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Documentation Index

Fetch the complete documentation index at: https://trunk-4cab4936-sam-gutentag-flaky-tests-new-monitors.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

Trunk Flaky Tests integrates with your CI by adding a step in your CircleCI Pipelines to upload tests with the Trunk Analytics CLI.
Not using GitHub for source control?Flaky Test support for source control providers like GitLab and BitBucket is still experimental. If you’re using a source control provider other than GitHub, contact us to get started.
Before you start on these steps, see the Test Frameworks docs for instructions on producing a Trunk-compatible output for your test framework.

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Checklist

By the end of this guide, you should achieve the following.
  • Get your Trunk organization slug and token
  • Set your slug and token as a variable in CI
  • Configure your CI to upload to Trunk
  • Validate your uploads in Trunk
After completing these checklist items, you’ll be integrated with Trunk.

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Trunk Organization Slug and Token

Before setting up uploads to Trunk, you must sign in to app.trunk.io and obtain your Trunk organization slug and token.

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Trunk Slug

You can find your organization slug under Settings > Organization > Manage > Organization Name > Slug. You’ll save this as a variable in CI in a later step.

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Trunk Token

You can find your token under Settings > Organization > Manage > Organization API Token > View Organization API Token > View. Since this is a secret, do not leak it publicly. Ensure you get your organization token, not your project/repo token.

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Add the Trunk Token as a Secret

Store your Trunk slug and API token in your CircleCI project settings under Environment Variables as new variables named TRUNK_ORG_SLUG and TRUNK_TOKEN respectively.

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Upload to Trunk

Add an Upload Test Results step after running tests in each of your CI jobs that run tests. This should be minimally all jobs that run on pull requests, as well as from jobs that run on your main or stable branches, for example, main, master, or develop.
The Trunk Analytics CLI automatically detects PR context from CircleCI environment variables, including the pull request number. No additional configuration is needed to associate test uploads with the correct PR in Trunk.
It is important to upload test results from CI runs on stable branches, such as main, master, or develop. This will give you a stronger signal about the health of your code and tests.Trunk can also detect test flakes on PR and merge branches. To best detect flaky tests, it is recommended to upload test results from stable, PR, and merge branch CI runs.Learn more about detection

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Example CircleCI workflow

The following is an example of a workflow step to upload test results after your tests run. Note: you must either run trunk from the repo root when uploading test results or pass a --repo-root argument. To find out how to produce the report files the uploader needs, see the instructions for your test framework in the Test Frameworks docs. 
jobs:
  test-node:
    # Install node dependencies and run tests
    executor: node/default
    steps:
      - run:
          name: Run Tests
          command: ...

      - run:
          name: Upload Test Results to Trunk.io
          command: |
            curl -fL --retry 3 "https://github.com/trunk-io/analytics-cli/releases/latest/download/trunk-analytics-cli-x86_64-unknown-linux.tar.gz" | tar -xz && chmod +x trunk-analytics-cli
            ./trunk-analytics-cli upload --junit-paths "**/junit.xml" --org-url-slug <TRUNK_ORG_SLUG> --token ${TRUNK_TOKEN}
The examples above use the Linux x64 binary. If your CI runs on a different platform, see the Trunk Analytics CLI page for all available platform downloads.
See the Uploader CLI Reference for all available command line arguments and usage.

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Stale files

Ensure you report every test run in CI and clean up stale files produced by your test framework. If you’re reusing test runners and using a glob like **/junit.xml to upload tests, stale files not cleaned up will be included in the current test run, throwing off detection of flakiness. You should clean up all your results files after every upload step.
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