What problem does it solve? Kubernetes failures like CrashLoopBackOff, OOMKilled, ImagePullBackOff, Pending pods, and NotReady nodes require deep, scattered operational knowledge to diagnose and fix quickly. This Skill provides structured decision trees and ready-to-run kubectl commands that guide an agent from symptom to root cause to a risk-tiered remediation plan. ## Core Features & Use Cases - Failure Decision Trees: Step-by-step diagnostic flows for pod states (Pending, CrashLoopBackOff, ImagePullBackOff), node conditions (MemoryPressure, DiskPressure), service/networking, PVC/storage, and HPA/VPA autoscaling issues. - Fix Paths with Risk Levels: Remediation procedures for OOMKilled, ImagePullBackOff, ReplicasMismatch, Node NotReady, CoreDNS, HPA, and PVC Pending, each with investigation commands, sizing guidance, risk tier (L1/L2), and rollback steps. - EKS Deep-Dive References: Detailed references covering VPC CNI behavior, prefix delegation, security groups for pods, kubelet logs, taints, QoS classes, exit codes, and pod eviction thresholds. - Use Case: A deployment shows 2/5 replicas ready. The Skill walks through checking pod events, node capacity, and resource limits, identifies memory limits that are too tight, applies kubectl set resources with a 2x-peak sizing rule, and provides a kubectl rollout undo rollback. ## Quick Start Ask the agent to diagnose why a specific pod in a namespace is stuck in CrashLoopBackOff and propose a fix with rollback steps.