SUMMARIZATION
Honeycomb anomaly to PagerDuty triage narrative
When a Honeycomb anomaly trigger fires during an active page, summarizes the slow-span cluster into a triage note and attaches it to the matching PagerDuty incident…
How it runs
The automated pipeline, trigger to output.
- TriggerHoneycomb anomaly trigger firesHoneycomb
- ActionIsolate dominant slow-span cluster from tracesHoneycomb
- LogicExit if no matching open PagerDuty incident
- ActionCompose triage note with first checksOpenAI
- ActionAttach note to PagerDuty incident timelinePagerDuty
- OutputPost confirmation to perf channelSlack
What it does
This workflow enriches a live PagerDuty incident with a Honeycomb-derived diagnosis. When an anomaly trigger fires, it identifies the slow-span cluster driving the anomaly, writes a plain-English triage note describing the affected service path and likely blast radius, and attaches that note to the open PagerDuty incident so the responder reads a head start instead of a metric.
When to use it
Use it on critical services where the on-call needs to move fast. Instead of opening Honeycomb cold at 3am, the responder sees which operation slowed, which downstream calls are implicated, and where to look first.
How it works
- 1A Honeycomb anomaly trigger fires for a watched service.
- 2The workflow pulls the anomalous traces and isolates the dominant slow-span cluster.
- 3It checks for an open PagerDuty incident matching the service; if none exists, it exits.
- 4An LLM composes a triage note: affected path, latency delta, and suggested first checks.
- 5The note is added to the PagerDuty incident timeline.
- 6A short confirmation with the note link posts to the perf Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect PagerDutyIncidents, on-call, escalations.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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