AI AGENTS

On-Call Agent: PagerDuty Incident Triage with Approval-Gated Remediation

When PagerDuty pages, an agent pulls the firing service's Datadog metrics and recent deploys, writes a plain-English diagnosis.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPagerDuty incident firesPagerDutyPagerDuty
  • ActionPull service metrics from DatadogDatadogDatadog
  • ActionFetch recent deploys and commits from GitHubGitHubGitHub
  • LogicRank likely causes and map to runbook fixes
  • OutputPost diagnosis with approval-gated steps to SlackSlack

What it does

Turns a raw PagerDuty page into a triaged incident brief. The agent gathers signal from Datadog and GitHub, reasons about the likely cause, and proposes concrete fixes — but never acts on its own. A human approves in Slack first.

When to use it

Use it when your on-call rotation gets paged faster than humans can context-switch, and you want the first five minutes of investigation done before anyone opens a laptop. Best for teams that want speed without handing an agent unattended write access to production.

How it works

  1. 1A PagerDuty incident fires the workflow with the affected service and severity.
  2. 2The agent queries Datadog for that service's error rate, latency, and saturation over the last hour.
  3. 3It pulls the service's recent merged commits and deploys from GitHub to spot suspicious changes.
  4. 4Logic ranks candidate causes and matches each to a runbook remediation (rollback, scale up, restart, feature-flag off).
  5. 5The agent posts a diagnosis plus an ordered list of proposed steps to the incident's Slack channel, each behind an Approve button — nothing executes until a responder clicks.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PagerDutyIncidents, on-call, escalations.
  2. 2
    Connect DatadogMetrics, traces, log search.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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