AI AGENTS
On-Call Agent: Scheduled Service Health Sweep with Pre-Page Warnings
On a schedule, an agent sweeps your fleet's Datadog health signals, flags services trending toward failure.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled sweep starts
- ActionRead fleet health metrics from DatadogDatadog
- LogicScore degradation trend per service
- LogicDrop healthy services, keep at-risk ones
- OutputPost prioritized watchlist to SlackSlack
What it does
Runs a proactive health check across all your services on a cadence you set. Instead of waiting for an alert, the agent looks for slow-burn degradations — climbing latency, shrinking headroom, rising error rates — and surfaces them early.
When to use it
Use it as a daily or hourly standup for your infrastructure when you want to catch problems before they become pages. Ideal for teams that prefer to fix things during business hours rather than during incidents.
How it works
- 1A schedule (for example every morning) starts the sweep.
- 2The agent reads health metrics for each tracked service from Datadog over the recent trailing window.
- 3Logic scores each service for degradation trend and proximity to known alert thresholds.
- 4Services that are healthy are dropped; only those trending toward trouble move forward, each tagged with a suggested preventive step.
- 5The agent posts a ranked watchlist to Slack so on-call can act on the worst offenders first — no remediation runs automatically.
Set it up
What you configure once, before turning it on.
- 1Connect DatadogMetrics, traces, log search.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
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.
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.
Datadog Bill Spike Attribution Agent
When a daily Datadog cost check detects a spend jump, an agent attributes the increase to the specific services and metric types driving it and posts a ranked breakdown to Slack.
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.
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.
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.
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.
