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Various validations are ran to check for correctness. There is a reusable workflow that repositories may call with input parameters defining which validations to use, with each input parameter corresponding to a subcommand under the ddev validate command group.

Agent requirements

ddev validate agent-reqs

This validates that each integration version is in sync with the requirements-agent-release.txt file. It is uncommon for this to fail because the release process is automated.

CI configuration

ddev validate ci

This validates that all CI entries for integrations are valid. This includes checking if the integration has the correct Codecov config, and has a valid CI entry if it is testable.


Run ddev validate ci --sync to resolve most errors.


ddev validate codeowners

This validates that every integration has a codeowner entry. If this validation fails, add an entry in the codewners file corresponding to any newly added integration.


This validation is only enabled for integrations-extras.

Default configuration files

ddev validate config

This verifies that the config specs for all integrations are valid by enforcing our configuration spec schema. The most common failure is some version of File <INTEGRATION_SPEC> needs to be synced. To resolve this issue, you can run ddev validate config --sync

If you see failures regarding formatting or missing parameters, see our config spec documentation for more details on how to construct configuration specs.

Dashboard definition files

ddev validate dashboards

This validates that dashboards are formatted correctly. This means that they need to be proper JSON and generated from Datadog's /dashboard API.


If you see a failure regarding use of the screen endpoint, consider using our dashboard utility command to generate your dashboard payload.


ddev validate dep

This command:

  • Verifies the uniqueness of dependency versions across all checks.
  • Verifies all the dependencies are pinned.
  • Verifies the embedded Python environment defined in the base check and requirements listed in every integration are compatible.

This validation only applies if your work introduces new external dependencies.

Manifest files

ddev validate manifest

This validates that the manifest files contain required fields, are formatted correctly, and don't contain common errors. See the Datadog docs for more detailed constraints.


ddev validate metadata

This checks that every metadata.csv file is formatted correctly. See the Datadog docs for more detailed constraints.

README files

ddev validate readmes

This ensures that every integration's file is formatted correctly. The main purpose of this validation is to ensure that any image linked in the readme exists and that all images are located in an integration's /image directory.

Saved views data

ddev validate saved-views

This validates that saved views for an integration are formatted correctly and contain required fields, such as "type".


View example saved views for inspiration and guidance.

Service check data

ddev validate service-checks

This checks that every service check file is formatted correctly. See the Datadog docs for more specific constraints.


ddev validate imports

This verifies that all integrations import the base package in the correct way, such as:

from import bar


See the New Integration Instructions for more examples of how to use the base package.

Last update: April 20, 2023