k8s-debug

To debug a crashing Kubernetes pod, you need to gather its status, events, and logs. This Skill runs diagnostic scripts via kubectl to collect failure details and resource usage, generating a consolidated report to identify the exact failure mode.

Checking Kubernetes cluster health involves assessing node readiness, component status, and resource pressure. This Skill executes targeted diagnostics to spot systemic issues across your deployment, helping you quickly understand if nodes are under resource pressure.

Troubleshooting Kubernetes network issues requires validating DNS resolution, endpoints, and service reachability across namespaces. This Skill applies network debugging scripts against your live cluster to verify connectivity and identify why services are unreachable.

Yes, you need both kubectl and Python 3 installed to execute these Kubernetes diagnostics. The Skill relies on Python scripts that invoke kubectl commands to query your live cluster for pod statuses, events, logs, and network endpoint data.

Yes, you can diagnose multiple Kubernetes namespaces simultaneously. The Skill is designed to validate service reachability, endpoints, and pod failures across multi-namespace deployments, providing a consolidated diagnostic report for your entire cluster.

The limitation of Kubernetes pod diagnostics depends on the live cluster data accessible via kubectl. This Skill gathers available status, events, logs, and resource usage, but cannot retrieve information missing from the cluster's own recorded event history.