AI & RAG

PagerDuty Escalation Brief from Cited Runbook Steps

On a PagerDuty escalation, assembles a grounded incident brief by retrieving the service's runbook and recent Sentry errors.

CategoryAI & RAG
Enginepaperclip
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPagerDuty incident escalates to next tierPagerDutyPagerDuty
  • ActionRetrieve matching runbook + version from ConfluenceConfluenceConfluence
  • ActionFetch recent Sentry errors for the affected serviceSentrySentry
  • ActionGround cited remediation brief in runbook text
  • OutputWrite cited brief as a PagerDuty incident notePagerDutyPagerDuty

What it does

When an incident escalates to the next tier, the agent builds a ready-to-act brief instead of a cold handoff. It pulls the affected service's runbook from Confluence, correlates the latest Sentry error context, and writes a PagerDuty note listing the exact remediation steps with the runbook version they came from — so the escalation responder starts solving, not researching.

When to use it

Use it when escalations lose time because the receiving engineer has to reconstruct context from scratch. Best for teams where PagerDuty drives escalation and runbooks plus Sentry errors hold the answer.

How it works

  1. 1PagerDuty escalates an incident, triggering the workflow with the service and incident summary.
  2. 2The agent retrieves the matching runbook from Confluence with its version.
  3. 3It fetches the most recent Sentry errors for the same service to add concrete failure context.
  4. 4It grounds a step-by-step remediation brief strictly in the retrieved runbook, citing each step's number.
  5. 5The brief is written back to the PagerDuty incident as a timeline note for the next responder.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PagerDutyIncidents, on-call, escalations.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  3. 3
    Connect SentryErrors, performance, releases.
  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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