Kubernetes Debugger

Systematic debugging workflows for Kubernetes issues using MCP kubernetes tools.

Prerequisites

Install Kubernetes MCP Server

claude mcp add kubernetes --scope user -- npx mcp-server-kubernetes

Requirements:

• Access to a Kubernetes cluster configured for kubectl (minikube, Rancher Desktop, GKE, EKS, AKS, etc.)
• kubeconfig at ~/.kube/config (default) or KUBECONFIG env var set
• Helm v3 in PATH (optional, for Helm operations)

Alternative installation methods:

# Global install
npm install -g mcp-server-kubernetes

# Or run directly with npx (no install)
npx mcp-server-kubernetes

Verify installation:

claude mcp list  # Should show 'kubernetes' server

Quick Reference: MCP Tools

Tool	Use For
kubectl_get	List resources, check status, find resource names
kubectl_describe	Detailed info, events, conditions
kubectl_logs	Container stdout/stderr, application errors
exec_in_pod	Run commands inside containers
kubectl_rollout	Deployment rollout status/history
node_management	Cordon/drain/uncordon nodes

Debugging Decision Tree

Issue reported
    │
    ├─ Pod not running? ──────────► See: Pod Debugging Workflow
    │
    ├─ Service unreachable? ──────► See: Service/Network Debugging
    │
    ├─ Deployment stuck? ─────────► See: Deployment Debugging
    │
    ├─ Node issues? ──────────────► See: Node Debugging
    │
    └─ Performance/Resources? ────► See: Resource Debugging

Pod Debugging Workflow

Step 1: Get Pod Status

kubectl_get(resourceType="pods", namespace="<ns>")

Common statuses and their meaning:

• Pending: Scheduling issues (resources, node selector, affinity)
• CrashLoopBackOff: Container crashing repeatedly
• ImagePullBackOff/ErrImagePull: Cannot pull container image
• Running but not ready: Readiness probe failing
• Terminating: Stuck deletion (finalizers, PDB)

Step 2: Check Events and Conditions

kubectl_describe(resourceType="pod", name="<pod>", namespace="<ns>")

Look for in output:

• Events section: Scheduling failures, image pull errors, probe failures
• Conditions: PodScheduled, Initialized, ContainersReady, Ready
• Container State: Waiting (reason), Running, Terminated (exit code)

Step 3: Get Container Logs

kubectl_logs(resourceType="pod", name="<pod>", namespace="<ns>", container="<container>")

Options:

• previous=true: Logs from crashed container
• tail=100: Last N lines
• since="1h": Logs from last hour

Step 4: Exec Into Container (if running)

exec_in_pod(name="<pod>", namespace="<ns>", command=["sh", "-c", "<cmd>"])

Useful commands:

• ["cat", "/etc/resolv.conf"] - Check DNS config
• ["env"] - Verify environment variables
• ["ls", "-la", "/app"] - Check mounted files
• ["nc", "-zv", "<host>", "<port>"] - Test connectivity

Common Pod Issues

CrashLoopBackOff

1. Get logs: kubectl_logs(previous=true) for crashed container
2. Check exit code in kubectl_describe output
3. Common causes:
   • Exit code 1: Application error
   • Exit code 137: OOMKilled (check memory limits)
   • Exit code 143: SIGTERM (graceful shutdown issue)

ImagePullBackOff

1. Check image name/tag in describe output
2. Verify image exists in registry
3. Check imagePullSecrets if private registry
4. Look for "Failed to pull image" in events

Pending Pod

1. Check events for scheduling failure reason
2. Common causes:
   • Insufficient cpu/memory: Node capacity exhausted
   • node(s) didn't match node selector: Wrong labels
   • PersistentVolumeClaim not bound: Storage issue
   • 0/N nodes available: Taints/tolerations mismatch

Service/Network Debugging

Step 1: Verify Service Exists

kubectl_get(resourceType="services", namespace="<ns>")
kubectl_describe(resourceType="service", name="<svc>", namespace="<ns>")

Step 2: Check Endpoints

kubectl_get(resourceType="endpoints", name="<svc>", namespace="<ns>")

No endpoints? Check:

• Pod labels match service selector
• Pods are Running and Ready
• Target port matches container port

Step 3: Test DNS Resolution

exec_in_pod(name="<debug-pod>", command=["nslookup", "<service>.<namespace>.svc.cluster.local"])

Step 4: Test Connectivity

exec_in_pod(name="<debug-pod>", command=["nc", "-zv", "<service>", "<port>"])

Deployment Debugging

Check Rollout Status

kubectl_rollout(subCommand="status", resourceType="deployment", name="<deploy>", namespace="<ns>")

View Rollout History

kubectl_rollout(subCommand="history", resourceType="deployment", name="<deploy>", namespace="<ns>")

Rollback if Needed

kubectl_rollout(subCommand="undo", resourceType="deployment", name="<deploy>", namespace="<ns>")

Common Issues

• Progressing stuck: New pods failing (check ReplicaSet pods)
• Available < desired: Pods not passing readiness probes
• Surge/unavailable conflicts: Check deployment strategy

Node Debugging

Check Node Status

kubectl_get(resourceType="nodes")
kubectl_describe(resourceType="node", name="<node>")

Node Conditions to Check

Condition	Problem If
Ready	False or Unknown
MemoryPressure	True
DiskPressure	True
PIDPressure	True
NetworkUnavailable	True

Drain Node for Maintenance

node_management(operation="cordon", nodeName="<node>")  # Prevent new pods
node_management(operation="drain", nodeName="<node>", confirmDrain=true)  # Evict pods
# After maintenance:
node_management(operation="uncordon", nodeName="<node>")

Resource Debugging

Check Resource Usage

kubectl_generic(command="top", resourceType="pods", namespace="<ns>")
kubectl_generic(command="top", resourceType="nodes")

OOMKilled Detection

1. kubectl_describe pod - look for "OOMKilled" in container state
2. Check memory limits vs actual usage
3. Solutions:
   • Increase memory limits
   • Fix memory leak in application
   • Add memory requests for better scheduling

CPU Throttling

1. Check if CPU limits are too restrictive
2. Consider removing CPU limits (keep requests)
3. Use kubectl top pods to see actual usage

Reference Files

• references/pod-states.md: Complete pod state reference
• references/common-errors.md: Error messages and solutions
• references/network-debug.md: Network troubleshooting details