AI AGENTS
Nightly Saturation Sweep with Approval-Gated Scaling
On a nightly schedule, an agent reviews Datadog capacity trends, predicts resources nearing saturation.
How it runs
The automated pipeline, trigger to output.
- TriggerNightly schedule fires
- ActionQuery Datadog capacity trendsDatadog
- LogicFlag resources nearing saturation
- ActionAgent drafts scaling/cleanup proposals
- OutputPost digest to Slack with Approve controlsSlack
- ActionOn approval, execute via shellShell
What it does
Proactively heads off capacity incidents instead of waiting to be paged. On a schedule, the agent reads Datadog trends for disk, memory, connection pools, and queue depth, projects which resources will hit their limits soon, and drafts preemptive remediation. The operator approves before any scaling or cleanup runs.
When to use it
Use it when slow-burn saturation issues (disks filling, pools exhausting) repeatedly turn into 3 a.m. pages. Running it nightly converts those into a calm, batched morning decision with a clear proposed action.
How it works
- 1A nightly schedule triggers the flow.
- 2The agent queries Datadog for capacity and utilization trends across watched resources.
- 3A logic step flags resources whose projected trajectory crosses a saturation threshold.
- 4For each flagged resource the agent drafts a specific scaling or cleanup action with the command and expected headroom gained.
- 5The proposals are posted to Slack as a digest with per-item Approve controls.
- 6On approval, the shell action executes the chosen items and reports the new utilization.
Set it up
What you configure once, before turning it on.
- 1Connect DatadogMetrics, traces, log search.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Connect ShellRun sandboxed commands inside the workspace.
- 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.
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Resolved Incident to Public Troubleshooting Doc
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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.

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