For AI agents: A markdown version of this page is available at https://docs.datadoghq.com/tests/setup/bazel.md. A documentation index is available at /llms.txt.

Configure Test Optimization with Bazel

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Datadog provides official Bazel rules for Test Optimization. Use these rules to configure Bazel test targets. The rules read Test Optimization metadata, write local payload files during test execution, and upload test results to Datadog after Bazel tests complete. See all rules in the DataDog/rules_test_optimization repository.

The Bazel integration keeps Datadog metadata fetches outside test execution. During module or repository resolution, Bazel fetches Test Optimization metadata from Datadog and exposes it through a generated repository. During test execution, language-specific macros pass the metadata location to the test process and configure payloads to be written under TEST_UNDECLARED_OUTPUTS_DIR. After tests finish, run the doctor and uploader targets with bazel run.

Test Impact Analysis and automatic coverage configuration are not supported for Bazel.

Language setup pages

Use the language-specific setup page for your Bazel test targets:

Java
Python
Go

Compatibility

This section includes setup pages for the following language test targets:

LanguageBazel macroNotes
Javadd_topt_java_testRequires a dd-java-agent JAR label. See Java compatibility.
Pythondd_topt_py_testSupports the managed pytest runner and repository-owned pytest wrappers. See Python compatibility.
Godd_topt_go_testUse test_optimization mode for the faster standard-library testing path, or general mode for broader Orchestrion support. See Go compatibility.

Use datadog-rules-test-optimization version 1.2.0 and the commit pin shown on each language setup page.

How the Bazel setup flow works

For detailed setup guides, see the language-specific setup pages. On a high level, the Bazel setup has four parts:

  1. Add the datadog-rules-test-optimization module and the companion module for your language to MODULE.bazel.
  2. Configure a sync repository with your Datadog service name, runtime name, and runtime version.
  3. Replace the language test rule with the Datadog Bazel macro for each instrumented test target.
  4. Run tests, validate local payloads with the doctor target, validate enrichment with the uploader dry run, and then upload payloads.

For remote execution, configure Bazel to download test outputs locally:

test:test-optimization --remote_download_outputs=all

Without local test.outputs directories, the doctor and uploader cannot inspect payload files after bazel test.

Upload payloads

Run the upload flow after your Bazel tests complete. Replace //tools/test_optimization with the package where you declared the doctor and uploader targets:

bazel test --config=test-optimization //...
bazel run --config=test-optimization //tools/test_optimization:dd_test_optimization_doctor
bazel run --config=test-optimization //tools/test_optimization:dd_upload_payloads -- --dry-run --validate-enrichment
DD_API_KEY=<DATADOG_API_KEY> DD_SITE=<DATADOG_SITE> bazel run --config=test-optimization //tools/test_optimization:dd_upload_payloads

Do not pass DD_API_KEY, DD_SITE, DD_GIT_*, or upload endpoint variables through --test_env. Forward sync metadata with --repo_env, and pass upload credentials only to the uploader runtime.

Further reading

Additional helpful documentation, links, and articles:

Configure Test OptimizationDOCUMENTATION more more Explore Test Results and PerformanceDOCUMENTATION more more Troubleshooting Test OptimizationDOCUMENTATION more more