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Kubernetes in production: 7 essential best practices

· 2 min read
Karim Benali
Karim Benali
Kubernetes Architect @ InSkillOps

Running Kubernetes locally is one thing; operating it in production is another. Here are 7 practices we apply consistently on our clusters.

1. Set requests and limits​

Without requests/limits, a pod can starve its neighbours. Always set realistic values:

resources:
  requests:
    cpu: "100m"
    memory: "128Mi"
  limits:
    cpu: "500m"
    memory: "256Mi"

2. Configure probes​

Liveness and readiness probes prevent traffic from reaching a pod that isn't ready (or is stuck):

livenessProbe:
  httpGet: { path: /healthz, port: 3000 }
  initialDelaySeconds: 10
readinessProbe:
  httpGet: { path: /ready, port: 3000 }

3. Enable autoscaling​

The Horizontal Pod Autoscaler adjusts the number of replicas based on load:

kubectl autoscale deployment my-app --cpu-percent=70 --min=2 --max=10

4. Lock down access with RBAC​

Apply the principle of least privilege: each ServiceAccount gets only the permissions it needs.

5. Isolate with namespaces​

Separate environments (dev, staging, prod) and teams by namespace, with ResourceQuotas to avoid overruns.

6. Never store secrets in plain text​

Use Kubernetes Secrets, encrypted at rest, or an external manager (Vault, AWS Secrets Manager). Never a password in an image or a versioned manifest.

7. Monitor and alert​

Prometheus + Grafana for metrics, a centralized logging stack, and alerts on key signals (error rate, latency, saturation).

These practices form the basis of a robust cluster. We detail them with hands-on labs in the Kubernetes path.