Optional requestFactory: MonitorsApiRequestFactoryOptional responseProcessor: MonitorsApiResponseProcessorPrivate configurationPrivate requestPrivate responseThe request object
Optional options: ConfigurationCreate a monitor using the specified options.
The type of monitor chosen from:
query alertquery alert or trace-analytics alertcompositeservice checkquery alertservice checkquery alert or service checkprocess alertlog alertquery alertservice checkquery alertservice checkrum alertslo alertevent-v2 alertevent-v2 alertaudit alerterror-tracking alertdatabase-monitoring alertnetwork-performance alertcost alertNotes:
Example: time_aggr(time_window):space_aggr:metric{tags} [by {key}] operator #
time_aggr: avg, sum, max, min, change, or pct_changetime_window: last_#m (with # between 1 and 10080 depending on the monitor type) or last_#h(with # between 1 and 168 depending on the monitor type) or last_1d, or last_1wspace_aggr: avg, sum, min, or maxtags: one or more tags (comma-separated), or *key: a 'key' in key:value tag syntax; defines a separate alert for each tag in the group (multi-alert)operator: <, <=, >, >=, ==, or !=#: an integer or decimal number used to set the thresholdIf you are using the _change_ or _pct_change_ time aggregator, instead use change_aggr(time_aggr(time_window), timeshift):space_aggr:metric{tags} [by {key}] operator # with:
change_aggr change, pct_changetime_aggr avg, sum, max, min Learn moretime_window last_#m (between 1 and 2880 depending on the monitor type), last_#h (between 1 and 48 depending on the monitor type), or last_#d (1 or 2)timeshift #m_ago (5, 10, 15, or 30), #h_ago (1, 2, or 4), or 1d_agoUse this to create an outlier monitor using the following query:
avg(last_30m):outliers(avg:system.cpu.user{role:es-events-data} by {host}, 'dbscan', 7) > 0
Example: "check".over(tags).last(count).by(group).count_by_status()
check name of the check, for example datadog.agent.uptags one or more quoted tags (comma-separated), or "*". for example: .over("env:prod", "role:db"); over cannot be blank.count must be at greater than or equal to your max threshold (defined in the options). It is limited to 100.
For example, if you've specified to notify on 1 critical, 3 ok, and 2 warn statuses, count should be at least 3.group must be specified for check monitors. Per-check grouping is already explicitly known for some service checks.
For example, Postgres integration monitors are tagged by db, host, and port, and Network monitors by host, instance, and url. See Service Checks documentation for more information.Note: The Event Alert Query has been replaced by the Event V2 Alert Query. For more information, see the Event Migration guide.
Example: events(query).rollup(rollup_method[, measure]).last(time_window) operator #
query The search query - following the Log search syntax.rollup_method The stats roll-up method - supports count, avg and cardinality.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold.Example: processes(search).over(tags).rollup('count').last(timeframe) operator #
search free text search string for querying processes.
Matching processes match results on the Live Processes page.tags one or more tags (comma-separated)timeframe the timeframe to roll up the counts. Examples: 10m, 4h. Supported timeframes: s, m, h and doperator <, <=, >, >=, ==, or !=# an integer or decimal number used to set the thresholdExample: logs(query).index(index_name).rollup(rollup_method[, measure]).last(time_window) operator #
query The search query - following the Log search syntax.index_name For multi-index organizations, the log index in which the request is performed.rollup_method The stats roll-up method - supports count, avg and cardinality.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold.Example: 12345 && 67890, where 12345 and 67890 are the IDs of non-composite monitors
name [required, default = dynamic, based on query]: The name of the alert.message [required, default = dynamic, based on query]: A message to include with notifications for this monitor.
Email notifications can be sent to specific users by using the same '@username' notation as events.tags [optional, default = empty list]: A list of tags to associate with your monitor.
When getting all monitor details via the API, use the monitor_tags argument to filter results by these tags.
It is only available via the API and isn't visible or editable in the Datadog UI.Example: error_budget("slo_id").over("time_window") operator #
slo_id: The alphanumeric SLO ID of the SLO you are configuring the alert for.time_window: The time window of the SLO target you wish to alert on. Valid options: 7d, 30d, 90d.operator: >= or >Example: audits(query).rollup(rollup_method[, measure]).last(time_window) operator #
query The search query - following the Log search syntax.rollup_method The stats roll-up method - supports count, avg and cardinality.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold.Example: ci-pipelines(query).rollup(rollup_method[, measure]).last(time_window) operator #
query The search query - following the Log search syntax.rollup_method The stats roll-up method - supports count, avg, and cardinality.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold.Example: ci-tests(query).rollup(rollup_method[, measure]).last(time_window) operator #
query The search query - following the Log search syntax.rollup_method The stats roll-up method - supports count, avg, and cardinality.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold."New issue" example: error-tracking(query).source(issue_source).new().rollup(rollup_method[, measure]).by(group_by).last(time_window) operator #
"High impact issue" example: error-tracking(query).source(issue_source).impact().rollup(rollup_method[, measure]).by(group_by).last(time_window) operator #
query The search query - following the Log search syntax.issue_source The issue source - supports all, browser, mobile and backend and defaults to all if omitted.rollup_method The stats roll-up method - supports count, avg, and cardinality and defaults to count if omitted.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.group by Comma-separated list of attributes to group by - should contain at least issue.id.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold.Database Monitoring Alert Query
Example: database-monitoring(query).rollup(rollup_method[, measure]).last(time_window) operator #
query The search query - following the Log search syntax.rollup_method The stats roll-up method - supports count, avg, and cardinality.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold.Network Performance Alert Query
Example: network-performance(query).rollup(rollup_method[, measure]).last(time_window) operator #
query The search query - following the Log search syntax.rollup_method The stats roll-up method - supports count, avg, and cardinality.measure For avg and cardinality rollup_method - specify the measure or the facet name you want to use.time_window #m (between 1 and 2880), #h (between 1 and 48).operator <, <=, >, >=, ==, or !=.# an integer or decimal number used to set the threshold.The request object
Optional options: ConfigurationDelete the specified monitor
The request object
Optional options: ConfigurationGet details about the specified monitor from your organization.
The request object
Optional options: ConfigurationGet details about the specified monitor from your organization.
The request object
Optional options: ConfigurationProvide a paginated version of listMonitors returning a generator with all the items.
Optional options: ConfigurationSearch and filter your monitor groups details.
The request object
Optional options: ConfigurationSearch and filter your monitors details.
The request object
Optional options: ConfigurationEdit the specified monitor.
The request object
Optional options: ConfigurationValidate the monitor provided in the request.
The request object
Optional options: ConfigurationValidate the monitor provided in the request.
Note: Log monitors require an unscoped App Key.
The request object
Optional options: ConfigurationGenerated using TypeDoc
Check if the given monitors can be deleted.