Troubleshooting CI Visibility

Your Jenkins instance is instrumented, but Datadog isn’t showing any data

1. Make sure that at least one pipeline has finished executing. Pipeline execution information is only sent after the pipeline has finished.
2. Make sure the Datadog Agent host is properly configured and it’s reachable by the Datadog Plugin. You can test connectivity by clicking on the Check connectivity with the Datadog Agent button on the Jenkins plugin configuration UI.
3. Check for any errors in the Jenkins logs. You can enable debug-level logs for the Datadog plugin by creating a logging.properties file and adding the line: org.datadog.level = ALL.
4. If you still don’t see any results, contact Support for troubleshooting help.

Your tests are instrumented, but Datadog isn’t showing any data

1. Go to the Setup Tracing on CI Tests page for the language you’re instrumenting and check the Compatibility section. Make sure the testing framework you are using is supported.
2. Check if you see any test results in the Test Runs section. If you do see results there, but not in the Tests section, Git information is missing. See Data appears in Test Runs but not Tests to troubleshoot it.
3. If you are reporting the data through the Datadog Agent, make sure it is running on the host where tests are run (accessible at localhost:8126), or if accessible on another hostname or port, make sure you run your tests with the appropriate Agent hostname set in the DD_AGENT_HOST and the appropriate port in DD_TRACE_AGENT_PORT environment variables. You can activate debug mode in the tracer to check if it’s able to connect to the Agent.
4. If you still don’t see any results, contact Support for troubleshooting help.

Pipeline not found

A “Pipeline not found” message is shown when you click on incomplete data coming from an in-progress pipeline. Data is received progressively for stages, jobs, or custom commands. Wait until the pipeline has finished and try again.

Data appears in test runs but not tests

If you can see test results data in the Test Runs tab, but not the Tests tab, Git metadata (repository, commit and/or branch) is probably missing. To confirm this is the case, open a test execution in the Test Runs section, and check that there is no git.repository_url, git.commit.sha, or git.branch. If these tags are not populated, nothing shows in the Tests section.

1. Tracers first use the environment variables, if any, set by the CI provider to collect Git information. See Running tests inside a container for a list of environment variables that the tracer attempts to read for each supported CI provider. At a minimum, this populates the repository, commit hash, and branch information.

2. Next, tracers fetch Git metadata using the local .git folder, if present, by executing git commands. This populates all Git metadata fields, including commit message, author, and committer information. Ensure the .git folder is present and the git binary is installed and in $PATH. This information is used to populate attributes not detected in the previous step.

3. You can also provide Git information manually using environment variables, which override information detected by any of the previous steps. The supported environment variables for providing Git information are the following:

   DD_GIT_REPOSITORY_URL (required)

   URL of the repository where the code is stored. Both HTTP and SSH URLs are supported.
   Example: git@github.com:MyCompany/MyApp.git, https://github.com/MyCompany/MyApp.git

   DD_GIT_COMMIT_SHA (required)

   Full (40-character long SHA1) commit hash.
   Example: a18ebf361cc831f5535e58ec4fae04ffd98d8152

   DD_GIT_BRANCH

   Git branch being tested. Leave empty if providing tag information instead.
   Example: develop

   DD_GIT_TAG

   Git tag being tested (if applicable). Leave empty if providing branch information instead.
   Example: 1.0.1

   DD_GIT_COMMIT_MESSAGE

   Commit message.
   Example: Set release number

   DD_GIT_COMMIT_AUTHOR_NAME

   Commit author name.
   Example: John Smith

   DD_GIT_COMMIT_AUTHOR_EMAIL

   Commit author email.
   Example: john@example.com

   DD_GIT_COMMIT_AUTHOR_DATE

   Commit author date in ISO 8601 format.
   Example: 2021-03-12T16:00:28Z

   DD_GIT_COMMIT_COMMITTER_NAME

   Commit committer name.
   Example: Jane Smith

   DD_GIT_COMMIT_COMMITTER_EMAIL

   Commit committer email.
   Example: jane@example.com

   DD_GIT_COMMIT_COMMITTER_DATE

   Commit committer date in ISO 8601 format.
   Example: 2021-03-12T16:00:28Z

4. If no CI provider environment variables are found, tests results are sent with no Git metadata.

The tests wall time is empty

If you cannot see the tests wall time it is likely that the CI provider metadata is missing. To confirm this is the case, open a test execution in the Test Runs section, and check if the ci.pipeline.id, ci.pipeline.name, ci.pipeline.number, or ci.job.url tags are missing. If these tags are not populated, then nothing shows in the wall time column.

1. Tracers use the environment variables set by the CI provider to collect this information. See Running tests inside a container for a list of environment variables that the tracer attempts to read for each supported CI provider. Make sure that the environment variables have the expected values set.
2. Check that you are running your tests in a supported CI provider. For a list of supported CI providers, see Running tests inside a container. Only these CI providers can extract the information to enrich the test metadata with CI information.
3. If you still don’t see the wall time, contact Datadog support for help.

The tests wall time is not what is expected

How wall time is calculated

The wall time is defined as the time difference between the start time of the first test and the end time of the last test for the given pipeline.

This is done using the following algorithm:

1. Compute a hash based on CI information to group the tests.
   1. If the tests include ci.job.url, use this tag to calculate the hash.
   2. If the tests don’t include ci.job.url, use ci.pipeline.id + ci.pipeline.name + ci.pipeline.number to calculate the hash.
2. The calculated wall time is associated to a given hash. Note: If there are multiple jobs that execute tests, the wall time is calculated for each job, and the maximum from all calculated wall times is shown.

Possible issues with wall time calculation

If you’re using a library for testing time-dependent code, like timecop for Ruby or FreezeGun for Python, it is possible that test timestamps are wrong, and therefore calculated wall times. If this is the case, make sure that modifications to time are rolled back before finishing your tests.

The test status numbers are not what is expected

The test status numbers are calculated based on the unique tests that were collected. The uniqueness of a test is defined not only by its suite and name, but by its test parameters and test configurations as well.

The numbers are lower than expected

If the numbers are lower than expected, it is likely that either the library or the tool you are using to collect test data cannot collect test parameters and/or some test configurations.

1. If you are uploading JUnit test report files:
   1. If you are running the same tests in different environment configurations, make sure you are setting those configuration tags during the upload.
   2. If you are running parameterized tests, it’s very likely that the JUnit report does not have that information. Try using a native library to report test data.
2. If you still don’t see the expected results, contact Datadog support for troubleshooting help.

The passed/failed/skipped numbers are different than expected

If the same test is collected several times for the same commit but with different status, the aggregated result follows the algorithm in the table below:

The default branch is not correct

How it impacts the product

The default branch is used to power some features of the products, namely:

• Default branches list on the Tests page: This list only displays default branches. Setting the wrong default branch can result in missing or incorrect data in the default branches list.

• Wall time comparison for non-default branches: On the Tests page, in the Branches view, the VS Default column is calculated by comparing wall time for the current branch against wall time for the default branch.

• New flaky tests: Tests that are not currently classified as flaky in the default branch. If the default branch is not properly set, this could lead to a wrong number of detected new flaky tests.

• Pipelines list: The pipelines list only displays default branches. Setting the wrong default branch can result in missing or incorrect data in the pipelines list.

How to fix the default branch

If you have admin access, you can update it from the Repository Settings Page.

Intelligent Test Runner is not working

Intelligent Test Runner works by analyzing your commit history along with code coverage information about past test runs to determine which tests need to be run and which ones can be safely skipped. A minimum amount of information needs to exist in order for the Intelligent Test Runner to work correctly:

• Your repository needs to have a commit history of at least two commits in the past month.
• You need to have collected test code coverage in past commits, which happens on test runs where Intelligent Test Runner was enabled.
• You git clone must contain commit and tree history. Shallow git clones (git clone --depth=0) are not supported.

Due to these restrictions, the first time you enable Intelligent Test Runner, you cannot see any tests skipped and the test execution time may be slower than usual because the code coverage is collected automatically.

Intelligent Test Runner only takes into account the commit history and test code coverage information for the past month. Additionally, it does not take into account code coverage information that is generated more than one week after a commit was made.

If your CI job is using shallow git clones, you can change it to use partial git clones by using the following command: git clone --filter=blob:none.

Intelligent Test Runner incorrectly skipped a test

Intelligent Test Runner performs test impact analysis based on code coverage to determine which tests are impacted by a given commit or set of commits. While this strategy works for the majority of tests, there are known scenarios where Intelligent Test Runner could skip a test that should have been run:

• Changes in library dependencies.
• Changes in compiler options.
• Changes in external services.
• Changes to data files in data-driven tests.

If you are authoring a commit that includes any of those cases, you can force-disable test skipping in Intelligent Test Runner by adding ITR:NoSkip (case insensitive) anywhere in your Git commit message.

Need further help?

Still need help? Contact Datadog support.