Running Kubernetes in production is a milestone that demands more than just cluster setup and deployment. To ensure high availability, optimal performance, and robust security, teams must follow best practices that span scaling, networking, and security. This guide offers a detailed walkthrough of Kubernetes production best practices, helping you build resilient and secure cloud-native platforms.

Scaling Kubernetes Workloads

Proper scaling is key to handling production workloads efficiently without overprovisioning or incurring unnecessary costs.

Horizontal Pod Autoscaling (HPA)
  • Automatically scales the number of pods based on CPU/memory usage or custom metrics.
  • Use the Kubernetes Metrics Server or Prometheus Adapter.
  • Define thresholds in the HorizontalPodAutoscaler object.
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: web-app
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
Cluster Autoscaler
  • Scales nodes up/down based on pod resource requests.
  • Works with cloud providers (AWS, GCP, Azure).
  • Ensures new nodes are added when pods can’t be scheduled.
Vertical Pod Autoscaler (VPA)
  • Adjusts CPU/memory resource requests for pods.
  • Best for workloads with stable patterns.
  • Use with caution in production, especially with HPA.

Networking Best Practices

Kubernetes networking can get complex in production due to multi-tenant workloads, service discovery, and ingress traffic. Follow these guidelines:

Use Ingress Controllers Effectively
  • Choose a robust ingress controller like NGINX, HAProxy, or Traefik.
  • Apply TLS termination and HTTP routing rules.
  • Use annotations for rewrites, timeouts, and path-based routing.
DNS and Service Discovery
  • Leverage CoreDNS for service discovery.
  • Use stable DNS naming for internal services (e.g., my-service.my-namespace.svc.cluster.local).
Network Policies
  • Implement Kubernetes NetworkPolicies to control traffic between pods.
  • Enforce zero-trust networking: deny all traffic by default and allow only specific communication.
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
spec:
  podSelector:
    matchLabels:
      role: backend
  policyTypes:
  - Ingress
  ingress:
  - from:
    - podSelector:
        matchLabels:
          role: frontend
Load Balancing and Traffic Control
  • Use external load balancers for public access.
  • Implement service meshes (e.g., Istio, Linkerd) for traffic shaping, retries, and observability.
  • Use readiness and liveness probes to remove unhealthy pods from load balancers.

Security Best Practices

Security is not optional in production. Kubernetes offers many tools, but proactive configuration is necessary.

Role-Based Access Control (RBAC)
  • Use least privilege principles.
  • Define fine-grained permissions for users, groups, and service accounts.
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  namespace: dev
  name: pod-reader
rules:
- apiGroups: [""]
  resources: ["pods"]
  verbs: ["get", "watch", "list"]
Use Namespaces for Isolation
  • Group workloads by environment (e.g., dev, staging, prod).
  • Apply quotas and limit ranges to prevent resource hogging.
  • Combine with NetworkPolicies for isolation.
Pod Security and Admission Controls
  • Enforce Pod Security Standards (restricted, baseline, privileged).
  • Use tools like OPA Gatekeeper or Kyverno to enforce policies.
  • Disable privileged containers unless absolutely necessary.
Secrets and Config Management
  • Store secrets using Kubernetes Secret resources or external tools like HashiCorp Vault.
  • Enable encryption at rest for secrets in etcd.
  • Avoid embedding secrets in environment variables or config files.

Logging, Monitoring, and Observability

Observability is a must in production environments to ensure uptime and debug issues efficiently.

Centralized Logging
  • Use tools like Fluentd, Logstash, or Loki to collect logs.
  • Route logs to centralized systems (e.g., Elasticsearch, Splunk).
Monitoring with Prometheus and Grafana
  • Monitor cluster and pod-level metrics with Prometheus.
  • Create custom dashboards in Grafana for visibility.
Tracing and Alerting
  • Implement distributed tracing with Jaeger or OpenTelemetry.
  • Configure alerting rules for SLA/SLO breaches.

Backup and Disaster Recovery

Don’t wait for failure to plan recovery.

  • Schedule regular etcd backups.
  • Use Velero for backing up Kubernetes resources and persistent volumes.
  • Automate restoration processes and document recovery runbooks.

Cost Optimization Tips

Efficient resource usage can save thousands in production.

  • Right-size requests and limits for each workload.
  • Use spot/preemptible nodes for non-critical jobs.
  • Use autoscaling to adjust to demand dynamically.

Conclusion

Running Kubernetes in production isn’t just about cluster uptime — it’s about resilience, security, and efficiency. By following these best practices across scaling, networking, and security, your platform becomes more maintainable, observable, and secure. Implement these strategies today and elevate your Kubernetes operations to a production-ready standard.