K8S Debug

What it does

The k8s-debug skill allows AI agents to troubleshoot and diagnose issues within Kubernetes clusters. It can analyze logs, describe pods and services, and execute commands within containers to identify the root cause of problems. This capability significantly reduces debugging time for common Kubernetes operational tasks.

When to use it

• Debugging application failures: Investigate why a specific pod is crashing or experiencing errors by analyzing its logs and resource usage.
• Troubleshooting network connectivity issues: Diagnose problems with service discovery or communication between pods within the cluster.
• Identifying resource constraints: Determine if pods are being throttled due to insufficient CPU or memory allocation.
• Investigating deployment rollbacks: Analyze why a Kubernetes deployment failed and requires a rollback.

Key capabilities

• Log analysis from pods and containers
• Kubernetes object description (pods, services, deployments)
• Container command execution within the cluster
• Resource usage monitoring for pods

Example prompts

• "Describe pod 'my-app-pod' in namespace 'production'."
• "Show me the logs from container 'webserver' in pod 'my-app-pod'."
• "Execute kubectl exec -it my-app-pod -- ps aux inside the 'my-app-pod' pod."

Tips & gotchas

Requires appropriate Kubernetes cluster access and credentials for the AI agent. The skill’s effectiveness depends on having sufficient logging enabled within your Kubernetes environment.