SUMMARIZATION

Sentry deploy regression triage brief to Slack

On each new Vercel production deploy, compares Sentry error rates against the previous release and posts a plain-English triage brief to Slack only when a regression crosses your…

CategorySummarization
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerVercel production deploy succeedsVercelVercel
  • ActionFetch release-health stats for new + previous releaseSentrySentry
  • LogicCompute error-rate delta; stop if below threshold
  • ActionPull top new and spiking issues for the releaseSentrySentry
  • ActionSummarize deltas + culprits into a triage briefOpenAI
  • OutputPost brief to incident Slack channelSlack

What it does

After every production deploy, it pulls Sentry release-health stats for the new release and the one it replaced, computes the crash-free-session and error-rate deltas, and — when the regression is material — writes a concise triage brief naming the most likely culprit issues and posts it to your incident Slack channel.

When to use it

Use it when your team ships to production several times a day and nobody has time to babysit the Sentry release dashboard after each deploy. It catches the silent regressions that don't page anyone but quietly degrade reliability.

How it works

  1. 1A Vercel deployment-succeeded webhook fires with the new release version.
  2. 2The flow fetches release-health metrics for the new and previous releases from Sentry.
  3. 3A logic step computes error-rate and crash-free deltas and stops quietly if the regression is below threshold.
  4. 4Sentry returns the top new and spiking issues for the release.
  5. 5An OpenAI step distills the numbers and issues into a short, ranked triage brief.
  6. 6The brief posts to Slack with links back to Sentry and the deploy.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect VercelDeploys, runtime logs, analytics.
  2. 2
    Connect SentryErrors, performance, releases.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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