What tools are required to run the diagnostic scripts?

The skill utilizes Python 3 and the standard kubectl CLI to execute health checks and gather cluster state information.

How does this skill help with CrashLoopBackOff errors?

It provides a systematic diagnostic script (diagnose_pod.py) that analyzes container states, exit codes, and recent events to identify the specific root cause and suggest remediation.

Does it support troubleshooting Helm-managed applications?

Yes, it contains specific guidance for resolving stuck Helm releases, chart conflicts, state problems, and template rendering errors.

Can this skill be used for production incident response?

Yes, it includes a structured framework for managing SEV-1 to SEV-4 incidents, including triage protocols, resolution playbooks, and post-mortem templates.

Kubernetes Troubleshooter & Incident Response

Name: Kubernetes Troubleshooter & Incident Response
Author: ahmedasmar

byahmedasmar

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Deployment & DevOps

Diagnoses and resolves Kubernetes cluster issues, pod failures, and production incidents using systematic workflows and automated scripts.

About

This skill empowers Claude to act as an expert SRE or DevOps engineer by providing a structured framework for Kubernetes troubleshooting. It includes specialized Python diagnostic scripts to assess cluster and namespace health, comprehensive playbooks for common errors like CrashLoopBackOff or OOMKilled, and detailed incident response protocols. Whether you are debugging networking latency, storage failures, or Helm deployment issues, this skill provides the evidence-based diagnostic patterns and remediation steps needed to restore system stability and optimize performance.

Key Features

Structured production incident response playbooks and severity assessment
Performance troubleshooting for CPU, memory, and network latency
Comprehensive Helm release and deployment troubleshooting guides
Deep-dive pod diagnostics for CrashLoopBackOff and ImagePullBackOff errors
Automated cluster and namespace health checks via Python scripts
6 GitHub stars

Use Cases

Performing automated health assessments of a new or existing Kubernetes namespace
Optimizing cluster performance by identifying resource bottlenecks and throttling issues
Rapidly diagnosing the root cause of failing pods or services during a production outage

About

Key Features

Structured production incident response playbooks and severity assessment
Performance troubleshooting for CPU, memory, and network latency
Comprehensive Helm release and deployment troubleshooting guides
Deep-dive pod diagnostics for CrashLoopBackOff and ImagePullBackOff errors
Automated cluster and namespace health checks via Python scripts
6 GitHub stars

Use Cases

Performing automated health assessments of a new or existing Kubernetes namespace
Optimizing cluster performance by identifying resource bottlenecks and throttling issues
Rapidly diagnosing the root cause of failing pods or services during a production outage