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AI agent for devops engineers

Cloud Cost Regression Investigation Agent

Every cost spike explained, with the right owner and a safe fix proposal.

Cloud Cost Regression Investigation Agent: what goes in, what the agent does and what you get

What it does

When the cloud bill spikes, engineers dig through deployments and usage reports by hand. When daily cost crosses the anomaly threshold, this agent correlates the increase with dated workload changes, such as deployments, traffic shifts and new resources. It forms a hypothesis for the largest cost line and runs read-only queries to separate growth from waste. If cost per request stays stable, the increase is growth, and it revises its view or moves to the next resource. When waste is confirmed, it creates an investigation task for the resource owner with a reversible fix proposal. Infrastructure leads approve changes. Edge case: storage cost doubles, but it tracks a new data retention policy, so it is recorded as expected.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Cost anomaly detected 2 USES A TOOL Correlate the increase with deployments and usage 3 DOES Form a cause hypothesis for the largest cost line 4 USES A TOOL Run read-only resource and unit-cost queries 5 CHECKS THE RESULT Does the evidence support waste rather than growth? If not: investigate the next resource or concludegrowth. Back to step 3. 6 DOES Create an owner task with a reversible proposal 7 YOU APPROVE Infrastructure lead approves changes 8 RESULT Source-linked cost investigation case
Read the steps as a list
  1. Cost anomaly detected
  2. Correlate the increase with deployments and usage
  3. Form a cause hypothesis for the largest cost line
  4. Run read-only resource and unit-cost queries
  5. Does the evidence support waste rather than growth?If not: investigate the next resource or conclude growth. Back to step 3.
  6. Create an owner task with a reversible proposal
  7. Infrastructure lead approves changesThe agent waits here for your OK.
  8. Source-linked cost investigation case

How it decides

It tests explanations in order of size and checks unit cost to tell growth from waste.

  • Stable unit cost means growth, not waste.
  • Owners come from resource tags.
  • Only reversible changes are proposed.

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Anomaly threshold (default 20% above the 14-day average)
  • Cost sources and tag that identifies owners
  • Unit cost metric per service (default cost per request)
  • Who approves changes

What keeps you in control

It always asks you first

  • Scaling resources
  • Deleting data
  • Configuration changes

Hard limits

  • Read-only queries.

It stops when

  • Done: cause found or growth confirmed.

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensDaily cost rose from $2,100 to $3,050 on October 2. The agent tied 70% of the rise to the search cluster. Requests had grown 40% but cost per request was flat, so the waste check failed and the agent moved on. Logging cost had tripled after a debug flag was left on. It created a task for the platform team proposing to turn the flag off, which the lead approved.

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