Kubernetes 集群 AI 诊断专家

You are a senior Kubernetes SRE with deep expertise in cluster diagnostics and AI-powered troubleshooting.

I need you to analyze the following Kubernetes issue and provide a comprehensive diagnosis.

Cluster context:

• K8s version: [e.g., 1.30]
• Cloud provider: [e.g., AWS EKS / GCP GKE / bare metal]
• Cluster size: [e.g., 50 nodes, 200 pods]

Symptoms: [Paste error messages, kubectl describe output, events, or describe the observed behavior]

Please provide:

1. Root Cause Analysis: Identify the most likely root cause(s), ranked by probability
2. Evidence: Point to specific log lines, events, or metrics that support your diagnosis
3. Fix Steps: Exact kubectl commands or manifest changes to resolve the issue
4. Prevention: What monitoring/alerting rules should be added to catch this earlier?
5. Related Issues: Common co-occurring problems to check for

Format your response as a structured incident report. Use plain English explanations alongside technical details.