AI & RAG

Suggest a runbook to the responder when a PagerDuty incident triggers

On a new PagerDuty incident, retrieves the most similar past postmortems and posts a suggested remediation playbook as a note on the incident so the responder starts with context.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPagerDuty incident.triggered webhook firesPagerDutyPagerDuty
  • ActionEmbed the alert and retrieve similar postmortems for the same service from PostgresPostgreSQLPostgres
  • LogicWiden candidate set for high-urgency incidents
  • ActionSummarize matches into a concise remediation playbookOpenAI
  • OutputAttach the playbook as a note on the PagerDuty incidentPagerDutyPagerDuty

What it does

The moment a PagerDuty incident fires, this flow looks up the closest historical postmortems by the alert's title and service, drafts a short "here's what worked last time" playbook, and attaches it directly to the incident as a note. The responder opens the page already armed with prior art.

When to use it

Use it to cut time-to-mitigation for recurring failure modes. Especially valuable for services that page often, where the same root causes resurface and institutional memory lives in old postmortems no one rereads.

How it works

  1. 1A PagerDuty incident.triggered webhook starts the flow with the alert title, service, and urgency.
  2. 2The alert text is embedded and matched against the Postgres postmortem vector table, filtered to the same affected service.
  3. 3A logic step routes high-urgency incidents to include more candidate matches than low-urgency ones.
  4. 4The model summarizes the matched postmortems into a concise, actionable remediation playbook with confidence caveats.
  5. 5The playbook is written back to the PagerDuty incident as a note for the responder.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PagerDutyIncidents, on-call, escalations.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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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