ENGINEERING

Pause a Vercel promotion when Honeycomb SLO burn-rate exceeds threshold

On every Vercel production deployment, checks the owning service's Honeycomb SLO burn rate and, if it is over budget, blocks the promotion and pings the owning team in Slack…

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerVercel production deployment webhookVercelVercel
  • ActionFetch SLO burn rate from HoneycombHoneycomb
  • LogicBurn rate over gate threshold?
  • ActionCancel or roll back the Vercel promotionVercelVercel
  • OutputAlert owning team in Slack with SLO detailsSlack

What it does

Guards your production promotions. When Vercel signals a new production deployment, this workflow reads the matching Honeycomb SLO burn-rate alert before traffic shifts. If the short-window burn rate is above your gate (for example 2x budget over a 1-hour window), it cancels the Vercel promotion and tells the owning team exactly which SLO tripped and by how much.

When to use it

Use it when you ship to production frequently and want an automatic safety brake tied to real reliability signals instead of a manual eyeball check. Best for teams that already define Honeycomb SLOs per service and use Vercel's deployment promotion flow.

How it works

  1. 1A Vercel deployment webhook fires on a new production build.
  2. 2The workflow queries Honeycomb for the burn rate of the SLO that maps to that service.
  3. 3A branch compares the burn rate against your configured threshold.
  4. 4If over budget, it calls the Vercel API to cancel or roll back the promotion.
  5. 5It posts the SLO name, current burn rate, and deploy URL to the owning team's Slack channel so they can decide next steps.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect VercelDeploys, runtime logs, analytics.
  2. 2
    Connect HoneycombDistributed traces and queries.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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