AI AGENTS
Cost Spike Rollback Recommendation to Linear
On a confirmed cost spike, an agent decides whether the suspect deploy should be rolled back or investigated further.
How it runs
The automated pipeline, trigger to output.
- TriggerDatadog cost-anomaly monitor firesDatadog
- ActionPull suspect deploy and diffGitLab
- ActionCheck error-rate and latency shiftsDatadog
- LogicDecide rollback vs investigate
- OutputFile Linear issue with recommendationLinear
What it does
Goes one step past diagnosis and makes a call. When a cost spike is confirmed, the agent finds the suspect deploy, weighs the spike severity against the change's blast radius, and recommends either an immediate rollback or further investigation. It files a Linear issue carrying that recommendation, the reasoning, and links to the diff and metrics so an engineer can execute or override quickly.
When to use it
Use this when your team triages cost regressions through an engineering backlog and wants the workflow to propose a decision, not just surface data. Good for platform teams that own a rollback runbook and want it triggered with context.
How it works
- 1A Datadog cost-anomaly monitor triggers the run.
- 2The agent pulls the suspect deploy and its diff from GitLab.
- 3It checks Datadog for error-rate and latency changes alongside the cost jump.
- 4It branches: high spike plus risky change leans rollback; ambiguous signals lean investigate.
- 5It files a Linear issue with the recommendation, evidence, and priority set from severity.
Set it up
What you configure once, before turning it on.
- 1Connect DatadogMetrics, traces, log search.
- 2Connect GitLabRepos, MRs, pipelines, registry.
- 3Connect LinearIssues, projects, cycles, triage.
- 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.
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