Creating Kubernetes Deployments

Generate production-ready Kubernetes manifests with health checks, resource limits, and security best practices.

Quick Start

Basic Deployment + Service

# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-api
  labels:
    app: my-api
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-api
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 25%
      maxUnavailable: 25%
  template:
    metadata:
      labels:
        app: my-api
    spec:
      containers:
      - name: my-api
        image: my-registry/my-api:v1.0.0
        ports:
        - containerPort: 8080  # 8080: HTTP proxy port
        resources:
          requests:
            cpu: 100m
            memory: 256Mi
          limits:
            cpu: 500m
            memory: 512Mi
        livenessProbe:
          httpGet:
            path: /healthz
            port: 8080  # HTTP proxy port
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /readyz
            port: 8080  # HTTP proxy port
          initialDelaySeconds: 5
          periodSeconds: 5
---
apiVersion: v1
kind: Service
metadata:
  name: my-api
spec:
  type: ClusterIP
  selector:
    app: my-api
  ports:
  - port: 80
    targetPort: 8080  # HTTP proxy port

Deployment Strategies

Strategy	Use Case	Configuration
RollingUpdate	Zero-downtime updates	`maxSurge: 25%`, `maxUnavailable: 25%`
Recreate	Stateful apps, incompatible versions	`type: Recreate`
Blue-Green	Instant rollback	Two deployments, switch Service selector
Canary	Gradual rollout	Multiple deployments with weighted traffic

Blue-Green Deployment

# Blue deployment (current production)
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-api-blue
  labels:
    app: my-api
    version: blue
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-api
      version: blue
  template:
    metadata:
      labels:
        app: my-api
        version: blue
    spec:
      containers:
      - name: my-api
        image: my-registry/my-api:v1.0.0
---
# Service points to blue
apiVersion: v1
kind: Service
metadata:
  name: my-api
spec:
  selector:
    app: my-api
    version: blue  # Switch to 'green' for deployment
  ports:
  - port: 80
    targetPort: 8080  # 8080: HTTP proxy port

Service Types

Type	Use Case	Access
ClusterIP	Internal services	`my-api.namespace.svc.cluster.local`
NodePort	Development, debugging	`<NodeIP>:<NodePort>`
LoadBalancer	External traffic (cloud)	Cloud provider LB IP
ExternalName	External service proxy	DNS CNAME

Ingress with TLS

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: my-api-ingress
  annotations:
    cert-manager.io/cluster-issuer: letsencrypt-prod
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
spec:
  ingressClassName: nginx
  tls:
  - hosts:
    - api.example.com
    secretName: api-tls-secret
  rules:
  - host: api.example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-api
            port:
              number: 80

Resource Limits

Always set resource requests and limits:

resources:
  requests:    # Guaranteed resources
    cpu: 100m  # 0.1 CPU core
    memory: 256Mi
  limits:      # Maximum allowed
    cpu: 500m  # 0.5 CPU core
    memory: 512Mi

Workload Type	CPU Request	Memory Request	CPU Limit	Memory Limit
Web API	100m-500m	256Mi-512Mi	500m-1000m	512Mi-1Gi
Worker	250m-1000m	512Mi-1Gi	1000m-2000m	1Gi-2Gi
Database	500m-2000m	1Gi-4Gi	2000m-4000m	4Gi-8Gi

Health Checks

Liveness Probe (Is container running?)

livenessProbe:
  httpGet:
    path: /healthz
    port: 8080  # 8080: HTTP proxy port
  initialDelaySeconds: 30  # Wait for app startup
  periodSeconds: 10         # Check every 10s
  timeoutSeconds: 5         # Timeout per check
  failureThreshold: 3       # Restart after 3 failures

Readiness Probe (Ready for traffic?)

readinessProbe:
  httpGet:
    path: /readyz
    port: 8080  # 8080: HTTP proxy port
  initialDelaySeconds: 5    # Quick check after start
  periodSeconds: 5          # Check every 5s
  successThreshold: 1       # 1 success = ready
  failureThreshold: 3       # Remove from LB after 3 failures

Startup Probe (Slow-starting apps)

startupProbe:
  httpGet:
    path: /healthz
    port: 8080  # 8080: HTTP proxy port
  initialDelaySeconds: 0
  periodSeconds: 10
  failureThreshold: 30      # Allow 5 minutes to start (30 * 10s)

Horizontal Pod Autoscaler

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: my-api-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-api
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80
  behavior:
    scaleDown:
      stabilizationWindowSeconds: 300  # 300: Wait 5min before scale down

ConfigMaps and Secrets

ConfigMap (Non-sensitive config)

apiVersion: v1
kind: ConfigMap
metadata:
  name: my-api-config
data:
  LOG_LEVEL: "info"
  API_ENDPOINT: "https://api.example.com"
  config.yaml: |
    server:
      port: 8080  # 8080: HTTP proxy port
    features:
      enabled: true

Secret (Sensitive data - base64 encoded)

apiVersion: v1
kind: Secret
metadata:
  name: my-api-secrets
type: Opaque
data:
  API_KEY: YXBpLWtleS1oZXJl          # echo -n "api-key-here" | base64
  DATABASE_URL: cG9zdGdyZXM6Ly8uLi4=  # echo -n "postgres://..." | base64

Using in Deployment

spec:
  containers:
  - name: my-api
    envFrom:
    - configMapRef:
        name: my-api-config
    - secretRef:
        name: my-api-secrets
    volumeMounts:
    - name: config-volume
      mountPath: /app/config
  volumes:
  - name: config-volume
    configMap:
      name: my-api-config

Instructions

Gather Requirements
- Application name, container image, port
- Replica count and resource requirements
- Health check endpoints
- External access requirements (Ingress/LoadBalancer)
Generate Base Manifests
- Create Deployment with resource limits and probes
- Create Service (ClusterIP for internal, LoadBalancer for external)
- Add ConfigMap for configuration
- Add Secret for sensitive data
Add Production Features
- Configure Ingress with TLS if external access needed
- Add HPA for auto-scaling
- Add NetworkPolicy for security
- Add PodDisruptionBudget for availability

Validate and Apply

# Validate manifests
kubectl apply -f manifests/ --dry-run=server

# Apply to cluster
kubectl apply -f manifests/

# Watch rollout
kubectl rollout status deployment/my-api

Error Handling

See ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive troubleshooting.

Error	Quick Fix
ImagePullBackOff	Check image name, tag, registry credentials
CrashLoopBackOff	Check logs: `kubectl logs <pod>`
OOMKilled	Increase memory limits
Pending	Check resources: `kubectl describe pod <pod>`

Examples

See ${CLAUDE_SKILL_DIR}/references/examples.md for detailed walkthroughs.

Resources

Kubernetes documentation: https://kubernetes.io/docs/
kubectl reference: https://kubernetes.io/docs/reference/kubectl/
Templates in ${CLAUDE_SKILL_DIR}/assets/
Scripts in ${CLAUDE_SKILL_DIR}/scripts/

Overview

Deploy applications to Kubernetes with production-ready manifests.

Prerequisites

Access to the Kubernetes environment or API
Required CLI tools installed and authenticated
Familiarity with Kubernetes concepts and terminology

Output

Configuration files or code changes applied to the project
Validation report confirming correct implementation
Summary of changes made and their rationale

See Kubernetes implementation details for output format specifications.

creating-kubernetes-deployments