k8s-troubleshooter

Q: How do I install k8s-troubleshooter?

Run npx skills add https://github.com/ahmedasmar/devops-claude-skills --skill k8s-troubleshooter in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/k8s-troubleshooter/ (personal) or .claude/skills/k8s-troubleshooter/ (project).

by ahmedasmarDevOps & Cloud

Systematic Kubernetes troubleshooting and incident response. Use this skill whenever the user mentions Kubernetes, K8s, kubectl, pods, containers, or clusters. Triggers include diagnosing CrashLoopBackOff, ImagePullBackOff, OOMKilled, or Pending pods, responding to production incidents, troubleshooting node NotReady or DiskPressure, debugging service connectivity or networking, investigating PVC or storage failures, analyzing performance degradation, checking cluster health, troubleshooting Helm releases, and conducting post-incident reviews.

Installs: 59
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Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/ahmedasmar/devops-claude-skills --skill k8s-troubleshooter

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads k8s-troubleshooter automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Kubernetes Troubleshooter & Incident Response

Systematic approach to diagnosing and resolving Kubernetes issues in production environments.

Core Troubleshooting Workflow

Follow this systematic approach for any Kubernetes issue:

1. Gather Context

What is the observed symptom?
When did it start?
What changed recently (deployments, config, infrastructure)?
What is the scope (single pod, service, node, cluster)?
What is the business impact (severity level)?

2. Initial Triage

Run cluster health check:

# Check node status and health
kubectl get nodes

# Find non-running pods across all namespaces
kubectl get pods -A --field-selector status.phase!=Running

# Check node resource usage
kubectl top nodes

This provides an overview of:

Node health status
Pending and failed pods across all namespaces
Node resource utilization

3. Deep Dive Investigation

Based on triage results, focus investigation:

For Namespace-Level Issues:

python3 scripts/check_namespace.py <namespace>

This provides comprehensive namespace health:

Pod status (running, pending, failed, crashlooping)
Service health and endpoints
Deployment availability
PVC status
Resource quota usage
Recent events
Actionable recommendations

For Pod Issues:

# Get full pod details (status, events, conditions, resource config)
kubectl describe pod <pod-name> -n <namespace>

# Check current and previous container logs
kubectl logs <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --previous

# Get events specific to the pod
kubectl get events -n <namespace> --field-selector involvedObject.name=<pod-name>

This reveals:

Pod phase and readiness
Container statuses and states
Restart counts and exit codes
Recent events and scheduling decisions
Resource requests and limits

For additional investigations:

Check all namespace events: kubectl get events -n <namespace> --sort-by='.lastTimestamp'

4. Identify Root Cause

Consult references/common_issues.md for detailed information on:

ImagePullBackOff / ErrImagePull
CrashLoopBackOff
Pending Pods
OOMKilled
Node issues (NotReady, DiskPressure)
Networking failures
Storage/PVC issues
Resource quotas and throttling
RBAC permission errors

Each issue includes:

Symptoms
Common causes
Diagnostic commands
Remediation steps
Prevention strategies

5. Apply Remediation

Follow remediation steps from common_issues.md based on root cause identified.

Always:

Test fixes in non-production first if possible
Document actions taken
Monitor for effectiveness
Have rollback plan ready

6. Verify & Monitor

After applying fix:

Verify issue is resolved
Monitor for recurrence (15-30 minutes minimum)
Check related systems
Update documentation

Incident Response

For production incidents, follow structured response in references/incident_response.md:

Severity Assessment:

SEV-1 (Critical): Complete outage, data loss, security breach
SEV-2 (High): Major degradation, significant user impact
SEV-3 (Medium): Minor impairment, workaround available
SEV-4 (Low): Cosmetic, minimal impact

Incident Phases:

Detection - Identify and assess
Triage - Determine scope and impact
Investigation - Find root cause
Resolution - Apply fix
Post-Incident - Document and improve

Common Incident Scenarios:

Complete cluster outage
Service degradation
Node failure
Storage issues
Security incidents

See references/incident_response.md for detailed playbooks.

Quick Reference Commands

Cluster Overview

kubectl cluster-info
kubectl get nodes
kubectl get pods --all-namespaces | grep -v Running
kubectl get events --all-namespaces --sort-by='.lastTimestamp' | tail -20

Pod Diagnostics

kubectl describe pod <pod> -n <namespace>
kubectl logs <pod> -n <namespace>
kubectl logs <pod> -n <namespace> --previous
kubectl exec -it <pod> -n <namespace> -- /bin/sh
kubectl get pod <pod> -n <namespace> -o yaml

Node Diagnostics

kubectl describe node <node>
kubectl top nodes
kubectl top pods --all-namespaces
ssh <node> "systemctl status kubelet"
ssh <node> "journalctl -u kubelet -n 100"

Service & Network

kubectl describe svc <service> -n <namespace>
kubectl get endpoints <service> -n <namespace>
kubectl get networkpolicies --all-namespaces

Storage

kubectl get pvc,pv --all-namespaces
kubectl describe pvc <pvc> -n <namespace>
kubectl get storageclass

Resource & Configuration

kubectl describe resourcequota -n <namespace>
kubectl describe limitrange -n <namespace>
kubectl get rolebindings,clusterrolebindings -n <namespace>

Diagnostic Scripts

check_namespace.py

Namespace-level health check and diagnostics:

Pod health (running, pending, failed, crashlooping, image pull errors)
Service health and endpoints
Deployment availability status
PersistentVolumeClaim status
Resource quota usage and limits
Recent namespace events
Health status assessment
Actionable recommendations

Usage:

# Human-readable output
python3 scripts/check_namespace.py <namespace>

# JSON output for automation
python3 scripts/check_namespace.py <namespace> --json

# Include more events
python3 scripts/check_namespace.py <namespace> --events 20

Best used when troubleshooting issues in a specific namespace or assessing overall namespace health.

Cluster-Level Diagnostics (kubectl)

For cluster-wide health checks, use kubectl directly:

# Node health and status
kubectl get nodes
kubectl top nodes

# Find non-running pods across all namespaces
kubectl get pods -A --field-selector status.phase!=Running

# System pod health
kubectl get pods -n kube-system

Pod-Level Diagnostics (kubectl)

For detailed pod investigation, use kubectl directly:

# Full pod details (status, events, conditions, resource config)
kubectl describe pod <pod-name> -n <namespace>

# Current and previous container logs
kubectl logs <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --previous

# Events specific to the pod
kubectl get events -n <namespace> --field-selector involvedObject.name=<pod-name>

Reference Documentation

references/common_issues.md

Comprehensive guide to common Kubernetes issues with:

Detailed symptom descriptions
Root cause analysis
Step-by-step diagnostic procedures
Remediation instructions
Prevention strategies

Covers:

Pod issues (ImagePullBackOff, CrashLoopBackOff, Pending, OOMKilled)
Node issues (NotReady, DiskPressure)
Networking issues (pod-to-pod communication, service access)
Storage issues (PVC pending, volume mount failures)
Resource issues (quota exceeded, CPU throttling)
Security issues (vulnerabilities, RBAC)

Read this when you identify a specific issue type but need detailed remediation steps.

references/incident_response.md

Structured incident response framework including:

Incident response phases (Detection → Triage → Investigation → Resolution → Post-Incident)
Severity level definitions
Detailed playbooks for common incident scenarios
Communication guidelines
Post-incident review template
Best practices for prevention, preparedness, response, and recovery

Read this when responding to production incidents or planning incident response procedures.

references/performance_troubleshooting.md

Comprehensive performance diagnosis and optimization guide covering:

High Latency Issues - API response time, request latency troubleshooting
CPU Performance - Throttling detection, profiling, optimization
Memory Performance - OOM issues, leak detection, heap profiling
Network Performance - Latency, packet loss, DNS resolution
Storage I/O Performance - Disk performance testing, optimization
Application-Level Metrics - Prometheus integration, distributed tracing
Cluster-Wide Performance - Control plane, scheduler, resource utilization

Read this when:

Investigating slow application response times
Diagnosing CPU or memory performance issues
Troubleshooting network latency or connectivity
Optimizing storage I/O performance
Setting up performance monitoring

references/helm_troubleshooting.md

Complete guide to Helm troubleshooting including:

Release Issues - Stuck releases, missing resources, state problems
Installation Failures - Chart conflicts, validation errors, template rendering
Upgrade and Rollback - Failed upgrades, immutable field errors, rollback procedures
Values and Configuration - Values not applied, parsing errors, secret handling
Chart Dependencies - Dependency updates, version conflicts, subchart values
Hooks and Lifecycle - Hook failures, cleanup issues
Repository Issues - Chart access problems, version mismatches

Read this when:

Working with Helm-deployed applications
Troubleshooting chart installations or upgrades
Debugging Helm release states
Managing chart dependencies

FAQ

What does the k8s-troubleshooter skill do?

How do I install k8s-troubleshooter?

Run npx skills add https://github.com/ahmedasmar/devops-claude-skills --skill k8s-troubleshooter in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/k8s-troubleshooter/ (personal) or .claude/skills/k8s-troubleshooter/ (project).

Which AI agents can use k8s-troubleshooter?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is k8s-troubleshooter safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains k8s-troubleshooter?

It is published by ahmedasmar in ahmedasmar/devops-claude-skills. It has 59 recorded installs.