ENGINEERING
Dependency Canary: AI Triage of Honeycomb Regressions
When a dependency canary shows a latency regression, pulls the slowest Honeycomb traces, has an AI agent diagnose the likely cause from the dependency changelog and trace spans.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled scan of regressed canary PRs
- ActionFetch slow traces and span breakdown from HoneycombHoneycomb
- ActionRead changed dependency and diff from GitHubGitHub
- ActionAI agent diagnoses likely causeOpenAI
- OutputPost triage note as GitHub PR reviewGitHub
What it does
Does the first pass of root-cause analysis for you. When a canary regresses, it gathers the slowest traces from Honeycomb, reads the dependency's changelog, and asks an AI agent to explain what likely changed and which spans got slower, then leaves that as a structured PR review.
When to use it
Use it when regressions are common enough that triage eats reviewer time. The agent's note gives the human a head start: suspected call, magnitude, and whether the changelog mentions a relevant change.
How it works
- 1A scheduled check runs against open canary PRs that an earlier step flagged as regressed.
- 2It fetches the top slow traces and per-span breakdown from Honeycomb for the service.
- 3It reads the changed dependency and version from the PR diff via GitHub.
- 4An OpenAI agent correlates the slow spans with the version's release notes and drafts a plain-language diagnosis with a confidence level.
- 5The workflow posts the diagnosis as a GitHub review comment and links the supporting Honeycomb trace.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect HoneycombDistributed traces and queries.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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