DEVOPS
Edge Canary: Agentic Multi-Signal Regression Triage
On a Honeycomb burn-alert during a canary, an agent correlates the regression against the GitHub diff, recent error traces, and infra changes.
How it runs
The automated pipeline, trigger to output.
- TriggerHoneycomb burn-rate alert webhookHoneycomb
- ActionFetch canary GitHub diff and changed filesGitHub
- ActionSample failing traces and error signatureHoneycomb
- LogicDoes the diff plausibly explain the regression?
- ActionPause Cloudflare rollout on high confidenceCloudflare
- OutputPost triage rationale to Slack and PagerDutySlack
What it does
When Honeycomb flags an error-budget regression mid-canary, an agent investigates rather than just alerting. It pulls the deploy's GitHub diff, samples failing traces from Honeycomb, and weighs whether the regression is plausibly caused by the new code or by unrelated noise. It then recommends a pause-or-continue action with a written rationale, and pauses the Cloudflare rollout when its confidence is high.
When to use it
Use for services where naive threshold auto-pause causes too many false halts and you want a reasoning layer that distinguishes a genuine code-caused regression from a coincident spike before freezing a deploy.
How it works
- 1A Honeycomb burn-rate alert webhook fires during an active canary.
- 2The agent fetches the canary's GitHub diff and changed files for context.
- 3The agent queries Honeycomb for representative failing traces and the error signature.
- 4It reasons over whether the diff plausibly explains the failures and forms a confidence-scored recommendation.
- 5On high-confidence regression it pauses the Cloudflare gradual deployment.
- 6It posts its findings and recommendation to Slack and annotates the PagerDuty incident.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Connect PagerDutyIncidents, on-call, escalations.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
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