AI Agents for DevOps in 2026: Tools That Are Actually Worth Using

A developer tested AI tools in Kubernetes workflows and found K8sGPT effective for cluster issue explanation, AI-assisted incident triage useful for log/metric correlation, and natural language infra provisioning promising but early. Fully autonomous remediation and AI-generated Helm charts were deemed overhyped due to production risks.

I've been testing a bunch of AI tools in my Kubernetes workflow over the past few months and wanted to share what's genuinely changed my day-to-day vs what's just marketing noise. What's actually working: - K8sGPT — scans your cluster and explains issues in plain English. Saved me a lot of time on pod crash debugging. Open source, worth trying. - AI-assisted incident triage — tools that correlate logs + metrics and surface root cause faster than manual grep-ing through Kibana - Natural language infra provisioning — still early but some teams are running Terraform via prompts in CI pipelines What's still overhyped: - Fully autonomous remediation without human approval too risky in prod - AI writing your Helm charts from scratch output needs heavy review Wrote a longer breakdown on my blog if anyone wants the full list with tool comparisons: https://infradecode.com https://infradecode.com Curious what tools others are actually running in production — anything I missed?