AI AGENTS
Build an incident context pack and stage next steps when PagerDuty pages
On a PagerDuty page, an agent gathers the triggering Sentry errors and Datadog dashboards, assembles a single context pack.
How it runs
The automated pipeline, trigger to output.
- TriggerPagerDuty incident pages on-callPagerDuty
- ActionRead incident and linked Sentry issuesSentry
- ActionPull Datadog dashboards and deploy timelineDatadog
- LogicAssemble dedup context pack and step checklist
- OutputPost approvable checklist to incident Slack channelSlack
What it does
Gives the paged responder everything in one place. Instead of opening five tabs, the agent collects the linked Sentry issues, the relevant Datadog graphs, and recent deploys, then writes a short situation summary plus an ordered checklist of suggested actions. The responder checks off and approves each step from Slack.
When to use it
Use it the moment a PagerDuty incident fires and you want to shave minutes off the orient phase. Best for teams whose incidents reliably span both error tracking and metrics, where context-gathering is the slowest part of MTTR.
How it works
- 1A PagerDuty incident triggers the workflow on page.
- 2The agent reads the incident, its service, and any linked Sentry issues.
- 3It pulls the matching Datadog dashboards, error rates, and deploy timeline for the affected service.
- 4Logic assembles a deduplicated context pack and drafts an ordered, approvable checklist of next steps.
- 5The pack and checklist post to the incident Slack channel, each step gated behind an approval action.
Set it up
What you configure once, before turning it on.
- 1Connect PagerDutyIncidents, on-call, escalations.
- 2Connect SentryErrors, performance, releases.
- 3Connect DatadogMetrics, traces, log search.
- 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.
More AI Agents workflows
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Weekly On-Call Doc-Gap Digest
Each week the agent reviews every Sentry issue resolved in the last 7 days, ranks the ones whose runbook coverage is missing or thin.
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.
Run this workflow in your colony.
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