instances for the given date and given org.

• serverless_apps_apm_apm_azure_azurefunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Azure Function instances for the given date and given org.

• serverless_apps_apm_apm_azure_containerapp_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Azure Container App instances for the given date and given org.

• serverless_apps_apm_apm_fargate_ecs_tasks_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Fargate Elastic Container Service tasks for the given date and given org.

• serverless_apps_apm_apm_gcp_cloudfunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Google Cloud Platform Cloud Function instances for the given date and given org.

• serverless_apps_apm_apm_gcp_cloudrun_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for Google Cloud Platform Cloud Run instances for the given date and given org.

• serverless_apps_apm_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring for the given date and given org.

• serverless_apps_apm_excl_fargate_apm_azure_appservice_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure App Service instances for the given date and given org.

• serverless_apps_apm_excl_fargate_apm_azure_azurefunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure Function instances for the given date and given org.

• serverless_apps_apm_excl_fargate_apm_azure_containerapp_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure Container App instances for the given date and given org.

• serverless_apps_apm_excl_fargate_apm_gcp_cloudfunction_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Google Cloud Platform Cloud Function instances for the given date and given org.

• serverless_apps_apm_excl_fargate_apm_gcp_cloudrun_instances_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Google Cloud Platform Cloud Run instances for the given date and given org.

• serverless_apps_apm_excl_fargate_avg (int, optional) – Shows the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for the given date and given org.

• serverless_apps_azure_container_app_instances_avg (int, optional) – Shows the average number of Serverless Apps for Azure Container App instances for the given date and given org.

• serverless_apps_azure_count_avg (int, optional) – Shows the average number of Serverless Apps for Azure for the given date and given org.

• serverless_apps_azure_function_app_instances_avg (int, optional) – Shows the average number of Serverless Apps for Azure Function App instances for the given date and given org.

• serverless_apps_azure_web_app_instances_avg (int, optional) – Shows the average number of Serverless Apps for Azure Web App instances for the given date and given org.

• serverless_apps_ecs_avg (int, optional) – Shows the average number of Serverless Apps for Elastic Container Service for the given date and given org.

• serverless_apps_eks_avg (int, optional) – Shows the average number of Serverless Apps for Elastic Kubernetes Service for the given date and given org.

• serverless_apps_excl_fargate_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for the given date and given org.

• serverless_apps_excl_fargate_azure_container_app_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Azure Container App instances for the given date and given org.

• serverless_apps_excl_fargate_azure_function_app_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Azure Function App instances for the given date and given org.

• serverless_apps_excl_fargate_azure_web_app_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Azure Web App instances for the given date and given org.

• serverless_apps_excl_fargate_google_cloud_functions_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Google Cloud Platform Cloud Functions instances for the given date and given org.

• serverless_apps_excl_fargate_google_cloud_run_instances_avg (int, optional) – Shows the average number of Serverless Apps excluding Fargate for Google Cloud Platform Cloud Run instances for the given date and given org.

• serverless_apps_google_cloud_functions_instances_avg (int, optional) – Shows the average number of Serverless Apps for Google Cloud Platform Cloud Functions instances for the given date and given org.

• serverless_apps_google_cloud_run_instances_avg (int, optional) – Shows the average number of Serverless Apps for Google Cloud Platform Cloud Run instances for the given date and given org.

• serverless_apps_google_count_avg (int, optional) – Shows the average number of Serverless Apps for Google Cloud for the given date and given org.

• serverless_apps_total_count_avg (int, optional) – Shows the average number of Serverless Apps for Azure and Google Cloud for the given date and given org.

• siem_analyzed_logs_add_on_count_sum (int, optional) – Shows the sum of all log events analyzed by Cloud SIEM over all hours in the current date for the given org.

• synthetics_browser_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic browser tests over all hours in the current date for the given org.

• synthetics_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic API tests over all hours in the current date for the given org.

• synthetics_mobile_test_runs_sum (int, optional) – Shows the sum of all Synthetic mobile application tests over all hours in the current date for the given org.

• synthetics_parallel_testing_max_slots_hwm (int, optional) – Shows the high-water mark of used synthetics parallel testing slots over all hours in the current date for the given org.

• trace_search_indexed_events_count_sum (int, optional) – Shows the sum of all Indexed Spans indexed over all hours in the current date for the given org.

• twol_ingested_events_bytes_sum (int, optional) – Shows the sum of all ingested APM span bytes over all hours in the current date for the given org.

• universal_service_monitoring_host_top99p (int, optional) – Shows the 99th percentile of all Universal Service Monitoring hosts over all hours in the current date for the given org.

• vsphere_host_top99p (int, optional) – Shows the 99th percentile of all vSphere hosts over all hours in the current date for the given org.

• vuln_management_host_count_top99p (int, optional) – Shows the 99th percentile of all Application Vulnerability Management hosts over all hours in the current date for the given org.

• workflow_executions_usage_sum (int, optional) – Sum of all workflows executed over all hours in the current date for the given org.

datadog_api_client.v1.model.usage_summary_response module

class UsageSummaryResponse(arg: None)

class UsageSummaryResponse(arg: ModelComposed)

class UsageSummaryResponse(*args, **kwargs)

Bases: ModelNormal

Response summarizing all usage aggregated across the months in the request for all organizations, and broken down by month and by organization.

Parameters:

• agent_host_top99p_sum (int, optional) – Shows the 99th percentile of all agent hosts over all hours in the current month for all organizations.

• apm_azure_app_service_host_top99p_sum (int, optional) – Shows the 99th percentile of all Azure app services using APM over all hours in the current month all organizations.

• apm_devsecops_host_top99p_sum (int, optional) – Shows the 99th percentile of all APM DevSecOps hosts over all hours in the current month for all organizations.

• apm_fargate_count_avg_sum (int, optional) – Shows the average of all APM ECS Fargate tasks over all hours in the current month for all organizations.

• apm_host_top99p_sum (int, optional) – Shows the 99th percentile of all distinct APM hosts over all hours in the current month for all organizations.

• appsec_fargate_count_avg_sum (int, optional) – Shows the average of all Application Security Monitoring ECS Fargate tasks over all hours in the current month for all organizations.

• asm_serverless_agg_sum (int, optional) – Shows the sum of all Application Security Monitoring Serverless invocations over all hours in the current months for all organizations.

• audit_logs_lines_indexed_agg_sum (int, optional) – Shows the sum of all audit logs lines indexed over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• audit_trail_enabled_hwm_sum (int, optional) – Shows the total number of organizations that had Audit Trail enabled over a specific number of months.

• avg_profiled_fargate_tasks_sum (int, optional) – The average total count for Fargate Container Profiler over all hours in the current month for all organizations.

• aws_host_top99p_sum (int, optional) – Shows the 99th percentile of all AWS hosts over all hours in the current month for all organizations.

• aws_lambda_func_count (int, optional) – Shows the average of the number of functions that executed 1 or more times each hour in the current month for all organizations.

• aws_lambda_invocations_sum (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current month for all organizations.

• azure_app_service_top99p_sum (int, optional) – Shows the 99th percentile of all Azure app services over all hours in the current month for all organizations.

• azure_host_top99p_sum (int, optional) – Shows the 99th percentile of all Azure hosts over all hours in the current month for all organizations.

• billable_ingested_bytes_agg_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current month for all organizations.

• browser_rum_lite_session_count_agg_sum (int, optional) – Shows the sum of all browser lite sessions over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• browser_rum_replay_session_count_agg_sum (int, optional) – Shows the sum of all browser replay sessions over all hours in the current month for all organizations (To be deprecated on October 1st, 2024).

• browser_rum_units_agg_sum (int, optional) – Shows the sum of all browser RUM units over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• ci_pipeline_indexed_spans_agg_sum (int, optional) – Shows the sum of all CI pipeline indexed spans over all hours in the current month for all organizations.

• ci_test_indexed_spans_agg_sum (int, optional) – Shows the sum of all CI test indexed spans over all hours in the current month for all organizations.

• ci_visibility_itr_committers_hwm_sum (int, optional) – Shows the high-water mark of all CI visibility intelligent test runner committers over all hours in the current month for all organizations.

• ci_visibility_pipeline_committers_hwm_sum (int, optional) – Shows the high-water mark of all CI visibility pipeline committers over all hours in the current month for all organizations.

• ci_visibility_test_committers_hwm_sum (int, optional) – Shows the high-water mark of all CI visibility test committers over all hours in the current month for all organizations.

• cloud_cost_management_aws_host_count_avg_sum (int, optional) – Sum of the host count average for Cloud Cost Management for AWS.

• cloud_cost_management_azure_host_count_avg_sum (int, optional) – Sum of the host count average for Cloud Cost Management for Azure.

• cloud_cost_management_gcp_host_count_avg_sum (int, optional) – Sum of the host count average for Cloud Cost Management for GCP.

• cloud_cost_management_host_count_avg_sum (int, optional) – Sum of the host count average for Cloud Cost Management for all cloud providers.

• cloud_siem_events_agg_sum (int, optional) – Shows the sum of all Cloud Security Information and Event Management events over all hours in the current month for all organizations.

• code_analysis_sa_committers_hwm_sum (int, optional) – Shows the high-water mark of all Static Analysis committers over all hours in the current month for all organizations.

• code_analysis_sca_committers_hwm_sum (int, optional) – Shows the high-water mark of all static Software Composition Analysis committers over all hours in the current month for all organizations.

• code_security_host_top99p_sum (int, optional) – Shows the 99th percentile of all Code Security hosts over all hours in the current month for all organizations.

• container_avg_sum (int, optional) – Shows the average of all distinct containers over all hours in the current month for all organizations.

• container_excl_agent_avg_sum (int, optional) – Shows the average of the containers without the Datadog Agent over all hours in the current month for all organizations.

• container_hwm_sum (int, optional) – Shows the sum of the high-water marks of all distinct containers over all hours in the current month for all organizations.

• csm_container_enterprise_compliance_count_agg_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise compliance containers over all hours in the current month for all organizations.

• csm_container_enterprise_cws_count_agg_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise Cloud Workload Security containers over all hours in the current month for all organizations.

• csm_container_enterprise_total_count_agg_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise containers over all hours in the current month for all organizations.

• csm_host_enterprise_aas_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure app services hosts over all hours in the current month for all organizations.

• csm_host_enterprise_aws_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise AWS hosts over all hours in the current month for all organizations.

• csm_host_enterprise_azure_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure hosts over all hours in the current month for all organizations.

• csm_host_enterprise_compliance_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise compliance hosts over all hours in the current month for all organizations.

• csm_host_enterprise_cws_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Cloud Workload Security hosts over all hours in the current month for all organizations.

• csm_host_enterprise_gcp_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise GCP hosts over all hours in the current month for all organizations.

• csm_host_enterprise_total_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise hosts over all hours in the current month for all organizations.

• cspm_aas_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure app services hosts over all hours in the current month for all organizations.

• cspm_aws_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro AWS hosts over all hours in the current month for all organizations.

• cspm_azure_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure hosts over all hours in the current month for all organizations.

• cspm_container_avg_sum (int, optional) – Shows the average number of Cloud Security Management Pro containers over all hours in the current month for all organizations.

• cspm_container_hwm_sum (int, optional) – Shows the sum of the high-water marks of Cloud Security Management Pro containers over all hours in the current month for all organizations.

• cspm_gcp_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro GCP hosts over all hours in the current month for all organizations.

• cspm_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro hosts over all hours in the current month for all organizations.

• custom_historical_ts_sum (int, optional) – Shows the average number of distinct historical custom metrics over all hours in the current month for all organizations.

• custom_live_ts_sum (int, optional) – Shows the average number of distinct live custom metrics over all hours in the current month for all organizations.

• custom_ts_sum (int, optional) – Shows the average number of distinct custom metrics over all hours in the current month for all organizations.

• cws_container_avg_sum (int, optional) – Shows the average of all distinct Cloud Workload Security containers over all hours in the current month for all organizations.

• cws_fargate_task_avg_sum (int, optional) – Shows the average of all distinct Cloud Workload Security Fargate tasks over all hours in the current month for all organizations.

• cws_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Workload Security hosts over all hours in the current month for all organizations.

• data_jobs_monitoring_host_hr_agg_sum (int, optional) – Shows the sum of Data Jobs Monitoring hosts over all hours in the current months for all organizations

• dbm_host_top99p_sum (int, optional) – Shows the 99th percentile of all Database Monitoring hosts over all hours in the current month for all organizations.

• dbm_queries_avg_sum (int, optional) – Shows the average of all distinct Database Monitoring Normalized Queries over all hours in the current month for all organizations.

• end_date (datetime, optional) – Shows the last date of usage in the current month for all organizations.

• eph_infra_host_agent_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with the Datadog Agent over all hours in the current month for all organizations.

• eph_infra_host_alibaba_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Alibaba over all hours in the current month for all organizations.

• eph_infra_host_aws_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on AWS over all hours in the current month for all organizations.

• eph_infra_host_azure_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Azure over all hours in the current month for all organizations.

• eph_infra_host_ent_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Enterprise over all hours in the current month for all organizations.

• eph_infra_host_gcp_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on GCP over all hours in the current month for all organizations.

• eph_infra_host_heroku_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts on Heroku over all hours in the current month for all organizations.

• eph_infra_host_only_aas_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with only Azure App Services over all hours in the current month for all organizations.

• eph_infra_host_only_vsphere_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts with only vSphere over all hours in the current month for all organizations.

• eph_infra_host_opentelemetry_agg_sum (int, optional) – Shows the sum of all ephemeral hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current month for all organizations.

• eph_infra_host_opentelemetry_apm_agg_sum (int, optional) – Shows the sum of all ephemeral APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current month for all organizations.

• eph_infra_host_pro_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Pro over all hours in the current month for all organizations.

• eph_infra_host_proplus_agg_sum (int, optional) – Shows the sum of all ephemeral infrastructure hosts for Pro Plus over all hours in the current month for all organizations.

• error_tracking_apm_error_events_agg_sum (int, optional) – Shows the sum of all Error Tracking APM error events over all hours in the current month for all organizations.

• error_tracking_error_events_agg_sum (int, optional) – Shows the sum of all Error Tracking error events over all hours in the current month for all organizations.

• error_tracking_events_agg_sum (int, optional) – Shows the sum of all Error Tracking events over all hours in the current months for all organizations.

• error_tracking_rum_error_events_agg_sum (int, optional) – Shows the sum of all Error Tracking RUM error events over all hours in the current month for all organizations.

• event_management_correlation_agg_sum (int, optional) – Shows the sum of all Event Management correlations over all hours in the current month for all organizations.

• event_management_correlation_correlated_events_agg_sum (int, optional) – Shows the sum of all Event Management correlated events over all hours in the current month for all organizations.

• event_management_correlation_correlated_related_events_agg_sum (int, optional) – Shows the sum of all Event Management correlated related events over all hours in the current month for all organizations.

• fargate_container_profiler_profiling_fargate_avg_sum (int, optional) – The average number of Profiling Fargate tasks over all hours in the current month for all organizations.

• fargate_container_profiler_profiling_fargate_eks_avg_sum (int, optional) – The average number of Profiling Fargate Elastic Kubernetes Service tasks over all hours in the current month for all organizations.

• fargate_tasks_count_avg_sum (int, optional) – Shows the average of all Fargate tasks over all hours in the current month for all organizations.

• fargate_tasks_count_hwm_sum (int, optional) – Shows the sum of the high-water marks of all Fargate tasks over all hours in the current month for all organizations.

• flex_logs_compute_large_avg_sum (int, optional) – Shows the average number of Flex Logs Compute Large Instances over all hours in the current months for all organizations.

• flex_logs_compute_medium_avg_sum (int, optional) – Shows the average number of Flex Logs Compute Medium Instances over all hours in the current months for all organizations.

• flex_logs_compute_small_avg_sum (int, optional) – Shows the average number of Flex Logs Compute Small Instances over all hours in the current months for all organizations.

• flex_logs_compute_xlarge_avg_sum (int, optional) – Shows the average number of Flex Logs Compute Extra Large Instances over all hours in the current months for all organizations.

• flex_logs_compute_xsmall_avg_sum (int, optional) – Shows the average number of Flex Logs Compute Extra Small Instances over all hours in the current months for all organizations.

• flex_logs_starter_avg_sum (int, optional) – Shows the average number of Flex Logs Starter Instances over all hours in the current months for all organizations.

• flex_logs_starter_storage_index_avg_sum (int, optional) – Shows the average number of Flex Logs Starter Storage Index Instances over all hours in the current months for all organizations.

• flex_logs_starter_storage_retention_adjustment_avg_sum (int, optional) – Shows the average number of Flex Logs Starter Storage Retention Adjustment Instances over all hours in the current months for all organizations.

• flex_stored_logs_avg_sum (int, optional) – Shows the average of all Flex Stored Logs over all hours in the current months for all organizations.

• forwarding_events_bytes_agg_sum (int, optional) – Shows the sum of all logs forwarding bytes over all hours in the current month for all organizations (data available as of April 1, 2023)

• gcp_host_top99p_sum (int, optional) – Shows the 99th percentile of all GCP hosts over all hours in the current month for all organizations.

• heroku_host_top99p_sum (int, optional) – Shows the 99th percentile of all Heroku dynos over all hours in the current month for all organizations.

• incident_management_monthly_active_users_hwm_sum (int, optional) – Shows sum of the high-water marks of incident management monthly active users in the current month for all organizations.

• indexed_events_count_agg_sum (int, optional) – Shows the sum of all log events indexed over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• infra_host_top99p_sum (int, optional) – Shows the 99th percentile of all distinct infrastructure hosts over all hours in the current month for all organizations.

• ingested_events_bytes_agg_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current month for all organizations.

• iot_device_agg_sum (int, optional) – Shows the sum of all IoT devices over all hours in the current month for all organizations.

• iot_device_top99p_sum (int, optional) – Shows the 99th percentile of all IoT devices over all hours in the current month of all organizations.

• last_updated (datetime, optional) – Shows the most recent hour in the current month for all organizations for which all usages were calculated.

• live_indexed_events_agg_sum (int, optional) – Shows the sum of all live logs indexed over all hours in the current month for all organization (To be deprecated on October 1st, 2024). Deprecated.

• live_ingested_bytes_agg_sum (int, optional) – Shows the sum of all live logs bytes ingested over all hours in the current month for all organizations (data available as of December 1, 2020).

• llm_observability_agg_sum (int, optional) – Sum of all LLM observability sessions for all hours in the current month for all organizations.

• llm_observability_min_spend_agg_sum (int, optional) – Minimum spend for LLM observability sessions for all hours in the current month for all organizations.

• logs_by_retention (LogsByRetention, optional) – Object containing logs usage data broken down by retention period.

• mobile_rum_lite_session_count_agg_sum (int, optional) – Shows the sum of all mobile lite sessions over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_agg_sum (int, optional) – Shows the sum of all mobile RUM sessions over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_android_agg_sum (int, optional) – Shows the sum of all mobile RUM sessions on Android over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_flutter_agg_sum (int, optional) – Shows the sum of all mobile RUM sessions on Flutter over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_ios_agg_sum (int, optional) – Shows the sum of all mobile RUM sessions on iOS over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_reactnative_agg_sum (int, optional) – Shows the sum of all mobile RUM sessions on React Native over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_session_count_roku_agg_sum (int, optional) – Shows the sum of all mobile RUM sessions on Roku over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• mobile_rum_units_agg_sum (int, optional) – Shows the sum of all mobile RUM units over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• ndm_netflow_events_agg_sum (int, optional) – Shows the sum of all Network Device Monitoring NetFlow events over all hours in the current month for all organizations.

• netflow_indexed_events_count_agg_sum (int, optional) – Shows the sum of all Network flows indexed over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• network_device_wireless_top99p_sum (int, optional) – Shows the 99th percentile of all Network Device Monitoring wireless devices over all hours in the current month for all organizations.

• npm_host_top99p_sum (int, optional) – Shows the 99th percentile of all distinct Cloud Network Monitoring hosts (formerly known as Network hosts) over all hours in the current month for all organizations.

• observability_pipelines_bytes_processed_agg_sum (int, optional) – Sum of all observability pipelines bytes processed over all hours in the current month for all organizations.

• oci_host_agg_sum (int, optional) – Shows the sum of Oracle Cloud Infrastructure hosts over all hours in the current months for all organizations

• oci_host_top99p_sum (int, optional) – Shows the 99th percentile of Oracle Cloud Infrastructure hosts over all hours in the current months for all organizations

• online_archive_events_count_agg_sum (int, optional) – Sum of all online archived events over all hours in the current month for all organizations.

• opentelemetry_apm_host_top99p_sum (int, optional) – Shows the 99th percentile of APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current month for all organizations.

• opentelemetry_host_top99p_sum (int, optional) – Shows the 99th percentile of all hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current month for all organizations.

• product_analytics_agg_sum (int, optional) – Sum of all product analytics sessions for all hours in the current month for all organizations.

• profiling_aas_count_top99p_sum (int, optional) – Shows the 99th percentile of all profiled Azure app services over all hours in the current month for all organizations.

• profiling_container_agent_count_avg (int, optional) – Shows the average number of profiled containers over all hours in the current month for all organizations.

• profiling_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all profiled hosts over all hours in the current month for all organizations.

• published_app_hwm_sum (int, optional) – Shows the high-water mark of all published applications over all hours in the current month for all organizations.

• rehydrated_indexed_events_agg_sum (int, optional) – Shows the sum of all rehydrated logs indexed over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• rehydrated_ingested_bytes_agg_sum (int, optional) – Shows the sum of all rehydrated logs bytes ingested over all hours in the current month for all organizations (data available as of December 1, 2020).

• rum_browser_and_mobile_session_count (int, optional) – Shows the sum of all mobile sessions and all browser lite and legacy sessions over all hours in the current month for all organizations (To be deprecated on October 1st, 2024).

• rum_browser_legacy_session_count_agg_sum (int, optional) – Shows the sum of all browser RUM legacy sessions over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_browser_lite_session_count_agg_sum (int, optional) – Shows the sum of all browser RUM lite sessions over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_browser_replay_session_count_agg_sum (int, optional) – Shows the sum of all browser RUM Session Replay counts over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_indexed_sessions_agg_sum (int, optional) – Sum of all RUM indexed sessions for all hours in the current month for all organizations.

• rum_ingested_sessions_agg_sum (int, optional) – Sum of all RUM ingested sessions for all hours in the current month for all organizations.

• rum_lite_session_count_agg_sum (int, optional) – Shows the sum of all RUM lite sessions (browser and mobile) over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_android_agg_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Android over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_flutter_agg_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Flutter over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_ios_agg_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on iOS over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_reactnative_agg_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on React Native over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_legacy_session_count_roku_agg_sum (int, optional) – Shows the sum of all mobile RUM legacy sessions on Roku over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_android_agg_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Android over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_flutter_agg_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Flutter over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_ios_agg_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on iOS over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_kotlinmultiplatform_agg_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Kotlin Multiplatform over all hours within the current month for all organizations.

• rum_mobile_lite_session_count_reactnative_agg_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on React Native over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_roku_agg_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Roku over all hours within the current month for all organizations (To be introduced on October 1st, 2024).

• rum_mobile_lite_session_count_unity_agg_sum (int, optional) – Shows the sum of all mobile RUM lite sessions on Unity over all hours within the current month for all organizations.

• rum_mobile_replay_session_count_android_agg_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on Android over all hours within the current month for all organizations.

• rum_mobile_replay_session_count_ios_agg_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on iOS over all hours within the current month for all organizations.

• rum_mobile_replay_session_count_kotlinmultiplatform_agg_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on Kotlin Multiplatform over all hours within the current month for all organizations.

• rum_mobile_replay_session_count_reactnative_agg_sum (int, optional) – Shows the sum of all mobile RUM replay sessions on React Native over all hours within the current month for all organizations.

• rum_replay_session_count_agg_sum (int, optional) – Shows the sum of all RUM Session Replay counts over all hours in the current month for all organizations (To be introduced on October 1st, 2024).

• rum_session_count_agg_sum (int, optional) – Shows the sum of all browser RUM lite sessions over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• rum_session_replay_add_on_agg_sum (int, optional) – Sum of all RUM session replay add-on sessions for all hours in the current month for all organizations.

• rum_total_session_count_agg_sum (int, optional) – Shows the sum of RUM sessions (browser and mobile) over all hours in the current month for all organizations.

• rum_units_agg_sum (int, optional) – Shows the sum of all browser and mobile RUM units over all hours in the current month for all organizations (To be deprecated on October 1st, 2024). Deprecated.

• sca_fargate_count_avg_sum (int, optional) – Shows the average of all Software Composition Analysis Fargate tasks over all hours in the current months for all organizations.

• sca_fargate_count_hwm_sum (int, optional) – Shows the sum of the high-water marks of all Software Composition Analysis Fargate tasks over all hours in the current months for all organizations.

• sds_apm_scanned_bytes_sum (int, optional) – Sum of all APM bytes scanned with sensitive data scanner in the current month for all organizations.

• sds_events_scanned_bytes_sum (int, optional) – Sum of all event stream events bytes scanned with sensitive data scanner in the current month for all organizations.

• sds_logs_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned of logs usage by the Sensitive Data Scanner over all hours in the current month for all organizations.

• sds_rum_scanned_bytes_sum (int, optional) – Sum of all RUM bytes scanned with sensitive data scanner in the current month for all organizations.

• sds_total_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned across all usage types by the Sensitive Data Scanner over all hours in the current month for all organizations.

• serverless_apps_apm_apm_azure_appservice_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring for Azure App Service instances in the current month for all organizations.

• serverless_apps_apm_apm_azure_azurefunction_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring for Azure Function instances in the current month for all organizations.

• serverless_apps_apm_apm_azure_containerapp_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring for Azure Container App instances in the current month for all organizations.

• serverless_apps_apm_apm_fargate_ecs_tasks_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring for Fargate Elastic Container Service tasks in the current month for all organizations.

• serverless_apps_apm_apm_gcp_cloudfunction_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring for Google Cloud Platform Cloud Function instances in the current month for all organizations.

• serverless_apps_apm_apm_gcp_cloudrun_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring for Google Cloud Platform Cloud Run instances in the current month for all organizations.

• serverless_apps_apm_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring in the current month for all organizations.

• serverless_apps_apm_excl_fargate_apm_azure_appservice_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure App Service instances in the current month for all organizations.

• serverless_apps_apm_excl_fargate_apm_azure_azurefunction_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure Function instances in the current month for all organizations.

• serverless_apps_apm_excl_fargate_apm_azure_containerapp_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Azure Container App instances in the current month for all organizations.

• serverless_apps_apm_excl_fargate_apm_gcp_cloudfunction_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Google Cloud Platform Cloud Function instances in the current month for all organizations.

• serverless_apps_apm_excl_fargate_apm_gcp_cloudrun_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring excluding Fargate for Google Cloud Platform Cloud Run instances in the current month for all organizations.

• serverless_apps_apm_excl_fargate_avg_sum (int, optional) – Sum of the average number of Serverless Apps with Application Performance Monitoring excluding Fargate in the current month for all organizations.

• serverless_apps_azure_container_app_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Azure Container App instances in the current month for all organizations.

• serverless_apps_azure_count_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Azure in the current month for all organizations.

• serverless_apps_azure_function_app_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Azure Function App instances in the current month for all organizations.

• serverless_apps_azure_web_app_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Azure Web App instances in the current month for all organizations.

• serverless_apps_ecs_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Elastic Container Service in the current month for all organizations.

• serverless_apps_eks_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Elastic Kubernetes Service in the current month for all organizations.

• serverless_apps_excl_fargate_avg_sum (int, optional) – Sum of the average number of Serverless Apps excluding Fargate in the current month for all organizations.

• serverless_apps_excl_fargate_azure_container_app_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps excluding Fargate for Azure Container App instances in the current month for all organizations.

• serverless_apps_excl_fargate_azure_function_app_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps excluding Fargate for Azure Function App instances in the current month for all organizations.

• serverless_apps_excl_fargate_azure_web_app_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps excluding Fargate for Azure Web App instances in the current month for all organizations.

• serverless_apps_excl_fargate_google_cloud_functions_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps excluding Fargate for Google Cloud Platform Cloud Functions instances in the current month for all organizations.

• serverless_apps_excl_fargate_google_cloud_run_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps excluding Fargate for Google Cloud Platform Cloud Run instances in the current month for all organizations.

• serverless_apps_google_cloud_functions_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Google Cloud Platform Cloud Functions instances in the current month for all organizations.

• serverless_apps_google_cloud_run_instances_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Google Cloud Platform Cloud Run instances in the current month for all organizations.

• serverless_apps_google_count_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Google Cloud in the current month for all organizations.

• serverless_apps_total_count_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Azure and Google Cloud in the current month for all organizations.

• siem_analyzed_logs_add_on_count_agg_sum (int, optional) – Shows the sum of all log events analyzed by Cloud SIEM over all hours in the current month for all organizations.

• start_date (datetime, optional) – Shows the first date of usage in the current month for all organizations.

• synthetics_browser_check_calls_count_agg_sum (int, optional) – Shows the sum of all Synthetic browser tests over all hours in the current month for all organizations.

• synthetics_check_calls_count_agg_sum (int, optional) – Shows the sum of all Synthetic API tests over all hours in the current month for all organizations.

• synthetics_mobile_test_runs_agg_sum (int, optional) – Shows the sum of Synthetic mobile application tests over all hours in the current month for all organizations.

• synthetics_parallel_testing_max_slots_hwm_sum (int, optional) – Shows the sum of the high-water marks of used synthetics parallel testing slots over all hours in the current month for all organizations.

• trace_search_indexed_events_count_agg_sum (int, optional) – Shows the sum of all Indexed Spans indexed over all hours in the current month for all organizations.

• twol_ingested_events_bytes_agg_sum (int, optional) – Shows the sum of all ingested APM span bytes over all hours in the current month for all organizations.

• universal_service_monitoring_host_top99p_sum (int, optional) – Shows the 99th percentile of all Universal Service Monitoring hosts over all hours in the current month for all organizations.

• usage ([UsageSummaryDate], optional) – An array of objects regarding hourly usage.

• vsphere_host_top99p_sum (int, optional) – Shows the 99th percentile of all vSphere hosts over all hours in the current month for all organizations.

• vuln_management_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Application Vulnerability Management hosts over all hours in the current month for all organizations.

• workflow_executions_usage_agg_sum (int, optional) – Sum of all workflows executed over all hours in the current month for all organizations.

datadog_api_client.v1.model.usage_synthetics_api_hour module

class UsageSyntheticsAPIHour(arg: None)

class UsageSyntheticsAPIHour(arg: ModelComposed)

class UsageSyntheticsAPIHour(*args, **kwargs)

Bases: ModelNormal

Number of Synthetics API tests run for each hour for a given organization.

Parameters:

• check_calls_count (int, none_type, optional) – Contains the number of Synthetics API tests run.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_synthetics_api_response module

class UsageSyntheticsAPIResponse(arg: None)

class UsageSyntheticsAPIResponse(arg: ModelComposed)

class UsageSyntheticsAPIResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of Synthetics API tests run for each hour for a given organization.

Parameters:

usage ([UsageSyntheticsAPIHour], optional) – Get hourly usage for Synthetics API tests.

datadog_api_client.v1.model.usage_synthetics_browser_hour module

class UsageSyntheticsBrowserHour(arg: None)

class UsageSyntheticsBrowserHour(arg: ModelComposed)

class UsageSyntheticsBrowserHour(*args, **kwargs)

Bases: ModelNormal

Number of Synthetics Browser tests run for each hour for a given organization.

Parameters:

• browser_check_calls_count (int, none_type, optional) – Contains the number of Synthetics Browser tests run.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_synthetics_browser_response module

class UsageSyntheticsBrowserResponse(arg: None)

class UsageSyntheticsBrowserResponse(arg: ModelComposed)

class UsageSyntheticsBrowserResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of Synthetics Browser tests run for each hour for a given organization.

Parameters:

usage ([UsageSyntheticsBrowserHour], optional) – Get hourly usage for Synthetics Browser tests.

datadog_api_client.v1.model.usage_synthetics_hour module

class UsageSyntheticsHour(arg: None)

class UsageSyntheticsHour(arg: ModelComposed)

class UsageSyntheticsHour(*args, **kwargs)

Bases: ModelNormal

The number of synthetics tests run for each hour for a given organization.

Parameters:

• check_calls_count (int, optional) – Contains the number of Synthetics API tests run.

• hour (datetime, optional) – The hour for the usage.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_synthetics_response module

class UsageSyntheticsResponse(arg: None)

class UsageSyntheticsResponse(arg: ModelComposed)

class UsageSyntheticsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of Synthetics API tests run for each hour for a given organization.

Parameters:

usage ([UsageSyntheticsHour], optional) – Array with the number of hourly Synthetics test run for a given organization.

datadog_api_client.v1.model.usage_timeseries_hour module

class UsageTimeseriesHour(arg: None)

class UsageTimeseriesHour(arg: ModelComposed)

class UsageTimeseriesHour(*args, **kwargs)

Bases: ModelNormal

The hourly usage of timeseries.

Parameters:

• hour (datetime, optional) – The hour for the usage.

• num_custom_input_timeseries (int, optional) – Contains the number of custom metrics that are inputs for aggregations (metric configured is custom).

• num_custom_output_timeseries (int, optional) – Contains the number of custom metrics that are outputs for aggregations (metric configured is custom).

• num_custom_timeseries (int, optional) – Contains sum of non-aggregation custom metrics and custom metrics that are outputs for aggregations.

• org_name (str, optional) – The organization name.

• public_id (str, optional) – The organization public ID.

datadog_api_client.v1.model.usage_timeseries_response module

class UsageTimeseriesResponse(arg: None)

class UsageTimeseriesResponse(arg: ModelComposed)

class UsageTimeseriesResponse(*args, **kwargs)

Bases: ModelNormal

Response containing hourly usage of timeseries.

Parameters:

usage ([UsageTimeseriesHour], optional) – An array of objects regarding hourly usage of timeseries.

datadog_api_client.v1.model.usage_top_avg_metrics_hour module

class UsageTopAvgMetricsHour(arg: None)

class UsageTopAvgMetricsHour(arg: ModelComposed)

class UsageTopAvgMetricsHour(*args, **kwargs)

Bases: ModelNormal

Number of hourly recorded custom metrics for a given organization.

Parameters:

• avg_metric_hour (int, optional) – Average number of timeseries per hour in which the metric occurs.

• max_metric_hour (int, optional) – Maximum number of timeseries per hour in which the metric occurs.

• metric_category (UsageMetricCategory, optional) – Contains the metric category.

• metric_name (str, optional) – Contains the custom metric name.

datadog_api_client.v1.model.usage_top_avg_metrics_metadata module

class UsageTopAvgMetricsMetadata(arg: None)

class UsageTopAvgMetricsMetadata(arg: ModelComposed)

class UsageTopAvgMetricsMetadata(*args, **kwargs)

Bases: ModelNormal

The object containing document metadata.

Parameters:

• day (datetime, optional) – The day value from the user request that contains the returned usage data. (If day was used the request)

• month (datetime, optional) – The month value from the user request that contains the returned usage data. (If month was used the request)

• pagination (UsageTopAvgMetricsPagination, optional) – The metadata for the current pagination.

datadog_api_client.v1.model.usage_top_avg_metrics_pagination module

class UsageTopAvgMetricsPagination(arg: None)

class UsageTopAvgMetricsPagination(arg: ModelComposed)

class UsageTopAvgMetricsPagination(*args, **kwargs)

Bases: ModelNormal

The metadata for the current pagination.

Parameters:

• limit (int, optional) – Maximum amount of records to be returned.

• next_record_id (str, none_type, optional) – The cursor to get the next results (if any). To make the next request, use the same parameters and add next_record_id.

• total_number_of_records (int, none_type, optional) – Total number of records.

datadog_api_client.v1.model.usage_top_avg_metrics_response module

class UsageTopAvgMetricsResponse(arg: None)

class UsageTopAvgMetricsResponse(arg: ModelComposed)

class UsageTopAvgMetricsResponse(*args, **kwargs)

Bases: ModelNormal

Response containing the number of hourly recorded custom metrics for a given organization.

Parameters:

• metadata (UsageTopAvgMetricsMetadata, optional) – The object containing document metadata.

• usage ([UsageTopAvgMetricsHour], optional) – Number of hourly recorded custom metrics for a given organization.

datadog_api_client.v1.model.user module

class User(arg: None)

class User(arg: ModelComposed)

class User(*args, **kwargs)

Bases: ModelNormal

Create, edit, and disable users.

Parameters:

• access_role (AccessRole, none_type, optional) – The access role of the user. Options are st (standard user), adm (admin user), or ro (read-only user).

• disabled (bool, optional) – The new disabled status of the user.

• email (str, optional) – The new email of the user.

• handle (str, optional) – The user handle, must be a valid email.

• icon (str, optional) – Gravatar icon associated to the user.

• name (str, optional) – The name of the user.

• verified (bool, optional) – Whether or not the user logged in Datadog at least once.

datadog_api_client.v1.model.user_disable_response module

class UserDisableResponse(arg: None)

class UserDisableResponse(arg: ModelComposed)

class UserDisableResponse(*args, **kwargs)

Bases: ModelNormal

Array of user disabled for a given organization.

Parameters:

message (str, optional) – Information pertaining to a user disabled for a given organization.

datadog_api_client.v1.model.user_list_response module

class UserListResponse(arg: None)

class UserListResponse(arg: ModelComposed)

class UserListResponse(*args, **kwargs)

Bases: ModelNormal

Array of Datadog users for a given organization.

Parameters:

users ([User], optional) – Array of users.

datadog_api_client.v1.model.user_response module

class UserResponse(arg: None)

class UserResponse(arg: ModelComposed)

class UserResponse(*args, **kwargs)

Bases: ModelNormal

A Datadog User.

Parameters:

user (User, optional) – Create, edit, and disable users.

datadog_api_client.v1.model.viewing_preferences module

class ViewingPreferences(arg: None)

class ViewingPreferences(arg: ModelComposed)

class ViewingPreferences(*args, **kwargs)

Bases: ModelNormal

The viewing preferences for a shared dashboard.

Parameters:

• high_density (bool, optional) – Whether the widgets on the shared dashboard should be displayed with high density.

• theme (ViewingPreferencesTheme, optional) – The theme of the shared dashboard view. “system” follows your system’s default viewing theme.

datadog_api_client.v1.model.viewing_preferences_theme module

class ViewingPreferencesTheme(arg: None)

class ViewingPreferencesTheme(arg: ModelComposed)

class ViewingPreferencesTheme(*args, **kwargs)

Bases: ModelSimple

The theme of the shared dashboard view. “system” follows your system’s default viewing theme.

Parameters:

• value (str) – Must be one of [“system”, “light”, “dark”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.webhooks_integration module

class WebhooksIntegration(arg: None)

class WebhooksIntegration(arg: ModelComposed)

class WebhooksIntegration(*args, **kwargs)

Bases: ModelNormal

Datadog-Webhooks integration.

Parameters:

• custom_headers (str, none_type, optional) – If null , uses no header. If given a JSON payload, these will be headers attached to your webhook.

• encode_as (WebhooksIntegrationEncoding, optional) – Encoding type. Can be given either json or form.

• name (str) – The name of the webhook. It corresponds with <WEBHOOK_NAME>. Learn more on how to use it in monitor notifications.

• payload (str, none_type, optional) – If null , uses the default payload. If given a JSON payload, the webhook returns the payload specified by the given payload. Webhooks variable usage.

• url (str) – URL of the webhook.

datadog_api_client.v1.model.webhooks_integration_custom_variable module

class WebhooksIntegrationCustomVariable(arg: None)

class WebhooksIntegrationCustomVariable(arg: ModelComposed)

class WebhooksIntegrationCustomVariable(*args, **kwargs)

Bases: ModelNormal

Custom variable for Webhook integration.

Parameters:

• is_secret (bool) – Make custom variable is secret or not. If the custom variable is secret, the value is not returned in the response payload.

• name (str) – The name of the variable. It corresponds with <CUSTOM_VARIABLE_NAME>.

• value (str) – Value of the custom variable.

datadog_api_client.v1.model.webhooks_integration_custom_variable_response module

class WebhooksIntegrationCustomVariableResponse(arg: None)

class WebhooksIntegrationCustomVariableResponse(arg: ModelComposed)

class WebhooksIntegrationCustomVariableResponse(*args, **kwargs)

Bases: ModelNormal

Custom variable for Webhook integration.

Parameters:

• is_secret (bool) – Make custom variable is secret or not. If the custom variable is secret, the value is not returned in the response payload.

• name (str) – The name of the variable. It corresponds with <CUSTOM_VARIABLE_NAME>. It must only contains upper-case characters, integers or underscores.

• value (str, optional) – Value of the custom variable. It won’t be returned if the variable is secret.

datadog_api_client.v1.model.webhooks_integration_custom_variable_update_request module

class WebhooksIntegrationCustomVariableUpdateRequest(arg: None)

class WebhooksIntegrationCustomVariableUpdateRequest(arg: ModelComposed)

class WebhooksIntegrationCustomVariableUpdateRequest(*args, **kwargs)

Bases: ModelNormal

Update request of a custom variable object.

All properties are optional.

Parameters:

• is_secret (bool, optional) – Make custom variable is secret or not. If the custom variable is secret, the value is not returned in the response payload.

• name (str, optional) – The name of the variable. It corresponds with <CUSTOM_VARIABLE_NAME>. It must only contains upper-case characters, integers or underscores.

• value (str, optional) – Value of the custom variable.

datadog_api_client.v1.model.webhooks_integration_encoding module

class WebhooksIntegrationEncoding(arg: None)

class WebhooksIntegrationEncoding(arg: ModelComposed)

class WebhooksIntegrationEncoding(*args, **kwargs)

Bases: ModelSimple

Encoding type. Can be given either json or form.

Parameters:

• value (str) – If omitted defaults to “json”. Must be one of [“json”, “form”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.webhooks_integration_update_request module

class WebhooksIntegrationUpdateRequest(arg: None)

class WebhooksIntegrationUpdateRequest(arg: ModelComposed)

class WebhooksIntegrationUpdateRequest(*args, **kwargs)

Bases: ModelNormal

Update request of a Webhooks integration object.

All properties are optional.

Parameters:

• custom_headers (str, optional) – If null , uses no header. If given a JSON payload, these will be headers attached to your webhook.

• encode_as (WebhooksIntegrationEncoding, optional) – Encoding type. Can be given either json or form.

• name (str, optional) –

  The name of the webhook. It corresponds with <WEBHOOK_NAME>. Learn more on how to use it in monitor notifications.

• payload (str, none_type, optional) –

  If null , uses the default payload. If given a JSON payload, the webhook returns the payload specified by the given payload. Webhooks variable usage.

• url (str, optional) – URL of the webhook.

datadog_api_client.v1.model.widget module

class Widget(arg: None)

class Widget(arg: ModelComposed)

class Widget(*args, **kwargs)

Bases: ModelNormal

Information about widget.

NoteThe layout property is required for widgets in dashboards with free layout_type.

For the new dashboard layout , the layout property depends on the reflow_type of the dashboard.

- If `reflow_type` is `fixed`, `layout` is required.
- If `reflow_type` is `auto`, `layout` should not be set.

Parameters:

• definition (WidgetDefinition) – Definition of the widget.

• id (int, optional) – ID of the widget.

• layout (WidgetLayout, optional) – The layout for a widget on a free or new dashboard layout dashboard.

datadog_api_client.v1.model.widget_aggregator module

class WidgetAggregator(arg: None)

class WidgetAggregator(arg: ModelComposed)

class WidgetAggregator(*args, **kwargs)

Bases: ModelSimple

Aggregator used for the request.

Parameters:

• value (str) – Must be one of [“avg”, “last”, “max”, “min”, “sum”, “percentile”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_axis module

class WidgetAxis(arg: None)

class WidgetAxis(arg: ModelComposed)

class WidgetAxis(*args, **kwargs)

Bases: ModelNormal

Axis controls for the widget.

Parameters:

• include_zero (bool, optional) – Set to true to include zero.

• label (str, optional) – The label of the axis to display on the graph. Only usable on Scatterplot Widgets.

• max (str, optional) – Specifies maximum numeric value to show on the axis. Defaults to auto.

• min (str, optional) – Specifies minimum numeric value to show on the axis. Defaults to auto.

• scale (str, optional) – Specifies the scale type. Possible values are linear , log , sqrt , and pow## (for example pow2 or pow0.5 ).

datadog_api_client.v1.model.widget_change_type module

class WidgetChangeType(arg: None)

class WidgetChangeType(arg: ModelComposed)

class WidgetChangeType(*args, **kwargs)

Bases: ModelSimple

Show the absolute or the relative change.

Parameters:

• value (str) – Must be one of [“absolute”, “relative”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_color_preference module

class WidgetColorPreference(arg: None)

class WidgetColorPreference(arg: ModelComposed)

class WidgetColorPreference(*args, **kwargs)

Bases: ModelSimple

Which color to use on the widget.

Parameters:

• value (str) – Must be one of [“background”, “text”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_comparator module

class WidgetComparator(arg: None)

class WidgetComparator(arg: ModelComposed)

class WidgetComparator(*args, **kwargs)

Bases: ModelSimple

Comparator to apply.

Parameters:

• value (str) – Must be one of [“=”, “>”, “>=”, “<”, “<=”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_compare_to module

class WidgetCompareTo(arg: None)

class WidgetCompareTo(arg: ModelComposed)

class WidgetCompareTo(*args, **kwargs)

Bases: ModelSimple

Timeframe used for the change comparison.

Parameters:

• value (str) – Must be one of [“hour_before”, “day_before”, “week_before”, “month_before”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_conditional_format module

class WidgetConditionalFormat(arg: None)

class WidgetConditionalFormat(arg: ModelComposed)

class WidgetConditionalFormat(*args, **kwargs)

Bases: ModelNormal

Define a conditional format for the widget.

Parameters:

• comparator (WidgetComparator) – Comparator to apply.

• custom_bg_color (str, optional) – Color palette to apply to the background, same values available as palette.

• custom_fg_color (str, optional) – Color palette to apply to the foreground, same values available as palette.

• hide_value (bool, optional) – True hides values.

• image_url (str, optional) – Displays an image as the background.

• metric (str, optional) – Metric from the request to correlate this conditional format with.

• palette (WidgetPalette) – Color palette to apply.

• timeframe (str, optional) – Defines the displayed timeframe.

• value (float) – Value for the comparator.

datadog_api_client.v1.model.widget_custom_link module

class WidgetCustomLink(arg: None)

class WidgetCustomLink(arg: ModelComposed)

class WidgetCustomLink(*args, **kwargs)

Bases: ModelNormal

Custom links help you connect a data value to a URL, like a Datadog page or your AWS console.

Parameters:

• is_hidden (bool, optional) – The flag for toggling context menu link visibility.

• label (str, optional) – The label for the custom link URL. Keep the label short and descriptive. Use metrics and tags as variables.

• link (str, optional) – The URL of the custom link. URL must include http or https. A relative URL must start with /.

• override_label (str, optional) – The label ID that refers to a context menu link. Can be logs , hosts , traces , profiles , processes , containers , or rum.

datadog_api_client.v1.model.widget_definition module

class WidgetDefinition(arg: None)

class WidgetDefinition(arg: ModelComposed)

class WidgetDefinition(*args, **kwargs)

Bases: ModelComposed

Definition of the widget.

Parameters:

• alert_id (str) – ID of the alert to use in the widget.

• time (WidgetTime, optional) – Time setting for the widget.

• title (str, optional) – The title of the widget.

• title_align (WidgetTextAlign, optional) – How to align the text on the widget.

• title_size (str, optional) – Size of the title.

• type (AlertGraphWidgetDefinitionType) – Type of the alert graph widget.

• viz_type (WidgetVizType) – Whether to display the Alert Graph as a timeseries or a top list.

• precision (int, optional) – Number of decimal to show. If not defined, will use the raw value.

• text_align (WidgetTextAlign, optional) – How to align the text on the widget.

• unit (str, optional) – Unit to display with the value.

• custom_links ([WidgetCustomLink], optional) – List of custom links.

• requests ([ChangeWidgetRequest]) –

  Array of one request object to display in the widget.

  See the dedicated [Request JSON schema documentation](https://docs.datadoghq.com/dashboards/graphing_json/request_json)

  to learn how to build the REQUEST_SCHEMA.

• check (str) – Name of the check to use in the widget.

• group (str, optional) – Group reporting a single check.

• group_by ([str], optional) – List of tag prefixes to group by in the case of a cluster check.

• grouping (WidgetGrouping) – The kind of grouping to use.

• tags ([str], optional) – List of tags used to filter the groups reporting a cluster check.

• legend_size (str, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar.

• markers ([WidgetMarker], optional) – List of markers.

• show_legend (bool, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar.

• xaxis (DistributionWidgetXAxis, optional) – X Axis controls for the distribution widget.

• yaxis (DistributionWidgetYAxis, optional) – Y Axis controls for the distribution widget.

• event_size (WidgetEventSize, optional) – Size to use to display an event.

• query (str) – Query to filter the event stream with.

• tags_execution (str, optional) – The execution method for multi-value filters. Can be either and or or.

• color (str, optional) – Color of the text.

• font_size (str, optional) – Size of the text.

• text (str) – Text to display.

• style (GeomapWidgetDefinitionStyle) – The style to apply to the widget.

• view (GeomapWidgetDefinitionView) – The view of the world that the map should render.

• background_color (str, optional) – Background color of the group title.

• banner_img (str, optional) – URL of image to display as a banner for the group.

• layout_type (WidgetLayoutType) – Layout type of the group.

• show_title (bool, optional) – Whether to show the title or not.

• widgets ([Widget]) – List of widget groups.

• events ([WidgetEvent], optional) – List of widget events.

• no_group_hosts (bool, optional) – Whether to show the hosts that don’t fit in a group.

• no_metric_hosts (bool, optional) – Whether to show the hosts with no metrics.

• node_type (WidgetNodeType, optional) – Which type of node to use in the map.

• notes (str, optional) – Notes on the title.

• scope ([str], optional) – List of tags used to filter the map.

• url (str) – URL of the iframe.

• has_background (bool, optional) – Whether to display a background or not.

• has_border (bool, optional) – Whether to display a border or not.

• horizontal_align (WidgetHorizontalAlign, optional) – Horizontal alignment.

• margin (WidgetMargin, optional) – Size of the margins around the image. Note: small and large values are deprecated.

• sizing (WidgetImageSizing, optional) – How to size the image on the widget. The values are based on the image object-fit CSS properties. Note: zoom, fit and center values are deprecated.

• url_dark_theme (str, optional) – URL of the image in dark mode.

• vertical_align (WidgetVerticalAlign, optional) – Vertical alignment.

• columns ([str], optional) – Which columns to display on the widget.

• indexes ([str], optional) – An array of index names to query in the stream. Use [] to query all indexes at once.

• logset (str, optional) – ID of the log set to use.

• message_display (WidgetMessageDisplay, optional) – Amount of log lines to display

• show_date_column (bool, optional) – Whether to show the date column or not

• show_message_column (bool, optional) – Whether to show the message column or not

• sort (WidgetFieldSort, optional) – Which column and order to sort by

• color_preference (WidgetColorPreference, optional) – Which color to use on the widget.

• count (int, optional) – The number of monitors to display.

• display_format (WidgetMonitorSummaryDisplayFormat, optional) – What to display on the widget.

• hide_zero_counts (bool, optional) – Whether to show counts of 0 or not.

• show_last_triggered (bool, optional) – Whether to show the time that has elapsed since the monitor/group triggered.

• show_priority (bool, optional) – Whether to show the priorities column.

• start (int, optional) – The start of the list. Typically 0.

• summary_type (WidgetSummaryType, optional) – Which summary type should be used.

• content (str) – Content of the note.

• has_padding (bool, optional) – Whether to add padding or not.

• show_tick (bool, optional) – Whether to show a tick or not.

• tick_edge (WidgetTickEdge, optional) – Define how you want to align the text on the widget.

• tick_pos (str, optional) – Where to position the tick on an edge.

• powerpack_id (str) – UUID of the associated powerpack.

• template_variables (PowerpackTemplateVariables, optional) – Powerpack template variables.

• autoscale (bool, optional) – Whether to use auto-scaling or not.

• custom_unit (str, optional) – Display a unit of your choice on the widget.

• timeseries_background (TimeseriesBackground, optional) – Set a timeseries on the widget background.

• inputs ([RunWorkflowWidgetInput], optional) – Array of workflow inputs to map to dashboard template variables.

• workflow_id (str) – Workflow id.

• additional_query_filters (str, optional) – Additional filters applied to the SLO query.

• global_time_target (str, optional) – Defined global time target.

• show_error_budget (bool, optional) – Defined error budget.

• slo_id (str, optional) – ID of the SLO displayed.

• time_windows ([WidgetTimeWindows], optional) – Times being monitored.

• view_mode (WidgetViewMode, optional) – Define how you want the SLO to be displayed.

• view_type (str) – Type of view displayed by the widget.

• color_by_groups ([str], optional) – List of groups used for colors.

• filters ([str]) – Your environment and primary tag (or * if enabled for your account).

• service (str) – The ID of the service you want to map.

• env (str) – APM environment.

• show_breakdown (bool, optional) – Whether to show the latency breakdown or not.

• show_distribution (bool, optional) – Whether to show the latency distribution or not.

• show_errors (bool, optional) – Whether to show the error metrics or not.

• show_hits (bool, optional) – Whether to show the hits metrics or not.

• show_latency (bool, optional) – Whether to show the latency metrics or not.

• show_resource_list (bool, optional) – Whether to show the resource list or not.

• size_format (WidgetSizeFormat, optional) – Size of the widget.

• span_name (str) – APM span name.

• has_uniform_y_axes (bool, optional) – Normalize y axes across graphs

• size (SplitGraphVizSize) – Size of the individual graphs in the split.

• source_widget_definition (SplitGraphSourceWidgetDefinition) – The original widget we are splitting on.

• split_config (SplitConfig) – Encapsulates all user choices about how to split a graph.

• hide_total (bool, optional) – Show the total value in this widget.

• legend (SunburstWidgetLegend, optional) – Configuration of the legend.

• has_search_bar (TableWidgetHasSearchBar, optional) – Controls the display of the search bar.

• legend_columns ([TimeseriesWidgetLegendColumn], optional) – Columns displayed in the legend.

• legend_layout (TimeseriesWidgetLegendLayout, optional) – Layout of the legend.

• right_yaxis (WidgetAxis, optional) – Axis controls for the widget.

• color_by (TreeMapColorBy, optional) – (deprecated) The attribute formerly used to determine color in the widget.

• size_by (TreeMapSizeBy, optional) – (deprecated) The attribute formerly used to determine size in the widget.

datadog_api_client.v1.model.widget_display_type module

class WidgetDisplayType(arg: None)

class WidgetDisplayType(arg: ModelComposed)

class WidgetDisplayType(*args, **kwargs)

Bases: ModelSimple

Type of display to use for the request.

Parameters:

• value (str) – Must be one of [“area”, “bars”, “line”, “overlay”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_event module

class WidgetEvent(arg: None)

class WidgetEvent(arg: ModelComposed)

class WidgetEvent(*args, **kwargs)

Bases: ModelNormal

Event overlay control options.

See the dedicated Events JSON schema documentation to learn how to build the <EVENTS_SCHEMA>.

Parameters:

• q (str) – Query definition.

• tags_execution (str, optional) – The execution method for multi-value filters.

datadog_api_client.v1.model.widget_event_size module

class WidgetEventSize(arg: None)

class WidgetEventSize(arg: ModelComposed)

class WidgetEventSize(*args, **kwargs)

Bases: ModelSimple

Size to use to display an event.

Parameters:

• value (str) – Must be one of [“s”, “l”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_field_sort module

class WidgetFieldSort(arg: None)

class WidgetFieldSort(arg: ModelComposed)

class WidgetFieldSort(*args, **kwargs)

Bases: ModelNormal

Which column and order to sort by

Parameters:

• column (str) – Facet path for the column

• order (WidgetSort) – Widget sorting methods.

datadog_api_client.v1.model.widget_formula module

class WidgetFormula(arg: None)

class WidgetFormula(arg: ModelComposed)

class WidgetFormula(*args, **kwargs)

Bases: ModelNormal

Formula to be used in a widget query.

Parameters:

• alias (str, optional) – Expression alias.

• cell_display_mode (TableWidgetCellDisplayMode, optional) – Define a display mode for the table cell.

• cell_display_mode_options (WidgetFormulaCellDisplayModeOptions, optional) – Cell display mode options for the widget formula. (only if cell_display_mode is set to trend ).

• conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.

• formula (str) – String expression built from queries, formulas, and functions.

• limit (WidgetFormulaLimit, optional) – Options for limiting results returned.

• number_format (WidgetNumberFormat, optional) – Number format options for the widget.

• style (WidgetFormulaStyle, optional) – Styling options for widget formulas.

datadog_api_client.v1.model.widget_formula_cell_display_mode_options module

class WidgetFormulaCellDisplayModeOptions(arg: None)

class WidgetFormulaCellDisplayModeOptions(arg: ModelComposed)

class WidgetFormulaCellDisplayModeOptions(*args, **kwargs)

Bases: ModelNormal

Cell display mode options for the widget formula. (only if cell_display_mode is set to trend ).

Parameters:

• trend_type (WidgetFormulaCellDisplayModeOptionsTrendType, optional) – Trend type for the cell display mode options.

• y_scale (WidgetFormulaCellDisplayModeOptionsYScale, optional) – Y scale for the cell display mode options.

datadog_api_client.v1.model.widget_formula_cell_display_mode_options_trend_type module

class WidgetFormulaCellDisplayModeOptionsTrendType(arg: None)

class WidgetFormulaCellDisplayModeOptionsTrendType(arg: ModelComposed)

class WidgetFormulaCellDisplayModeOptionsTrendType(*args, **kwargs)

Bases: ModelSimple

Trend type for the cell display mode options.

Parameters:

• value (str) – Must be one of [“area”, “line”, “bars”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_formula_cell_display_mode_options_y_scale module

class WidgetFormulaCellDisplayModeOptionsYScale(arg: None)

class WidgetFormulaCellDisplayModeOptionsYScale(arg: ModelComposed)

class WidgetFormulaCellDisplayModeOptionsYScale(*args, **kwargs)

Bases: ModelSimple

Y scale for the cell display mode options.

Parameters:

• value (str) – Must be one of [“shared”, “independent”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_formula_limit module

class WidgetFormulaLimit(arg: None)

class WidgetFormulaLimit(arg: ModelComposed)

class WidgetFormulaLimit(*args, **kwargs)

Bases: ModelNormal

Options for limiting results returned.

Parameters:

• count (int, optional) – Number of results to return.

• order (QuerySortOrder, optional) – Direction of sort.

datadog_api_client.v1.model.widget_formula_sort module

class WidgetFormulaSort(arg: None)

class WidgetFormulaSort(arg: ModelComposed)

class WidgetFormulaSort(*args, **kwargs)

Bases: ModelNormal

The formula to sort the widget by.

Parameters:

• index (int) – The index of the formula to sort by.

• order (WidgetSort) – Widget sorting methods.

• type (FormulaType) – Set the sort type to formula.

datadog_api_client.v1.model.widget_formula_style module

class WidgetFormulaStyle(arg: None)

class WidgetFormulaStyle(arg: ModelComposed)

class WidgetFormulaStyle(*args, **kwargs)

Bases: ModelNormal

Styling options for widget formulas.

Parameters:

• palette (str, optional) – The color palette used to display the formula. A guide to the available color palettes can be found at https://docs.datadoghq.com/dashboards/guide/widget_colors

• palette_index (int, optional) – Index specifying which color to use within the palette.

datadog_api_client.v1.model.widget_group_sort module

class WidgetGroupSort(arg: None)

class WidgetGroupSort(arg: ModelComposed)

class WidgetGroupSort(*args, **kwargs)

Bases: ModelNormal

The group to sort the widget by.

Parameters:

• name (str) – The name of the group.

• order (WidgetSort) – Widget sorting methods.

• type (GroupType) – Set the sort type to group.

datadog_api_client.v1.model.widget_grouping module

class WidgetGrouping(arg: None)

class WidgetGrouping(arg: ModelComposed)

class WidgetGrouping(*args, **kwargs)

Bases: ModelSimple

The kind of grouping to use.

Parameters:

• value (str) – Must be one of [“check”, “cluster”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_horizontal_align module

class WidgetHorizontalAlign(arg: None)

class WidgetHorizontalAlign(arg: ModelComposed)

class WidgetHorizontalAlign(*args, **kwargs)

Bases: ModelSimple

Horizontal alignment.

Parameters:

• value (str) – Must be one of [“center”, “left”, “right”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_image_sizing module

class WidgetImageSizing(arg: None)

class WidgetImageSizing(arg: ModelComposed)

class WidgetImageSizing(*args, **kwargs)

Bases: ModelSimple

How to size the image on the widget. The values are based on the image object-fit CSS properties.

Note: zoom, fit and center values are deprecated.

Parameters:

• value (str) – Must be one of [“fill”, “contain”, “cover”, “none”, “scale-down”, “zoom”, “fit”, “center”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_layout module

class WidgetLayout(arg: None)

class WidgetLayout(arg: ModelComposed)

class WidgetLayout(*args, **kwargs)

Bases: ModelNormal

The layout for a widget on a free or new dashboard layout dashboard.

Parameters:

• height (int) – The height of the widget. Should be a non-negative integer.

• is_column_break (bool, optional) – Whether the widget should be the first one on the second column in high density or not. Note : Only for the new dashboard layout and only one widget in the dashboard should have this property set to true.

• width (int) – The width of the widget. Should be a non-negative integer.

• x (int) – The position of the widget on the x (horizontal) axis. Should be a non-negative integer.

• y (int) – The position of the widget on the y (vertical) axis. Should be a non-negative integer.

datadog_api_client.v1.model.widget_layout_type module

class WidgetLayoutType(arg: None)

class WidgetLayoutType(arg: ModelComposed)

class WidgetLayoutType(*args, **kwargs)

Bases: ModelSimple

Layout type of the group.

Parameters:

• value (str) – If omitted defaults to “ordered”. Must be one of [“ordered”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_legacy_live_span module

class WidgetLegacyLiveSpan(arg: None)

class WidgetLegacyLiveSpan(arg: ModelComposed)

class WidgetLegacyLiveSpan(*args, **kwargs)

Bases: ModelNormal

Wrapper for live span

Parameters:

• hide_incomplete_cost_data (bool, optional) – Whether to hide incomplete cost data in the widget.

• live_span (WidgetLiveSpan, optional) – The available timeframes depend on the widget you are using.

additional_properties_type = None

datadog_api_client.v1.model.widget_line_type module

class WidgetLineType(arg: None)

class WidgetLineType(arg: ModelComposed)

class WidgetLineType(*args, **kwargs)

Bases: ModelSimple

Type of lines displayed.

Parameters:

• value (str) – Must be one of [“dashed”, “dotted”, “solid”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_line_width module

class WidgetLineWidth(arg: None)

class WidgetLineWidth(arg: ModelComposed)

class WidgetLineWidth(*args, **kwargs)

Bases: ModelSimple

Width of line displayed.

Parameters:

• value (str) – Must be one of [“normal”, “thick”, “thin”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_live_span module

class WidgetLiveSpan(arg: None)

class WidgetLiveSpan(arg: ModelComposed)

class WidgetLiveSpan(*args, **kwargs)

Bases: ModelSimple

The available timeframes depend on the widget you are using.

Parameters:

• value (str) – Must be one of [“1m”, “5m”, “10m”, “15m”, “30m”, “1h”, “4h”, “1d”, “2d”, “1w”, “1mo”, “3mo”, “6mo”, “week_to_date”, “month_to_date”, “1y”, “alert”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_live_span_unit module

class WidgetLiveSpanUnit(arg: None)

class WidgetLiveSpanUnit(arg: ModelComposed)

class WidgetLiveSpanUnit(*args, **kwargs)

Bases: ModelSimple

Unit of the time span.

Parameters:

• value (str) – Must be one of [“minute”, “hour”, “day”, “week”, “month”, “year”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_margin module

class WidgetMargin(arg: None)

class WidgetMargin(arg: ModelComposed)

class WidgetMargin(*args, **kwargs)

Bases: ModelSimple

Size of the margins around the image.

Note: small and large values are deprecated.

Parameters:

• value (str) – Must be one of [“sm”, “md”, “lg”, “small”, “large”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_marker module

class WidgetMarker(arg: None)

class WidgetMarker(arg: ModelComposed)

class WidgetMarker(*args, **kwargs)

Bases: ModelNormal

Markers allow you to add visual conditional formatting for your graphs.

Parameters:

• display_type (str, optional) –

  Combination of:

  • A severity error, warning, ok, or info

  • A line type: dashed, solid, or bold In this case of a Distribution widget, this can be set to be x_axis_percentile.

• label (str, optional) – Label to display over the marker.

• time (str, optional) – Timestamp for the widget.

• value (str) – Value to apply. Can be a single value y = 15 or a range of values 0 < y < 10.

datadog_api_client.v1.model.widget_message_display module

class WidgetMessageDisplay(arg: None)

class WidgetMessageDisplay(arg: ModelComposed)

class WidgetMessageDisplay(*args, **kwargs)

Bases: ModelSimple

Amount of log lines to display

Parameters:

• value (str) – Must be one of [“inline”, “expanded-md”, “expanded-lg”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_monitor_summary_display_format module

class WidgetMonitorSummaryDisplayFormat(arg: None)

class WidgetMonitorSummaryDisplayFormat(arg: ModelComposed)

class WidgetMonitorSummaryDisplayFormat(*args, **kwargs)

Bases: ModelSimple

What to display on the widget.

Parameters:

• value (str) – Must be one of [“counts”, “countsAndList”, “list”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_monitor_summary_sort module

class WidgetMonitorSummarySort(arg: None)

class WidgetMonitorSummarySort(arg: ModelComposed)

class WidgetMonitorSummarySort(*args, **kwargs)

Bases: ModelSimple

Widget sorting methods.

Parameters:

• value (str) – Must be one of [“name”, “group”, “status”, “tags”, “triggered”, “group,asc”, “group,desc”, “name,asc”, “name,desc”, “status,asc”, “status,desc”, “tags,asc”, “tags,desc”, “triggered,asc”, “triggered,desc”, “priority,asc”, “priority,desc”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_new_fixed_span module

class WidgetNewFixedSpan(arg: None)

class WidgetNewFixedSpan(arg: ModelComposed)

class WidgetNewFixedSpan(*args, **kwargs)

Bases: ModelNormal

Used for fixed span times, such as ‘March 1 to March 7’.

Parameters:

• _from (int) – Start time in seconds since epoch.

• hide_incomplete_cost_data (bool, optional) – Whether to hide incomplete cost data in the widget.

• to (int) – End time in seconds since epoch.

• type (WidgetNewFixedSpanType) – Type “fixed” denotes a fixed span.

datadog_api_client.v1.model.widget_new_fixed_span_type module

class WidgetNewFixedSpanType(arg: None)

class WidgetNewFixedSpanType(arg: ModelComposed)

class WidgetNewFixedSpanType(*args, **kwargs)

Bases: ModelSimple

Type “fixed” denotes a fixed span.

Parameters:

• value (str) – If omitted defaults to “fixed”. Must be one of [“fixed”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_new_live_span module

class WidgetNewLiveSpan(arg: None)

class WidgetNewLiveSpan(arg: ModelComposed)

class WidgetNewLiveSpan(*args, **kwargs)

Bases: ModelNormal

Used for arbitrary live span times, such as 17 minutes or 6 hours.

Parameters:

• hide_incomplete_cost_data (bool, optional) – Whether to hide incomplete cost data in the widget.

• type (WidgetNewLiveSpanType) – Type “live” denotes a live span in the new format.

• unit (WidgetLiveSpanUnit) – Unit of the time span.

• value (int) – Value of the time span.

datadog_api_client.v1.model.widget_new_live_span_type module

class WidgetNewLiveSpanType(arg: None)

class WidgetNewLiveSpanType(arg: ModelComposed)

class WidgetNewLiveSpanType(*args, **kwargs)

Bases: ModelSimple

Type “live” denotes a live span in the new format.

Parameters:

• value (str) – If omitted defaults to “live”. Must be one of [“live”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_node_type module

class WidgetNodeType(arg: None)

class WidgetNodeType(arg: ModelComposed)

class WidgetNodeType(*args, **kwargs)

Bases: ModelSimple

Which type of node to use in the map.

Parameters:

• value (str) – Must be one of [“host”, “container”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_number_format module

class WidgetNumberFormat(arg: None)

class WidgetNumberFormat(arg: ModelComposed)

class WidgetNumberFormat(*args, **kwargs)

Bases: ModelNormal

Number format options for the widget.

Parameters:

• unit (NumberFormatUnit, optional) – Number format unit.

• unit_scale (NumberFormatUnitScale, none_type, optional) – The definition of NumberFormatUnitScale object.

datadog_api_client.v1.model.widget_order_by module

class WidgetOrderBy(arg: None)

class WidgetOrderBy(arg: ModelComposed)

class WidgetOrderBy(*args, **kwargs)

Bases: ModelSimple

What to order by.

Parameters:

• value (str) – Must be one of [“change”, “name”, “present”, “past”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_palette module

class WidgetPalette(arg: None)

class WidgetPalette(arg: ModelComposed)

class WidgetPalette(*args, **kwargs)

Bases: ModelSimple

Color palette to apply.

Parameters:

• value (str) – Must be one of [“blue”, “custom_bg”, “custom_image”, “custom_text”, “gray_on_white”, “grey”, “green”, “orange”, “red”, “red_on_white”, “white_on_gray”, “white_on_green”, “green_on_white”, “white_on_red”, “white_on_yellow”, “yellow_on_white”, “black_on_light_yellow”, “black_on_light_green”, “black_on_light_red”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_request_style module

class WidgetRequestStyle(arg: None)

class WidgetRequestStyle(arg: ModelComposed)

class WidgetRequestStyle(*args, **kwargs)

Bases: ModelNormal

Define request widget style.

Parameters:

• line_type (WidgetLineType, optional) – Type of lines displayed.

• line_width (WidgetLineWidth, optional) – Width of line displayed.

• palette (str, optional) – Color palette to apply to the widget.

datadog_api_client.v1.model.widget_service_summary_display_format module

class WidgetServiceSummaryDisplayFormat(arg: None)

class WidgetServiceSummaryDisplayFormat(arg: ModelComposed)

class WidgetServiceSummaryDisplayFormat(*args, **kwargs)

Bases: ModelSimple

Number of columns to display.

Parameters:

• value (str) – Must be one of [“one_column”, “two_column”, “three_column”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_size_format module

class WidgetSizeFormat(arg: None)

class WidgetSizeFormat(arg: ModelComposed)

class WidgetSizeFormat(*args, **kwargs)

Bases: ModelSimple

Size of the widget.

Parameters:

• value (str) – Must be one of [“small”, “medium”, “large”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_sort module

class WidgetSort(arg: None)

class WidgetSort(arg: ModelComposed)

class WidgetSort(*args, **kwargs)

Bases: ModelSimple

Widget sorting methods.

Parameters:

• value (str) – Must be one of [“asc”, “desc”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_sort_by module

class WidgetSortBy(arg: None)

class WidgetSortBy(arg: ModelComposed)

class WidgetSortBy(*args, **kwargs)

Bases: ModelNormal

The controls for sorting the widget.

Parameters:

• count (int, optional) – The number of items to limit the widget to.

• order_by ([WidgetSortOrderBy], optional) – The array of items to sort the widget by in order.

datadog_api_client.v1.model.widget_sort_order_by module

class WidgetSortOrderBy(arg: None)

class WidgetSortOrderBy(arg: ModelComposed)

class WidgetSortOrderBy(*args, **kwargs)

Bases: ModelComposed

The item to sort the widget by.

Parameters:

• index (int) – The index of the formula to sort by.

• order (WidgetSort) – Widget sorting methods.

• type (FormulaType) – Set the sort type to formula.

• name (str) – The name of the group.

datadog_api_client.v1.model.widget_style module

class WidgetStyle(arg: None)

class WidgetStyle(arg: ModelComposed)

class WidgetStyle(*args, **kwargs)

Bases: ModelNormal

Widget style definition.

Parameters:

palette (str, optional) – Color palette to apply to the widget.

datadog_api_client.v1.model.widget_summary_type module

class WidgetSummaryType(arg: None)

class WidgetSummaryType(arg: ModelComposed)

class WidgetSummaryType(*args, **kwargs)

Bases: ModelSimple

Which summary type should be used.

Parameters:

• value (str) – Must be one of [“monitors”, “groups”, “combined”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_text_align module

class WidgetTextAlign(arg: None)

class WidgetTextAlign(arg: ModelComposed)

class WidgetTextAlign(*args, **kwargs)

Bases: ModelSimple

How to align the text on the widget.

Parameters:

• value (str) – Must be one of [“center”, “left”, “right”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_tick_edge module

class WidgetTickEdge(arg: None)

class WidgetTickEdge(arg: ModelComposed)

class WidgetTickEdge(*args, **kwargs)

Bases: ModelSimple

Define how you want to align the text on the widget.

Parameters:

• value (str) – Must be one of [“bottom”, “left”, “right”, “top”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_time module

class WidgetTime(arg: None)

class WidgetTime(arg: ModelComposed)

class WidgetTime(*args, **kwargs)

Bases: ModelComposed

Time setting for the widget.

Parameters:

• hide_incomplete_cost_data (bool, optional) – Whether to hide incomplete cost data in the widget.

• live_span (WidgetLiveSpan, optional) – The available timeframes depend on the widget you are using.

• type (WidgetNewLiveSpanType) – Type “live” denotes a live span in the new format.

• unit (WidgetLiveSpanUnit) – Unit of the time span.

• value (int) – Value of the time span.

• _from (int) – Start time in seconds since epoch.

• to (int) – End time in seconds since epoch.

datadog_api_client.v1.model.widget_time_windows module

class WidgetTimeWindows(arg: None)

class WidgetTimeWindows(arg: ModelComposed)

class WidgetTimeWindows(*args, **kwargs)

Bases: ModelSimple

Define a time window.

Parameters:

• value (str) – Must be one of [“7d”, “30d”, “90d”, “week_to_date”, “previous_week”, “month_to_date”, “previous_month”, “global_time”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_vertical_align module

class WidgetVerticalAlign(arg: None)

class WidgetVerticalAlign(arg: ModelComposed)

class WidgetVerticalAlign(*args, **kwargs)

Bases: ModelSimple

Vertical alignment.

Parameters:

• value (str) – Must be one of [“center”, “top”, “bottom”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_view_mode module

class WidgetViewMode(arg: None)

class WidgetViewMode(arg: ModelComposed)

class WidgetViewMode(*args, **kwargs)

Bases: ModelSimple

Define how you want the SLO to be displayed.

Parameters:

• value (str) – Must be one of [“overall”, “component”, “both”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

datadog_api_client.v1.model.widget_viz_type module

class WidgetVizType(arg: None)

class WidgetVizType(arg: ModelComposed)

class WidgetVizType(*args, **kwargs)

Bases: ModelSimple

Whether to display the Alert Graph as a timeseries or a top list.

Parameters:

• value (str) – Must be one of [“timeseries”, “toplist”].

• _check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.

• _path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.

• _spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).

• _configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

Module contents