Introduction

Cloud ops—incident triage, scaling decisions, and cost tuning—is increasingly augmented (and in some cases delegated) to AI agents. They combine LLMs with cloud APIs, runbooks, and observability data. We explore what’s working and what’s still risky.

What Agents Can Do Today

Incident response Agents can read alerts, correlate logs, and suggest or execute runbook steps. We cover design patterns: approval gates, rollback triggers, and human escalation so automation stays safe.

Cost and resource optimization Right-sizing, scheduling, and spot/preemptible strategies are being automated. We discuss how to set bounds and audit agent actions so you don’t over-optimize into fragility.

Safety and Observability

Audit and rollback Every agent action should be logged and reversible. We outline how to implement audit trails and circuit breakers so autonomous ops remain trustworthy.

When to keep humans in the loop We suggest which decisions to automate fully vs. “assist and recommend” so you get efficiency without losing control.