Kubernetes Cluster AI Diagnostic Expert

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.