Kubernetes in Production: Essential Best Practices

Running Kubernetes in production requires careful planning and adherence to best practices. This guide covers the essential patterns for reliable deployments.

Resource Management

Set Resource Requests and Limits

Always define resource constraints:

resources:
  requests:
    memory: "256Mi"
    cpu: "250m"
  limits:
    memory: "512Mi"
    cpu: "500m"

Use Horizontal Pod Autoscaling

Scale based on metrics:

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
spec:
  minReplicas: 2
  maxReplicas: 10
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70

High Availability

Pod Disruption Budgets

Protect against voluntary disruptions:

apiVersion: policy/v1
kind: PodDisruptionBudget
spec:
  minAvailable: 2
  selector:
    matchLabels:
      app: my-app

Multi-Zone Deployment

Spread pods across availability zones using topology spread constraints.

Security

Network Policies

Restrict pod-to-pod communication:

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
spec:
  podSelector:
    matchLabels:
      app: backend
  ingress:
    - from:
        - podSelector:
            matchLabels:
              app: frontend

Pod Security Standards

Enforce security contexts on all pods.

Observability

Implement the three pillars:

• Logging with a centralized solution
• Metrics with Prometheus/Grafana
• Tracing with Jaeger or similar

Conclusion

Production Kubernetes requires attention to detail across resource management, availability, security, and observability. Follow these practices to build reliable systems.