DEVOPS

Open a GitHub RCA issue when a release regresses in Sentry

When Sentry flags an issue as regressed against a new Vercel release, it opens a pre-filled GitHub root-cause issue with the release diff, top stack traces.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSentry issue-regressed webhookSentrySentry
  • ActionResolve release to Vercel deploy and commit SHAVercelVercel
  • ActionPull commit range and author from GitHubGitHubGitHub
  • LogicAssemble RCA body with traces and impact
  • ActionOpen and assign GitHub RCA issueGitHubGitHub
  • OutputLink the issue into SlackSlack

What it does

Closes the loop between a regression and the fix work. When Sentry marks an issue regressed in a release that maps to a recent Vercel deploy, the flow assembles a root-cause analysis issue in GitHub containing the suspect release, the commit range since the last good deploy, the top stack frames from Sentry, and how many users are affected, then assigns it to the engineer who shipped the deploy.

When to use it

Use it when regressions slip through and you want every one to automatically become a tracked, assigned, well-scoped GitHub issue rather than a forgotten Slack mention.

How it works

  1. 1A Sentry regression webhook fires for a re-opened issue.
  2. 2The flow resolves the issue's release back to a Vercel deployment and its commit SHA.
  3. 3It pulls the commit range and author from GitHub since the last healthy deploy.
  4. 4Logic assembles the RCA body with stack traces and affected-user counts.
  5. 5It opens a GitHub issue labeled regression and assigns the deploy author.
  6. 6It links the new issue back into Slack for visibility.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SentryErrors, performance, releases.
  2. 2
    Connect VercelDeploys, runtime logs, analytics.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  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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