Debugging Failing Tests and Test Pipelines

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On this page

• Overview
  • General guidelines
  • QA test pipelines
• How to triage a QA test pipeline failure
  • Report the failure
    • Create an issue
    • Special consideration for Staging-Canary
    • Special consideration for Preprod
  • Review the failure logs
  • Investigate the root cause
    • Run the test against your GDK
    • Run the test against a GitLab Docker container
    • Run the tests against CustomersDot staging environment
    • Tips for running tests locally
    • Checking Docker images
      • Checking test code (QA image)
      • Checking application code
      • Checking application version has the specific MR
  • Classify and triage the test failure
    • Stale test due to application change
    • Bug in the test
    • Bug in the application
    • Flaky Test
    • Failure due to test environment
  • Notify relevant groups about the failure
• Following up on test failures
  • Fixing the test
  • Quarantining Tests
    • Quarantined Test Types
    • Examples
    • Nested contexts
  • Dequarantining Tests
  • Re-evaluating tests
• Training Videos
• Other references

Overview

These guidelines are intended to help you to investigate end-to-end test pipeline failures so that they can be properly addressed. This will involve analyzing each failure and creating an issue to report it. It might also involve fixing tests, putting them in quarantine, or reporting bugs in the application.

The Pipeline triage DRI is responsible for analyzing and debugging test pipeline failures. Please refer to the Quality Department pipeline triage rotation schedule to know who the current DRI is.

General guidelines

• Fix tests failing in master before other development work: Failing tests on master are treated as the highest priority relative to other development work, e.g., new features. Note that for pipeline triage DRIs, triage and reporting takes priority over fixing tests.
• Follow the pipeline triage guidelines for investigating, reporting, and resolving test failures
• Flaky tests are quarantined until proven stable: A flaky test is as bad as no tests or in some cases worse due to the effort required to fix or even re-write the test. As soon as detected it is quarantined immediately to stabilize CI, and then fixed as soon as possible, and monitored until it is fixed.
• Close issue when the test is moved out of quarantine: Quarantine issues should not be closed unless tests are moved out of quarantine.
• Quarantine issues should be assigned and scheduled: To ensure that someone is owning the issue, it should be assigned with a milestone set.
• Make relevant stage group aware: When a test fails no matter the reason, an issue should be created and made known to the relevant product stage group as soon as possible. In addition to notifying that a test in their domain fails, enlist help from the group as necessary.
• Failure due to bug: If a test failure is a result of a bug, link the failure to the bug issue. It should be fixed as soon as possible.
• Everyone can fix a test, the responsibility falls on the last who worked on it: Anyone can fix a failing/flaky test, but to ensure that a quarantined test isn't ignored, the last engineer who worked on the test is responsible for taking it out of quarantine.

QA test pipelines

The test pipelines run on a scheduled basis, and their results are posted to Slack. The following are the QA test pipelines that are monitored every day.

For each pipeline there is a notification of success or failure (except for master pipelines, which only report failures). If there's a failure, we use emoji to indicate the state of its investigation:

• The :eyes: emoji, to show you're investigating a failing pipeline.
• The :boom: emoji, when there's a new failure.
• The :fire_engine: emoji, when a failure is already reported.
• The :retry: emoji, when there's a system failure (e.g., Docker or runner failure).

How to triage a QA test pipeline failure

The general triage steps are:

• Report the failure
• Review the failure logs
• Investigate the root cause
• Classify the failure

After triaging failed tests, possible follow up actions are:

• Fixing tests
• Quarantining tests
• Dequarantining tests
• Re-evaluating tests

Report the failure

Your priority is to make sure we have an issue for each failure, and to communicate the status of its investigation and resolution. When there are multiple failures to report, consider their impact when deciding which to report first. See the pipeline triage reponsilibities for further guidance.

If there are multiple failures we recommend that you identify whether each one is new or old (and therefore already has an issue open for it). For each new failure, open an issue that includes only the required information. Once you have opened an issue for each new failure you can investigate each more thoroughly and act on them appropriately, as described in later sections.

The reason for reporting all new failures first is to allow faster discovery by engineers who might find the test failing in their own merge request test pipeline. If there is no open issue about that failure, the engineer will have to spend time trying to figure out if their changes caused it.

Known failures should be linked to the current pipeline triage report. However, issues can be opened by anyone and are not linked automatically, so be sure to confirm there is no existing issue before creating one.

1. Search for existing issues that have already been created with the failure::* label. By order of likelihood:
   1. failure::investigating
   2. failure::test-environment
   3. failure::broken-test
   4. failure::flaky-test
   5. failure::stale-test
2. If the issue has already been reported please use the existing issue to track the latest status.
3. If there is no existing issue for the failure, please create an issue using one of classification labels via the steps below.

In the relevant Slack channel:

1. Apply the :eyes: emoji to indicate that you're investigating the failure(s).
2. If there's a system failure (e.g., Docker or runner failure), retry the job and apply the :retry: emoji. Read below for examples of system failures.
3. If an issue exists, add a :fire_engine: emoji. It can be helpful to reply to the failure notification with a link to the issue(s), but this isn't always necessary, especially if the failures are the same as in the previous pipeline and there are links there.
4. If you create a new issue, add a :boom: emoji.

Create an issue

Please use this step if there are no issues created to capture the failure. If there is already an issue please skip this step.

1. Create an issue for the test or system failure (if retrying the job does not resolve the latter) in https://gitlab.com/gitlab-org/gitlab/issues using the QA failure template. For failures in CustomersDot tests, open an issue in CustomersDot project.
   • Apply the ~"type::ignore" label to the issue until the investigation is complete and an issue type is determined.
   • Inform the counterpart SET about the failure.
   • For system failures, it may make sense to open an issue in a different project such as Omnibus GitLab, GitLab QA, or GitLab Runner.
   • For staging environment-related failures, you can post a question in #infrastructure-lounge, or open an issue in the infrastructure project
   • Ask for help in #quality if you're unsure where to file the issue.
2. In the relevant Slack channel, add the :boom: emoji and reply to the failure notification with a link to the issue.
3. Add the issue as a related issue to the current pipeline triage report.

Special consideration for Staging-Canary

Staging-Canary is unique when it comes to its blocking smoke and reliable tests that are triggered by the deployer pipeline. Staging-Canary executes smoke/reliable tests for both Staging-Canary AND Staging environments. This special configuration is designed to help catch issues that occur when incompatabilities arise between the shared and non-shared components of the environments.

Staging-Canary and Staging both share the same database backend, for example. Should a migration or change to either of the non-shared components during a deployment create an issue, running these tests together helps expose this situation. When the deployer pipeline triggers these test runs, they are reported serially in the #qa_staging Slack channel and they appear as different runs.

Note when viewing a deployment failure from the #announcements Slack channel, you will have to click into the pipeline and look at the Downstream results to understand if the deployment failure arose from a failure in Staging-Canary or if the failure occurred in Staging.

Click on the diagram below to visit the announcement issue for more context and view an uncompressed image:

Note the diagram has been upadted as part of increasing rollback availability by removing the blocking nature of post-deployment migrations.

Special consideration for Preprod

Preprod is used to perform validation of release candidates. Every month around the 22nd, and the few days before, it is essential that there are no unexpected failures in the pipeline that will delay the release. There is a pipeline scheduled to run prior to deployment of the release candidate, to give us a chance to identify and resolve any issues with tests or the test environment. This scheduled pipeline should be given equal priority with Production and Staging pipelines because of the potential impact failures can have on a release.

Tests pipelines are also triggered by the Kubernetes Workload configuration project to ensure that any configuration changes are valid.

Review the failure logs

The aim of this step is to understand the failure. The results of the investigation will also let you know what to do about the failure. Update the failure issue with any findings from your review.

The following can help with your investigation:

Investigate the root cause

Depending on your level of context for the test and its associated setup, you might feel comfortable investigating the root cause on your own, or you might get help from other SETs right away.

When investigating on your own, we suggest spending at most 20-30 minutes actively trying to find the root cause (this excludes time spent reporting the failure, reviewing the failure logs, or any test setup and pipeline execution time). After that point, or whenever you feel out of ideas, we recommend asking for help to unblock you.

Note: Please avoid logging in via gitlab-qa and all the other bot accounts on Canary/Production. They are monitored by SIRT and will raise an alert if someone uses them to log in. If it is really needed to log in with these accounts, please give a quick heads-up in #security-department that someone is logging into the bot and tag @sirt-members for awareness.

Below is the list of the common root causes in descending order of likelihood:

1. Code changes: Check if the new code was deployed to the environment.
   • Find the diff between current and previous GitLab versions using this example https://gitlab.com/gitlab-org/security/gitlab/-/compare/start_commit_sha...end_commit_sha to see if there was a change that could have affected the test.
2. Feature Flag: Check if a new feature flag is enabled in the environment.
   • When a feature flag is enabled, it's being reported to specific QA pipeline Slack channel. This also triggers a Full QA job and it may help to identify which specific feature flag caused the failure.
   • A list of logs containing details on both recent and historic feature flag changes can also be viewed by visiting the feature-flag-log project. Each time a feature flag is updated, a new issue is generated in the project with helpful information such as when the feature flag was changed, who performed the update and on which environment. The project contains several host labels that can help filter by environment when searching through issues (ex: ~host::staging.gitlab.com)
     • You can also reference this dashboard for a visual representation of feature flag statuses.
3. Environment configuration: If there were no code or feature flag changes and the environment has flaky errors, analyze Sentry errors and Kibana logs to further investigate the issue. Consider reaching out to the Infrastructure team at #infrastructure-lounge and ask if something was changed recently on the environment in question.
4. Test Data: Check that test data is valid. Live environments like Staging and Production rely on pre-existing data (QA users, access tokens).
5. New GitLab QA version: Check if a new GitLab QA version was released.

Failure examples can be seen in Training Videos.

Run the test against your GDK

You can run the test (or perform the test steps manually) against your local GitLab instance to see if the failure is reproducible. For example:

CHROME_HEADLESS=false bundle exec bin/qa Test::Instance::All http://localhost:3000 qa/specs/features/browser_ui/1_manage/project/create_project_spec.rb

Orchestrated tests are excluded by default. To run them, use -- --tag orchestrated before your file name. For example:

CHROME_HEADLESS=false bundle exec bin/qa Test::Instance::All http://localhost:3000 -- --tag orchestrated qa/specs/features/browser_ui/1_manage/project/create_project_spec.rb

Run the test against a GitLab Docker container

You can also use the same Docker image (same sha256 hash) as the one used in the failing job to run GitLab in a container on your local. In the logs of the failing job, search for Downloaded newer image for gitlab/gitlab-ce:nightly or Downloaded newer image for gitlab/gitlab-ee:nightly and use the sha256 hash just above that line.

To run GitLab in a container on your local, the docker command similar to the one shown in the logs can be used. E.g.:

docker run --publish 80:80 --env GITLAB_OMNIBUS_CONFIG='gitlab_rails["initial_root_password"] = "CHOSEN_PASSWORD"' --name gitlab --hostname localhost gitlab/gitlab-ce:nightly@sha256:<hash>

You can now run the test against this Docker instance. E.g.:

CHROME_HEADLESS=false bundle exec bin/qa Test::Instance::All http://localhost qa/specs/features/browser_ui/1_manage/project/create_project_spec.rb

Run the tests against CustomersDot staging environment

To run CustomersDot E2E tests locally against staging environment, you will need to clone CustomersDot project, switch to qa directory, and then run

STAGING=1 CP_ADMIN_TOKEN=<TOKEN> GL_ADMIN_TOKEN=<TOKEN> bundle exec rspec spec/ui/purchase/purchase_plan_spec.rb

Note - Token value can be found in GitLab-QA Vault. For details on running tests locally with more options, please refer to CustomersDot README doc

Tips for running tests locally

• Use the environment variable QA_DEBUG=true to enable logging output including page actions and Git commands.
• Additional information about running tests locally can be found in the QA readme and in the instructions for running tests that require special setup.
• To determine if the test is flaky, check the logs or run the test a few times. If it passes at least once but fails otherwise, it's flaky.

Checking Docker images

Sometimes tests may fail due to an outdated Docker image. To check if that's the case, follow the instructions below to see if specific merged code is available in a Docker image.

Checking test code (QA image)

If you suspect that certain test is failing due to the gitlab/gitlab-{ce|ee}-qa image being outdated, follow these steps:

1. Locally, run docker run -it --entrypoint /bin/sh gitlab/gitlab-ce-qa:latest to check for GitLab QA CE code, or docker run -it --entrypoint /bin/sh gitlab/gitlab-ee-qa:latest to check for GitLab QA EE code
2. Then, navigate to the qa directory (cd /home/qa/qa)
3. Finally, use cat to see if the code you're looking for is available in certain file (e.g., cat page/project/issue/show.rb)

Note if you need to check in another tag (e.g., nightly), change it in one of the scripts of step 1 above.

Checking application code

1. Locally, run docker run -it --entrypoint /bin/sh gitlab/gitlab-ce:latest to check for GitLab CE code, or docker run -it --entrypoint /bin/sh gitlab/gitlab-ee:latest to check for GitLab EE code
2. Then, navigate to the gitlab-rails directory (cd /opt/gitlab/embedded/service/gitlab-rails/)
3. Finally, use cat to see if the code you're looking for is available or not in a certain file (e.g., cat public/assets/issues_analytics/components/issues_analytics-9c3887211ed5aa599c9eea63836486d04605f5dfdd76c49f9b05cc24b103f78a.vue.)

Note if you want to check another tag (e.g., nightly) change it in one of the scripts of step 1 above.

Checking application version has the specific MR

1. Find the version which GitLab application is running on. In the failing job logs, search for docker pull dev.gitlab.org:5005/gitlab/omnibus-gitlab/gitlab-ee-qa and use the version specified after gitlab-ee-qa:.
   • For nightly the approach above won't work. There are two ways for finding the commit version of nightly:
     • Run the nightly image on local, sign-in as admin and navigate to /help page or call the /api/v4/version API.
     • Search for the commit in the omnibus-gitlab pipeline that built the last nightly. Jobs that build nightly have bundle exec rake docker:push:nightly command in the Docker-branch job of the Package-and-image stage. Once you find the latest pipeline, search for gitlab-rails under build-component_shas in any job under the Gitlab_com:package stage. For example, in this Ubuntu-16.04-branch job, the commit SHA for gitlab-rails is 32e76bc4fb02a615c2bf5a00a8fceaee7812a6bd.
2. Open commits list for the specific version:
   • If version format is like a commit SHA, for example gitlab-ee-qa:13.10-4b373026c98, navigate to https://gitlab.com/gitlab-org/gitlab/-/commits/<commit_SHA> page, in our example the commit SHA is 4b373026c98.
   • If version format is like a tag, for example 13.10.0-rc20210223090520-ee, navigate to https://gitlab.com/gitlab-org/gitlab/-/commits/v<tag> page, in our example the tag is 13.10.0-rc20210223090520-ee.
   • If page above returns 404 error, check if the version exists in GitLab Security repo in case there is a security release.
3. Check if the MR that you were searching for is in this version.
   • Note the branch name of the MR.
   • Search the commits from Step 2 by the branch name.
     • If the commit is found, the MR is in this version. For example.
     • If no results, the MR is not in this version. For example.

Classify and triage the test failure

The aim of this step is to categorize the failure as either a stale test, a bug in the test, a bug in the application code, or a flaky test.

We use the following labels to capture the cause of the failure.

• ~"failure::investigating": Default label to apply at the start of investigation.
• ~"failure::stale-test": Stale test due to application change
• ~"failure::broken-test": Bug in the test
• ~"failure::flaky-test": Flaky test
• ~"failure::test-environment": Failure due to test environment
• ~"type::bug": Bug in the application

Bugs blocking end-to-end test execution (due to the resulting quarantined tests) should additionally have severity and priority labels. For guidelines about which to choose, please see the blocked tests section of the issue triage page.

Note: It might take a while for a fix to propagate to all environments. Be aware that a new failure could be related to a recently-merged fix that hasn't made it to the relevant environment yet. Similarly, if a known failure occurs but the test should pass because a fix has been merged, verify that the fix has been deployed to the relevant environment before attempting to troubleshoot further.

Stale test due to application change

The failure was caused by a change in the application code and the test needs to be updated.

• Include your findings in a note in the issue about the failure.
• Apply the ~"failure::stale-test" label.
• If possible, mention the merge request which caused the test to break, to keep the corresponding engineer informed.

See Quarantining Tests

Bug in the test

The failure was caused by a bug in the test code itself, not in the application code.

• Include your findings in a note in the issue about the failure.
• Apply the ~"failure::broken-test" label.

See Quarantining Tests

Bug in the application

The failure was caused by a bug in the application code.

• Include your findings in a note in the issue about the failure.
• Add the steps to reproduce the bug and expected/actual behavior.
• Apply the ~"type::bug" label, and cc-ing the corresponding Engineering Managers (EM), QEM, and SET.
• If the problem adheres to the definition of a transient bug, apply the ~"bug::transient" label as well.
• If there is an issue open already for the bug, mark the new issue as a duplicate of the original bug.
• Communicate the issue in the corresponding Slack channels.
• Do not quarantine the test immediately unless the bug won't be fixed quickly (e.g. if it is a minor/superficial bug). Instead, leave a comment in the issue for the bug asking if the bug can be fixed in the current release. If it can't, quarantine the test.
• When the reason for quarantining a test is because of a low severity bug in the code which will not be fixed in the upcoming couple of releases, add type: :bug in the quarantine tag.

Note: GitLab maintains a daily deployment cadence so a breaking change in master reaches Canary and Production fast. Please communicate broadly to ensure that the corresponding Product Group is aware of the regression and action is required. If the bug is qualified for dev escalation (example: priority::1/severity::1 issue that blocks the deployment process), consider involving On-call Engineers in the #dev-escalation channel. To find out who’s on-call follow the links in the channel subject line.

To find the appropriate team member to cc, please refer to the Organizational Chart. The Quality Engineering team list and DevOps stage group list might also be helpful.

See Quarantining Tests

Flaky Test

The failure is due to flakiness in the test itself.

• Include your findings in a note in the issue about the failure.
• Apply the ~"failure::flaky-test" label.
• Add the test to our Test Reliability: Improve test design tracking issue to identify areas of improvement that can help prevent future flakiness.

Flakiness can be caused by a myriad of problems. Examples of underlying problems that have caused us flakiness include:

• Not waiting appropriately for pages to load or transitions from one state to another to complete.
• Animations preventing tests from interacting with elements.
• Non-independent tests (i.e. test A passes when run first, but fails otherwise).
• Actions not completing successfully (e.g. logging out).

For more details, see the list with example issues in our Testing standards and style guidelines section on Flaky tests.

See Quarantining Tests

Failure due to test environment

The failure is due external factors outside the scope of the test. This could be due to environments, deployment hang-ups, or upstream dependencies.

• Include your findings in a note in the issue about the failure.
• Apply the ~"failure::test-environment" label.
• Identify the general category of improvement and add the failure issue to the approprite Test Reliability issue listed within the Improve test environment reliability and reduce flaky/transient test failures tracking issue.
  • Endeavor to create an appropriate action item (issue or MR) to help resolve the reliability issue as indicated in the tracking issues.

A job may fail due to infrastructure or orchestration issues that are not related to any specific test. In some cases these issues will fail a job before tests are ever executed. Some examples of non-test related failures include:

• Failed to download Docker image
• Failed to complete orchestration of a Geo cluster
• CI runner timeouts
• 500 error while uploading job artifacts

Notify relevant groups about the failure

If the failure is in a smoke or a reliable test, it will block deployments. Please inform the release managers of the root cause and if a fix is in progress by Quality. On GitLab.com you can use @gitlab-org/release/managers. In Slack you can use @release-managers.

Please also raise awareness by looping in the appropriate team members from the product group, such as SET or EM. You may also want to post to Quality's Slack channel, #quality, depending on the impact of the failure.

If the failure could affect the performance of GitLab.com production, or make it unavailable to a specific group of users, you can declare an incident with /incident declare in the #production slack channel, this will automatically prevent deployments (if the incident is at least an S2).

Following up on test failures

Fixing the test

If you've found that the test is the cause of the failure (either because the application code was changed or there's a bug in the test itself), it will need to be fixed. This might be done by another SET or by yourself. However, it should be fixed as soon as possible. In any case, the steps to follow are as follows:

• Create a merge request (MR) with the fix for the test failure.
• Apply the ~"Pick into auto-deploy", ~"priority::1", and ~"severity::1" labels if the fix is urgent and required to unblock deployments.

If the test was flaky:

• Confirm that the test is stable by ensuring it passes 3 to 5 times while in quarantine.

Note The number of passes needed to be sure a test is stable is just a suggestion. You can use your judgement to pick a different threshold.

If the test was in quarantine, remove it from quarantine.

Quarantining Tests

Note We should be very strict about quarantining tests. Quarantining a test is very costly and poses a higher risk because it allows tests to fail without blocking the pipeline, which could mean we miss new failures.

The aim of quarantining a test is not to get back a green pipeline, but rather to reduce the noise (due to constantly failing tests, flaky tests, and so on) so that new failures are not missed. If you're unsure about quarantining a test ask for help in the#quality Slack channel, and then consider adding to the list of examples below to help future pipeline triage DRIs.

Examples of when to quarantine a test:

• Bug in test code (~"failure::broken-test"), and a fix won't be ready for review within 24 hours
• Stale test (~"failure::stale-test"), and a fix won't be ready for review within 24 hours

Examples of when not to quarantine a test:

• Test failure is environment-related (~"failure::test-environment"), and neither the application code nor test code are the cause of the failure
• A merge request to fix the failure will be ready for review within 24 hours
• A flaky smoke test.
  • The :smoke tag should be removed from the test to prevent it running with the smoke suite, but still allowed to run elsewhere while the flakiness is under investigation or being worked on to unblock deployment.
  • Create an issue to follow up and restore the :smoke tag as soon as possible. Tests at the :smoke level should be given priority when addressing flakiness within our test suites.
  • Create a # TODO note in the test as a reminder with a link to the previously created issue url. For example:
    • # TODO restore :smoke tag and close https://gitlab.com/gitlab-org/gitlab/-/issues/######

Note The time limit for the fix is just a suggestion. You can use your judgement to pick a different threshold.

To quarantine a test:

• Add the :quarantine metadata to the test with a link to the issue (see quarantined test types)

Note If the example has a before hook, the quarantine metadata should be assigned to the outer context to avoid running the before hook.

• Create a merge request using the Quarantine End to End Test template.
  • The merge request shall have the labels: ~"Quality", ~"QA", ~"type::bug".
  • The merge request may have auto-deploy labels: ~"Pick into auto-deploy", ~"priority::1", and ~"severity::1". Please note that this is reserved for emergency cases only, such as blocked deployments, as it will delay all other deployments by around two hours.
  • The merge request may have stage or group labels. E.g. ~"devops::create" ~"group::source code".
  • The merge request shall have the current milestone.
  • The merge request shall link to (but not close) the failure issue.
• The failure issue should remain open and be assigned a DRI (likely the counterpart SET) for fixing, re-evaluating, or dequarantining the test as needed.

To be sure that the test is quarantined quickly, ask in the #quality Slack channel for someone to review and merge the merge request, rather than assigning it directly.

Here is an example quarantine merge request.

Quarantined Test Types

If a test is placed under quarantine, it is important to specify why. By specifying a quarantine type we can see quickly the reason for the quarantine.

The report accepts the quarantine types below:

Note: Be sure to attach an issue to the quarantine metadata. We use this issue for tracking the average age of the quarantined tests.

Examples

it 'is flaky', quarantine: { issue: 'https://gitlab.com/gitlab-org/gitlab/issues/12345', type: :flaky }
it 'is due to a bug', quarantine: {
                        issue: 'https://gitlab.com/gitlab-org/gitlab/issues/12345',
                        type: :bug
                      }
context 'when these tests rely on another MR', quarantine: {
                                                 type: :waiting_on,
                                                 issue: 'https://gitlab.com/gitlab-org/gitlab/merge_requests/12345'
                                               }

Nested contexts

You should apply the quarantine tag to the outermost describe/context block that has tags relevant to the test being quarantined.

# Good
RSpec.describe 'Plan', :smoke, quarantine: { issue: 'https://gitlab.com/gitlab-org/gitlab/issues/12345', type: :flaky } do
  describe 'Feature' do
    before(:context) do
      # This before(:context) block will only be executed in smoke quarantine jobs
    end
  end
end

# Bad
RSpec.describe 'Plan', :smoke do
  describe 'Feature', quarantine: { issue: 'https://gitlab.com/gitlab-org/gitlab/issues/12345', type: :flaky } do
    before(:context) do
      # This before(:context) block could be mistakenly executed in quarantine jobs that _don't_ have the smoke tag
    end
  end
end

Dequarantining Tests

Failing to dequarantine tests periodically reduces the effectiveness of the test suite. Hence, the tests should be dequarantined on or before the due-date mentioned in the corresponding issue.

Before dequarantining a test:

• If the test failure was originally discovered in nightly, MR or master pipeline, please make sure that the test passes on your local against GDK with latest code and that it has passed a few times in the nightly pipeline's quarantine job for that test.
• If the test failure was originally discovered in staging, canary or production pipeline, please make sure that the test passes in the CI pipeline against that environment. You can trigger a CI pipeline against a live environment by clicking "Run Pipeline" button on the staging, canary or production pipelines page and setting the RELEASE variable to the release that has your changes. See Running GitLab-QA pipeline against a specific GitLab release for instruction on finding your release version created and tagged by the Omnibus pipeline.

To dequarantine a test:

• Create a merge request that removes the :quarantine tag using the Quarantine End to End Test MR template.
• Close the issue created as part of the quarantining process.

As with quarantining a test, you can ask in the #quality Slack channel for someone to review and merge the merge request, rather than assigning it.

Re-evaluating tests

If the due date of a failing test issue is reached, you should re-evaluate if the failing test should really be covered at the end-to-end test level, or if it should be covered in a lower level of the testing levels pyramid.

If you decide to delete the test, open a merge request to delete it and close the test failure issue. In the MR description or comment, mention the stable counterpart SET for the test's stage for their awareness. Then open a new issue to cover the test scenario in a different test level.

If you decide the test is still valuable but don't want to leave it quarantined, you could replace :quarantine with :skip, which will skip the test entirely (i.e., it won't run even in jobs for quarantined tests). That can be useful when you know the test will continue to fail for some time (e.g., at least the next milestone or two).

Training Videos

These videos walking through the triage process were recorded and uploaded to the GitLab Unfilitered YouTube channel.

• Quality Team: Failure Triage Training - Part 1
  • Covers the basics of investigating pipeline failures locally.
• Quality Team: Failure Triage Training - Part 2
  • Continued discussion with a focus on using Docker containers that were used in the pipeline that failed.
• Quality Engineering On-call Rotation and Debugging QA failures (private video on GitLab Unfiltered)
  • Overview of QE on-call rotation process, GitLab deployment process and how to debug failed E2E specs with examples.

Other references

You can find some general tips for troubleshooting problems with GitLab end-to-end tests in the development documentation.