ENGINEERING

Block Vercel promotion when crash-free rate regresses vs baseline

On a new Sentry release deploy, compares the crash-free session rate against the previous stable release and, if it drops below your threshold, posts a blocking comment…

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSentry release created for new deploySentrySentry
  • ActionFetch crash-free rate for new + baseline releaseSentrySentry
  • LogicCompare delta against allowed drop threshold
  • ActionPost approval comment on Vercel deploymentVercelVercel
  • OutputPost blocking comment if regression detectedVercelVercel

What it does

Gates production promotion on release health. When Sentry reports a fresh release, this workflow pulls the new release's crash-free session rate, compares it to the last stable release as a baseline, and decides whether the build is safe to promote. A regression beyond your tolerance leaves a clear blocking comment on the Vercel deployment so no one promotes a degraded build by accident.

When to use it

Use it when your team promotes Vercel deployments manually and you want an automated quality bar tied to real user crash data, not just CI green checks. Ideal for high-traffic web apps where a small crash-free dip means thousands of broken sessions.

How it works

  1. 1Sentry emits a release-created event for the new deploy.
  2. 2The flow fetches crash-free session rates for the new release and the prior stable baseline from Sentry.
  3. 3A logic step computes the delta and checks it against your allowed drop (e.g. 0.5%).
  4. 4If healthy, it posts an approval comment on the Vercel deployment.
  5. 5If regressed, it posts a blocking comment naming the baseline, the new rate, and the delta so a human stops the promotion.

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
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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