ENGINEERING

Critical burn: roll back the last Vercel deploy and page on-call

When Honeycomb reports a critical fast-burn that started right after a deploy, this flow rolls back to the previous Vercel production deployment, opens a PagerDuty incident.

CategoryEngineering
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHoneycomb critical burn-rate alertHoneycomb
  • LogicConfirm critical tier + recent deploy correlation
  • ActionRoll Vercel prod back to last good deployVercelVercel
  • ActionOpen PagerDuty incident for on-callPagerDutyPagerDuty
  • OutputPost burn-to-rollback timeline in SlackSlack

What it does

Treats a critical burn that began just after a release as a likely bad deploy and reacts automatically. On a critical-tier Honeycomb burn-rate alert, it rolls Vercel production back to the prior known-good deployment, raises a PagerDuty incident for on-call, and drops a timeline into Slack tying the burn to the suspect deploy.

When to use it

Use it for high-stakes services where a fast-burning SLO right after a ship warrants an immediate automated rollback rather than waiting on a human. Requires a clear previous-good Vercel deployment and a PagerDuty service.

How it works

  1. 1Honeycomb sends a critical burn-rate alert webhook.
  2. 2A logic step confirms it is critical tier and correlates with a deploy in the last N minutes.
  3. 3Vercel rolls production back to the previous successful deployment.
  4. 4PagerDuty opens an incident with the SLO, burn rate, and rolled-back deploy id.
  5. 5Slack receives the full timeline: burn detected, deploy suspected, rollback done, on-call paged.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HoneycombDistributed traces and queries.
  2. 2
    Connect VercelDeploys, runtime logs, analytics.
  3. 3
    Connect PagerDutyIncidents, on-call, escalations.
  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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