How to Use Kubernetes Specialist in Claude Code for Beginners

Feb 14, 2026

Purpose

This post demonstrates how to use the Kubernetes Specialist skill in Claude Code to manage and develop Kubernetes infrastructure. The Kubernetes Specialist skill helps with deployment configurations, troubleshooting, and best practices for container orchestration.

Environment

Claude Code with claude-skills plugin
Kubernetes cluster (local or remote)
kubectl CLI tool
Basic understanding of containers

What is Kubernetes Specialist?

The Kubernetes Specialist is a specialized skill in the claude-skills ecosystem that focuses on Kubernetes infrastructure development. When I need to create deployments, services, configmaps, or troubleshoot cluster issues, I can invoke this skill to get targeted assistance.

There are 4 main benefits:

Deployment automation: Generate YAML manifests for deployments, services, and ingress
Configuration management: Create and manage ConfigMaps and Secrets
Troubleshooting: Diagnose pod failures, service issues, and resource constraints
Best practices: Ensure configurations follow Kubernetes standards

Installation and Setup

First, I need to install the claude-skills plugin. I’ll use npm:

npm install -g @jeffallan/claude-skills

Then I verify the installation:

claude-skills --version

The output shows:

claude-skills v1.0.0

Now I can activate the Kubernetes Specialist skill by calling it through Claude Code’s Skill tool.

Core Usage Patterns

The Kubernetes Specialist skill activates when I use specific trigger phrases or context. Here are the common patterns:

Direct invocation:

"Use kubernetes-specialist"

Context-based triggers:

"Create a Kubernetes deployment for my Node.js app"
"Help me debug why my pods are crashing"
"Write a Kubernetes manifest for a Redis service"

Typical use cases:

Generating deployment manifests
Creating service definitions
Setting up ConfigMaps and Secrets
Debugging pod startup failures
Configuring ingress rules
Managing resource limits

Practical Examples

Example 1: Creating a Deployment

When I needed to deploy a Node.js application, I used the Kubernetes Specialist skill:

"Use kubernetes-specialist to create a deployment for a Node.js app"

The skill generated this manifest:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nodejs-app
  labels:
    app: nodejs-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: nodejs-app
  template:
    metadata:
      labels:
        app: nodejs-app
    spec:
      containers:
      - name: nodejs-app
        image: nodejs-app:latest
        ports:
        - containerPort: 3000
        resources:
          requests:
            memory: "128Mi"
            cpu: "100m"
          limits:
            memory: "256Mi"
            cpu: "200m"
        livenessProbe:
          httpGet:
            path: /health
            port: 3000
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 3000
          initialDelaySeconds: 5
          periodSeconds: 5

The skill included resource limits and health checks, which I hadn’t thought about initially.

Example 2: Creating a Service

Next, I needed to expose the application:

"Create a Kubernetes service for the nodejs-app deployment"

The skill produced:

apiVersion: v1
kind: Service
metadata:
  name: nodejs-app-service
spec:
  type: LoadBalancer
  selector:
    app: nodejs-app
  ports:
  - protocol: TCP
    port: 80
    targetPort: 3000

I noticed the skill used LoadBalancer type, which is appropriate for external access.

Example 3: Debugging Pod Failures

When my pods kept crashing, I used:

"Help me debug why my pods are in CrashLoopBackOff"

The skill guided me through:

Checking pod logs: kubectl logs <pod-name>
Describing the pod: kubectl describe pod <pod-name>
Checking resource usage: kubectl top pods

The issue was that I hadn’t set resource limits, causing the pod to be killed by the OOMKiller.

Best Practices

DO

Use specific triggers:

"Create a deployment with 3 replicas for a Python API"
"Generate a ConfigMap for application configuration"

Provide context:

"I'm using Minikube locally and need to deploy a PostgreSQL database"

Follow naming conventions:

Use lowercase names for deployments
Include app labels for selector matching
Name services with a -service suffix

Always include resource limits:

resources:
  requests:
    memory: "64Mi"
    cpu: "50m"
  limits:
    memory: "128Mi"
    cpu: "100m"

DON’T

Don’t forget health checks: Without liveness and readiness probes, Kubernetes can’t properly manage your pods.

Don’t use default namespaces: Always specify a namespace in production environments:

metadata:
  name: my-app
  namespace: production

Don’t hardcode sensitive data: Use Secrets instead of putting passwords in ConfigMaps:

apiVersion: v1
kind: Secret
metadata:
  name: db-credentials
type: Opaque
data:
  password: cGFzc3dvcmQxMjM=

Don’t skip labels: Labels are essential for service discovery and pod selection:

metadata:
  labels:
    app: my-app
    version: v1.0.0
    environment: production

Complementary skills:

docker-patterns: For container image creation and optimization
backend-patterns: For application architecture that works well with Kubernetes
security-review: For validating Kubernetes security configurations

Official resources:

Community resources:

Summary

In this post, I showed how to use the Kubernetes Specialist skill in Claude Code for infrastructure development. I covered installation and setup, core usage patterns, and practical examples for creating deployments, services, and debugging issues. The key point is that the Kubernetes Specialist skill helps you follow best practices and avoid common pitfalls when working with Kubernetes manifests.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!