ENGINEERING
Sentry error cluster to GitLab issue with suspected-commit blame
When a Sentry issue crosses an event-volume threshold, it opens a GitLab issue enriched with the stack trace and the most likely culprit commit identified by matching the failing…
How it runs
The automated pipeline, trigger to output.
- TriggerSentry issue crosses event-volume thresholdSentry
- ActionFetch event payload and resolved stack framesSentry
- LogicIsolate top in-app frame (file + line)
- ActionQuery GitLab blame for last commit on that lineGitLab
- ActionDraft issue title and body with suspected commitOpenAI
- OutputCreate labeled GitLab issue linked to SentryGitLab
What it does
Turns a noisy Sentry error cluster into a ready-to-triage GitLab issue. It pulls the stack trace, finds the top in-app frame, looks up who last touched that file and line in GitLab, and files an issue that names the suspected commit and author so triage starts with a lead instead of a blank page.
When to use it
Use it when production exceptions spike and your team wants every meaningful cluster captured as a GitLab issue automatically, with a starting hypothesis about which change introduced it. Best for teams who triage in GitLab and want to skip the manual stack-trace-to-blame archaeology.
How it works
- 1Sentry fires when an issue's event count crosses the configured threshold.
- 2The flow fetches the full event payload, including the resolved stack frames.
- 3It isolates the top in-app frame (file path plus line number).
- 4It queries GitLab blame for that file and line to find the last commit and author that touched it.
- 5OpenAI drafts a concise issue title and body summarizing the error and the suspected commit.
- 6A GitLab issue is created, labeled, and linked back to the Sentry issue.
Set it up
What you configure once, before turning it on.
- 1Connect SentryErrors, performance, releases.
- 2Connect GitLabRepos, MRs, pipelines, registry.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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