Can this skill help with networking issues?

Yes, it includes diagnostics for service selectors, DNS resolution failures, and Ingress controller configuration issues.

Does it support resource management and scaling?

It provides commands to check resource pressure, view allocated resources per node, and identify pods without defined limits or those exceeding quotas.

Which pod states can this skill help diagnose?

The skill provides specialized workflows for CrashLoopBackOff, ImagePullBackOff, Pending, CreateContainerConfigError, and OOMKilled states.

How does it handle log analysis?

The skill guides users through advanced logging techniques including following previous container logs, time-based filtering, and multi-container output.

Is it compatible with modern Kubernetes features?

Yes, it includes procedures for using ephemeral debug containers (introduced in K8s 1.25) to troubleshoot running pods without sidecars.

Kubernetes Debugging Toolkit

Name: Kubernetes Debugging Toolkit
Author: martin-janci

bymartin-janci

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Deployment & DevOps

Streamlines Kubernetes cluster troubleshooting by providing systematic workflows for diagnosing pod failures, networking issues, and resource bottlenecks.

About

The k8s-debug skill equips Claude with a robust framework for investigating and resolving complex Kubernetes issues. It covers critical failure patterns such as CrashLoopBackOff, ImagePullBackOff, and OOMKilled events, while providing diagnostic paths for networking, volume mounts, and node health. Whether you are dealing with scheduling failures or DNS resolution errors, this skill offers the precise kubectl commands and systematic logic required to restore cluster stability and application performance.

Key Features

Step-by-step diagnostic workflows for pod lifecycle and container start-up errors
Network and DNS troubleshooting for services, endpoints, and ingress controllers
Resource pressure analysis to identify memory leaks and CPU hogs
Node health checks including condition monitoring and maintenance workflows
Advanced log analysis and ephemeral container debugging techniques
1 GitHub stars

Use Cases

Debugging connectivity gaps between microservices and external resources
Optimizing resource quotas and limits based on real-time pod metrics
Identifying the root cause of service restarts and container termination codes

About

Key Features

Step-by-step diagnostic workflows for pod lifecycle and container start-up errors
Network and DNS troubleshooting for services, endpoints, and ingress controllers
Resource pressure analysis to identify memory leaks and CPU hogs
Node health checks including condition monitoring and maintenance workflows
Advanced log analysis and ephemeral container debugging techniques
1 GitHub stars

Use Cases

Debugging connectivity gaps between microservices and external resources
Optimizing resource quotas and limits based on real-time pod metrics
Identifying the root cause of service restarts and container termination codes