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K8s Debug

  • 491 installs
  • 286 repo stars
  • Updated July 26, 2026
  • akin-ozer/cc-devops-skills

k8s-debug is a Claude Code skill that triages failing Kubernetes pods, crash loops, networking faults, and resource limits so developers who run production clusters can restore service and document root causes during inc

About

k8s-debug is a Claude Code skill in akin-ozer/cc-devops-skills aimed at developers responding to live Kubernetes incidents. It guides systematic triage of pods in CrashLoopBackOff, image pull failures, OOMKilled containers, probe misconfigurations, Service and Ingress networking breaks, DNS issues, and CPU or memory limit exhaustion. The workflow emphasizes kubectl-oriented evidence gathering—logs, events, describe output, and endpoint checks—so engineers can distinguish transient noise from configuration or quota problems worth a permanent fix. Teams invoke k8s-debug when a deployment rolls out but workloads never become Ready, when traffic stops reaching pods behind a Service, or when HPA or limit changes suddenly spike restarts. It complements cluster provisioning skills by focusing on fast restoration and root-cause capture under incident pressure.

  • kubectl diagnostic workflows
  • Pod crash loop analysis
  • Service and ingress checks
  • Resource quota troubleshooting
  • Rollout rollback guidance

K8s Debug by the numbers

  • 491 all-time installs (skills.sh)
  • Ranked #89 of 596 Debugging skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
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Installs491
repo stars286
Last updatedJuly 26, 2026
Repositoryakin-ozer/cc-devops-skills

Why are Kubernetes pods crash looping?

Triage failing pods, crash loops, networking, and resource limits in Kubernetes clusters to restore service quickly and capture root causes during live incidents.

Who is it for?

Platform and backend developers on call for Kubernetes who need a structured incident triage playbook for pods, networking, and resource limits.

Skip if: Teams provisioning new clusters from scratch or developers who only deploy to serverless platforms without kubectl access.

When should I use this skill?

A developer reports failing pods, CrashLoopBackOff, networking outages, or resource limit errors in a live Kubernetes cluster and needs structured triage commands.

What you get

Root-cause hypothesis, kubectl evidence summary, and remediation steps for pods, networking, or resource limits blocking service recovery.

  • Incident triage notes
  • Root-cause summary
  • Remediation command list

Files

SKILL.mdMarkdownGitHub ↗

Kubernetes Debugging Skill

Overview

Systematic toolkit for debugging Kubernetes clusters, workloads, networking, and storage with a deterministic, safety-first workflow.

Trigger Phrases

Use this skill when requests resemble:

  • "My pod is in CrashLoopBackOff; help me find the root cause."
  • "Service DNS works in one pod but not another."
  • "Deployment rollout is stuck."
  • "Pods are Pending and not scheduling."
  • "Cluster health looks degraded after a change."
  • "PVC is pending and pods cannot mount storage."

Prerequisites

Run from the skill directory (devops-skills-plugin/skills/k8s-debug) so relative script paths work as written.

Required

  • kubectl installed and configured.
  • An active cluster context.
  • Read access to namespaces, pods, events, services, and nodes.

Quick preflight:

kubectl config current-context
kubectl auth can-i get pods -A
kubectl auth can-i get events -A
kubectl get ns

Optional but Recommended

  • jq for more precise filtering in ./scripts/cluster_health.sh.
  • Metrics API (metrics-server) for kubectl top.
  • In-container debug tools (nslookup, getent, curl, wget, ip) for deep network tests.

Fallback behavior:

  • If optional tools are missing, scripts continue and print warnings with reduced output.
  • If kubectl top is unavailable, continue with kubectl describe and events.

When to Use This Skill

Use this skill for:

  • Pod failures (CrashLoopBackOff, ImagePullBackOff, Pending, OOMKilled)
  • Service connectivity or DNS resolution issues
  • Network policy or ingress problems
  • Volume and storage mount failures
  • Deployment rollout issues
  • Cluster health or performance degradation
  • Resource exhaustion (CPU/memory)
  • Configuration problems (ConfigMaps, Secrets, RBAC)

Safety Rules for Disruptive Commands

Default mode is read-only diagnosis first. Only execute disruptive commands after confirming blast radius and rollback.

Commands requiring explicit confirmation:

  • kubectl delete pod ... --force --grace-period=0
  • kubectl drain ...
  • kubectl rollout restart ...
  • kubectl rollout undo ...
  • kubectl debug ... --copy-to=...

Before disruptive actions:

# Snapshot current state for rollback and incident notes
kubectl get deploy,rs,pod,svc -n <namespace> -o wide
kubectl get pod <pod-name> -n <namespace> -o yaml > before-<pod-name>.yaml
kubectl get events -n <namespace> --sort-by='.lastTimestamp' > before-events.txt

Reference Navigation Map

Load only the section needed for the observed symptom.

Symptom / NeedOpenStart section
You need an end-to-end diagnosis path./references/troubleshooting_workflow.mdGeneral Debugging Workflow
Pod state is Pending, CrashLoopBackOff, or ImagePullBackOff./references/troubleshooting_workflow.mdPod Lifecycle Troubleshooting
Service reachability or DNS failure./references/troubleshooting_workflow.mdNetwork Troubleshooting Workflow
Node pressure or performance regression./references/troubleshooting_workflow.mdResource and Performance Workflow
PVC / PV / storage class issues./references/troubleshooting_workflow.mdStorage Troubleshooting Workflow
Quick symptom-to-fix lookup./references/common_issues.mdmatching issue heading
Post-mortem fix options for known issues./references/common_issues.mdSolutions sections

Scripts Overview

ScriptPurposeRequired argsOptional argsOutputFallback behavior
./scripts/cluster_health.shCluster-wide health snapshot (nodes, workloads, events, common failure states)None--strict, K8S_REQUEST_TIMEOUT env varSectioned report to stdoutContinues on check failures, tracks them in summary and exit code
./scripts/network_debug.shPod-centric network and DNS diagnostics<pod-name> (<namespace> defaults to default)--strict, --insecure, K8S_REQUEST_TIMEOUT env varSectioned report to stdoutUses secure API probe by default; insecure TLS requires explicit --insecure
./scripts/pod_diagnostics.pyDeep pod diagnostics (status, describe, YAML, events, per-container logs, node context)<pod-name>-n/--namespace, -o/--outputSectioned report to stdout or fileFails fast on missing access; skips optional metrics/log blocks with clear messages

Script Exit Codes

./scripts/cluster_health.sh and ./scripts/network_debug.sh share the same contract:

  • 0: checks completed with no check failures (warnings allowed unless --strict is set).
  • 1: one or more checks failed, or warnings occurred in --strict mode.
  • 2: blocked preconditions (for example: missing kubectl, no active context, inaccessible namespace/pod).

Deterministic Debugging Workflow

Follow this systematic approach for any Kubernetes issue:

1. Preflight and Scope

kubectl config current-context
kubectl get ns
kubectl auth can-i get pods -n <namespace>

If preflight fails, stop and fix access/context first.

2. Identify the Problem Layer

Categorize the issue:

  • Application Layer: Application crashes, errors, bugs
  • Pod Layer: Pod not starting, restarting, or pending
  • Service Layer: Network connectivity, DNS issues
  • Node Layer: Node not ready, resource exhaustion
  • Cluster Layer: Control plane issues, API problems
  • Storage Layer: Volume mount failures, PVC issues
  • Configuration Layer: ConfigMap, Secret, RBAC issues

3. Gather Diagnostics with the Right Script

Use the appropriate diagnostic script based on scope:

Pod-Level Diagnostics

Use ./scripts/pod_diagnostics.py for comprehensive pod analysis:

python3 ./scripts/pod_diagnostics.py <pod-name> -n <namespace>

This script gathers:

  • Pod status and description
  • Pod events
  • Container logs (current and previous)
  • Resource usage
  • Node information
  • YAML configuration

Output can be saved for analysis:

python3 ./scripts/pod_diagnostics.py <pod-name> -n <namespace> -o diagnostics.txt
Cluster-Level Health Check

Use ./scripts/cluster_health.sh for overall cluster diagnostics:

./scripts/cluster_health.sh > cluster-health-$(date +%Y%m%d-%H%M%S).txt

This script checks:

  • Cluster info and version
  • Node status and resources
  • Pods across all namespaces
  • Failed/pending pods
  • Recent events
  • Deployments, services, statefulsets, daemonsets
  • PVCs and PVs
  • Component health
  • Common error states (CrashLoopBackOff, ImagePullBackOff)
Network Diagnostics

Use ./scripts/network_debug.sh for connectivity issues:

./scripts/network_debug.sh <namespace> <pod-name>
# or force warning sensitivity / insecure TLS only when explicitly needed:
./scripts/network_debug.sh --strict <namespace> <pod-name>
./scripts/network_debug.sh --insecure <namespace> <pod-name>

This script analyzes:

  • Pod network configuration
  • DNS setup and resolution
  • Service endpoints
  • Network policies
  • Connectivity tests
  • CoreDNS logs

4. Follow Issue-Specific Reference Workflow

Based on the identified issue, consult ./references/troubleshooting_workflow.md:

  • Pod Pending: Resource/scheduling workflow
  • CrashLoopBackOff: Application crash workflow
  • ImagePullBackOff: Image pull workflow
  • Service issues: Network connectivity workflow
  • DNS failures: DNS troubleshooting workflow
  • Resource exhaustion: Performance investigation workflow
  • Storage issues: PVC binding workflow
  • Deployment stuck: Rollout workflow

5. Apply Targeted Fixes

Refer to ./references/common_issues.md for symptom-specific fixes.

6. Verify and Close

Run final verification:

kubectl get pods -n <namespace> -o wide
kubectl get events -n <namespace> --sort-by='.lastTimestamp' | tail -20
kubectl rollout status deployment/<name> -n <namespace>

Issue is done when user-visible behavior is healthy and no new critical warning events appear.

Example Flows

Example 1: CrashLoopBackOff in payments Namespace

python3 ./scripts/pod_diagnostics.py payments-api-7c97f95dfb-q9l7k -n payments -o payments-diagnostics.txt
kubectl logs payments-api-7c97f95dfb-q9l7k -n payments --previous --tail=100
kubectl get deploy payments-api -n payments -o yaml | grep -A 8 livenessProbe

Then open ./references/common_issues.md and apply the CrashLoopBackOff solutions.

Example 2: Service DNS/Connectivity Failure

./scripts/network_debug.sh checkout checkout-api-75f49c9d8f-z6qtm
kubectl get svc checkout-api -n checkout
kubectl get endpoints checkout-api -n checkout
kubectl get networkpolicies -n checkout

Then follow Service Connectivity Workflow in ./references/troubleshooting_workflow.md.

Essential Manual Commands

Pod Debugging

# View pod status
kubectl get pods -n <namespace> -o wide

# Detailed pod information
kubectl describe pod <pod-name> -n <namespace>

# View logs
kubectl logs <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --previous  # Previous container
kubectl logs <pod-name> -n <namespace> -c <container>  # Specific container

# Execute commands in pod
kubectl exec <pod-name> -n <namespace> -it -- /bin/sh

# Get pod YAML
kubectl get pod <pod-name> -n <namespace> -o yaml

Service and Network Debugging

# Check services
kubectl get svc -n <namespace>
kubectl describe svc <service-name> -n <namespace>

# Check endpoints
kubectl get endpoints -n <namespace>

# Test DNS
kubectl exec <pod-name> -n <namespace> -- nslookup kubernetes.default

# View events
kubectl get events -n <namespace> --sort-by='.lastTimestamp'

Resource Monitoring

# Node resources
kubectl top nodes
kubectl describe nodes

# Pod resources
kubectl top pods -n <namespace>
kubectl top pod <pod-name> -n <namespace> --containers

Emergency Operations

# Restart deployment
kubectl rollout restart deployment/<name> -n <namespace>

# Rollback deployment
kubectl rollout undo deployment/<name> -n <namespace>

# Force delete stuck pod
kubectl delete pod <pod-name> -n <namespace> --force --grace-period=0

# Drain node (maintenance)
kubectl drain <node-name> --ignore-daemonsets --delete-emptydir-data

# Cordon node (prevent scheduling)
kubectl cordon <node-name>

Completion Criteria

Troubleshooting session is complete when all are true:

  • [ ] Cluster context and namespace are confirmed.
  • [ ] Relevant diagnostic script output is captured.
  • [ ] Root cause is identified and tied to evidence (events/logs/config/state).
  • [ ] Any disruptive action was preceded by snapshot and rollback plan.
  • [ ] Fix verification commands show healthy state.
  • [ ] Reference path used (./references/troubleshooting_workflow.md or ./references/common_issues.md) is documented in notes.

Related Tools

Useful additional tools for Kubernetes debugging:

  • kubectl-debug: Advanced debugging plugin
  • stern: Multi-pod log tailing
  • kubectx/kubens: Context and namespace switching
  • k9s: Terminal UI for Kubernetes
  • lens: Desktop IDE for Kubernetes
  • Prometheus/Grafana: Monitoring and alerting
  • Jaeger/Zipkin: Distributed tracing

Related skills

How it compares

Use k8s-debug for live incident triage; use a cluster provisioning or Helm skill when standing up new environments rather than fixing broken workloads.

FAQ

What Kubernetes failures does k8s-debug cover?

k8s-debug covers failing pods, crash loops, networking problems, and resource limit exhaustion in live clusters. The skill emphasizes kubectl logs, events, and describe output to separate config errors from quota or probe issues.

When should teams invoke k8s-debug?

k8s-debug fits active incidents where deployments never become Ready, Services lose endpoints, or restarts spike after limit changes. The skill prioritizes fast service restoration plus root-cause notes for durable fixes.

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