> For the complete documentation index, see [llms.txt](https://docs.baz.co/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.baz.co/basics/integrations/datadog.md).

# Datadog

When Datadog is connected, Baz validates the integration during setup and uses production issues from Datadog to identify recurring problems and open fix PRs in the mapped repositories.

#### Simple setup flow

1. Open the Datadog integration settings in Baz.
2. Enter your Datadog API key and Application key.
3. Select the correct Datadog base URL for your region.
4. Save the integration.
5. Make sure the relevant repositories are connected to Baz with write access.
6. Make sure sandbox is enabled for the repositories where Baz should open SRE PRs.
7. Enable the SRE agent for the org.
8. Add service-to-repository mapping where needed so Baz can connect production issues to the right codebase.

#### What Baz checks during setup

Baz validates that:

* the credentials are valid
* the Datadog workspace is reachable
* the integration has enough access for the SRE agent to work

If the setup is valid, Baz can use Datadog findings as input for the SRE flow.

#### What is required for SRE PRs to work

A connected Datadog integration is only one part of the flow.

Baz also needs:

* the target repositories connected in Baz
* GitHub write access for those repositories
* sandbox configured for those repositories
* SRE agent enabled for the org
* service-to-repository mapping when the service name does not resolve automatically

#### Common reasons it does not work

* The Datadog credentials are valid, but the integration does not have enough access.
* The repositories are not connected with write access.
* Sandbox is missing for the target repository.
* The SRE agent is disabled for the org.
* Baz cannot map the Datadog service to the correct repository.


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