ENGINEERING
Skip Known-Flaky Tests on GitLab Pipeline Retries
On a GitLab pipeline retry, checks the quarantine ledger and posts a merge-request note listing which failures are known-flaky versus real.
How it runs
The automated pipeline, trigger to output.
- TriggerGitLab pipeline retriedGitLab
- ActionFetch failing job test reportsGitLab
- ActionLook up each failure in the quarantine ledgerBigQuery
- LogicPartition known-flaky vs genuine regressions
- OutputPost flaky-vs-real breakdown note on the MRGitLab
What it does
When a developer retries a failed GitLab pipeline, this workflow cross-references each failing test against the quarantine ledger and separates known-flaky failures from genuine regressions. It posts a clear note on the merge request so reviewers can see at a glance whether a red pipeline is real or just flake noise.
When to use it
Use it when flaky failures are eroding trust in your pipeline and reviewers can't tell which reds matter. It keeps real regressions visible while de-emphasizing tests already tracked as flaky.
How it works
- 1A GitLab pipeline event with a retry status fires the trigger.
- 2The flow fetches the failing job test reports from the pipeline.
- 3It queries the BigQuery quarantine ledger for each failing test's status.
- 4Logic partitions failures into known-flaky and genuine buckets.
- 5If any genuine failures exist, the MR is flagged as blocking; otherwise it's marked flake-only.
- 6A summarizing note is posted to the merge request with both lists and links.
Set it up
What you configure once, before turning it on.
- 1Connect GitLabRepos, MRs, pipelines, registry.
- 2Connect BigQueryDatasets, queries, schemas.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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