Production-Ready Kubernetes Deployments: Lessons from the Trenches

After managing Kubernetes clusters in production for several years, I've learned that successful deployments require more than just basic configurations. Here are the critical practices that separate hobby projects from production-ready systems.

Essential Production Configurations

1. Resource Management

Always define resource requests and limits:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: video-streaming-service
spec:
  replicas: 3
  selector:
    matchLabels:
      app: video-streaming
  template:
    metadata:
      labels:
        app: video-streaming
    spec:
      containers:
      - name: streaming-service
        image: streaming-service:v1.2.0
        resources:
          requests:
            memory: "512Mi"
            cpu: "250m"
          limits:
            memory: "1Gi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5

2. Security Best Practices

Implement Pod Security Standards:

apiVersion: v1
kind: Pod
spec:
  securityContext:
    runAsNonRoot: true
    runAsUser: 1000
    fsGroup: 2000
  containers:
  - name: app
    securityContext:
      allowPrivilegeEscalation: false
      readOnlyRootFilesystem: true
      capabilities:
        drop:
        - ALL

3. Monitoring and Observability

Deploy comprehensive monitoring stack:

• Prometheus: For metrics collection
• Grafana: For visualization
• Jaeger: For distributed tracing
• Fluentd: For log aggregation

These practices have helped me maintain stable, secure, and observable Kubernetes environments in production.