Originally published at claudeguide.io/claude-code-kubernetes-devops

Claude Code for Kubernetes and DevOps: YAML Generation and Automation

Claude Code generates production-quality Kubernetes YAML manifests from plain English descriptions — Deployments, Services, ConfigMaps, Secrets, HPA, PodDisruptionBudgets, and Helm charts — and can troubleshoot cluster issues by reading your kubectl output directly. A full microservice deployment that takes 2–3 hours to write manually takes under 15 minutes with Claude Code.

This guide covers the full DevOps workflow: YAML generation, Helm chart authoring, CI/CD pipeline integration, and live cluster troubleshooting.

Setup: Add Kubernetes Context to CLAUDE.md

Before generating any manifests, add your cluster conventions to CLAUDE.md:

## Kubernetes Configuration
- Cluster: GKE (Google Kubernetes Engine) on us-central1
- Namespace convention: {app}-{env} (e.g., payments-prod, payments-staging)
- Resource limits: always set both requests AND limits
- Image registry: gcr.io/my-project/
- Node selector: environment=production for prod workloads
- Labels: app, env, version (all required)
- Liveness/readiness probes: required on all Deployments
- Anti-affinity: prefer spread across availability zones

Claude applies these rules to every generated manifest without being re-told each session.

Generating a Complete Deployment

claude "Generate a Kubernetes Deployment for a Node.js API service:
- Image: gcr.io/my-project/api:v1.2.0
- 3 replicas
- Port 3000
- Env vars: NODE_ENV=production, PORT=3000, DB_URL from a Secret named api-secrets
- CPU request: 250m, limit: 500m
- Memory request: 256Mi, limit: 512Mi
- Liveness probe: GET /health every 30s
- Readiness probe: GET /ready every 10s
Apply CLAUDE.md conventions."

Output (excerpt):

apiVersion: apps/v1
kind: Deployment
metadata:
  name: api
  namespace: api-prod
  labels:
    app: api
    env: production
    version: v1.2.0
spec:
  replicas: 3
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
        env: production
        version: v1.2.0
    spec:
      affinity:
        podAntiAffinity:
          preferredDuringSchedulingIgnoredDuringExecution:
          - weight: 100
            podAffinityTerm:
              topologyKey: topology.kubernetes.io/zone
              labelSelector:
                matchLabels:
                  app: api
      containers:
      - name: api
        image: gcr.io/my-project/api:v1.2.0
        ports:
        - containerPort: 3000
        env:
        - name: NODE_ENV
          value: production
        - name: DB_URL
          valueFrom:
            secretKeyRef:
              name: api-secrets
              key: db-url
        resources:
          requests:
            cpu: 250m
            memory: 256Mi
          limits:
            cpu: 500m
            memory: 512Mi
        livenessProbe:
          httpGet:
            path: /health
            port: 3000
          periodSeconds: 30
        readinessProbe:
          httpGet:
            path: /ready
            port: 3000
          periodSeconds: 10

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Horizontal Pod Autoscaler


bash
claude "Generate an HPA for the api deployment.
- Min: 3 replicas, Max: 20 replicas
- Scale up when CPU 

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