ENGINEERING

Pre-Deploy Burn Guard for Vercel Releases

When a deploy tag is pushed to GitHub, checks the target service's Honeycomb burn rate and either promotes the Vercel deployment or cancels it and comments on the release…

CategoryEngineering
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGitHub release tag pushedGitHubGitHub
  • ActionFetch service SLO burn rate from HoneycombHoneycomb
  • LogicDecide promote or hold on burn threshold
  • ActionPromote or cancel the Vercel deploymentVercelVercel
  • OutputComment verdict and burn math on GitHub releaseGitHubGitHub

What it does

Applies the burn-rate gate at the deploy boundary instead of the merge boundary. When a release tag lands on GitHub, it reads the service's current Honeycomb SLO burn rate; if the budget is healthy it promotes the pending Vercel deployment to production, and if burn is over threshold it cancels the promotion and posts the blocking math on the GitHub release. This stops a new release from compounding an already-burning budget.

When to use it

Use it when merges are allowed freely but production promotions should respect live SLO health — for example tag-driven releases on Vercel where you want a final reliability check right before traffic shifts.

How it works

  1. 1A GitHub tag-push event for a release tag triggers the flow.
  2. 2It fetches the service's SLO burn rate from Honeycomb.
  3. 3A logic step decides promote or hold based on the burn threshold.
  4. 4If healthy, it promotes the Vercel deployment; if hot, it cancels the promotion.
  5. 5It posts the verdict and burn math as a comment on the GitHub release.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect HoneycombDistributed traces and queries.
  3. 3
    Connect VercelDeploys, runtime logs, analytics.
  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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