AI AGENTS
Draft a fix PR from a Datadog monitor alert and wait for review
When a Datadog monitor goes critical, an agent matches it to your runbook, drafts a targeted GitHub pull request implementing the documented fix.
How it runs
The automated pipeline, trigger to output.
- TriggerDatadog monitor goes criticalDatadog
- ActionRead monitor tags and metric valuesDatadog
- LogicMatch to runbook; route to manual if no code fix
- ActionOpen draft GitHub PR with the documented fixGitHub
- OutputRequest on-call review and post link to SlackSlack
What it does
Closes the gap between a Datadog alert and the actual code change. The agent reads the firing monitor, finds the matching runbook entry, and opens a draft GitHub PR that implements the prescribed remediation (bump a timeout, raise a pool size, revert a config). A human reviews and merges — the agent never merges on its own.
When to use it
Use it when your recurring alerts have well-documented, code-level fixes that are tedious to type out at 2am but risky to fully automate. Ideal for infra-as-code repos where most remediations are small, reviewable diffs.
How it works
- 1A Datadog monitor transitions to the critical state and triggers the workflow.
- 2The agent reads the monitor name, tags, and current metric values to identify the affected service.
- 3It matches the alert to a runbook and decides whether a code-level fix exists; if not, it routes to manual triage.
- 4The agent opens a draft GitHub PR with the change, an explanation, and a link to the alert.
- 5It requests review from the on-call team and posts the PR link to Slack for visibility.
Set it up
What you configure once, before turning it on.
- 1Connect DatadogMetrics, traces, log search.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, 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.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.