ENGINEERING

Dependency Canary: Auto-Close PR on Error-Rate Spike

After a dependency PR deploys to a canary, watches the Honeycomb error rate and, if errors spike past the budget, comments the evidence on the PR and converts it back to draft…

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCanary PR marked ready for reviewGitHubGitHub
  • ActionQuery Honeycomb error-rate for canary vs baselineHoneycomb
  • LogicCompare error rate to budget
  • ActionRevert PR to draft and comment evidenceGitHubGitHub
  • OutputAlert on-call in SlackSlack

What it does

Guards the merge button. It watches the Honeycomb error rate for a service running a freshly bumped dependency and, when errors blow past your budget, it freezes the PR and writes the evidence into the conversation so nobody merges a broken upgrade.

When to use it

Use it when latency alone is not enough and you care most about new exceptions or 5xx counts introduced by a version bump. Ideal for libraries that touch hot paths or serialization where breakage shows up as errors, not slowness.

How it works

  1. 1A PR with the `canary` label is marked ready for review, signaling the canary is live.
  2. 2The workflow queries Honeycomb for the `error` count rate over the canary window versus the prior baseline.
  3. 3A logic step checks the rate against the configured error budget.
  4. 4If the budget is breached, it converts the PR back to draft and posts a comment with the spike numbers and a Honeycomb query link.
  5. 5It pings the on-call engineer in Slack with the PR and the failing metric.

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 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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