SUMMARIZATION

Sentry Error-Budget Burn Brief Posted to GitLab MR

When a GitLab merge request is marked ready, compares Sentry release-health metrics between the current deploy and the previous release.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGitLab MR marked readyGitLabGitLab
  • ActionResolve candidate vs prior release tagsGitLabGitLab
  • ActionFetch Sentry release-health for both releasesSentrySentry
  • ActionSummarize error-budget burn deltaOpenAI
  • OutputPost regression brief as MR commentGitLabGitLab

What it does

Attaches a release-health verdict to every merge request before it lands. It pulls Sentry's crash-free session rate and unhandled error count for the candidate release and the release it would replace, computes how much of the error budget each one burns, and writes a short reviewer-facing brief directly on the GitLab MR.

When to use it

Use it when your team gates merges on stability and you want reviewers to see regression risk without opening Sentry. Ideal for services with defined crash-free SLOs where a noisy deploy should block the merge.

How it works

  1. 1A GitLab MR transitions to ready and fires a webhook.
  2. 2The flow resolves the candidate release tag and the prior production release from the MR metadata.
  3. 3Sentry release-health stats are fetched for both releases: crash-free sessions, crash-free users, and unhandled error volume.
  4. 4An LLM summarizes the delta into a budget-burn brief with a clear pass or regression verdict.
  5. 5The brief is posted as a comment on the originating GitLab merge request.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitLabRepos, MRs, pipelines, registry.
  2. 2
    Connect SentryErrors, performance, releases.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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