Kubernetes Storage Best Practices for Production

💡 Quick Answer: Production storage best practices for Kubernetes. Covers StorageClass selection, backup strategies, volume expansion, data migration, and storage performance tuning.

The Problem

Engineers frequently search for this topic but find scattered, incomplete guides. This recipe provides a comprehensive, production-ready reference.

The Solution

StorageClass Recommendations

# Production: encrypted, high IOPS
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: fast-encrypted
provisioner: ebs.csi.aws.com
parameters:
  type: gp3
  iops: "5000"
  throughput: "250"
  encrypted: "true"
  kmsKeyId: "arn:aws:kms:..."
reclaimPolicy: Retain        # Don't auto-delete data!
allowVolumeExpansion: true
volumeBindingMode: WaitForFirstConsumer
---
# Development: cheap, no encryption
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: dev-storage
provisioner: ebs.csi.aws.com
parameters:
  type: gp3
reclaimPolicy: Delete
allowVolumeExpansion: true

Checklist

Volume Expansion

# Expand a PVC (no downtime for most CSI drivers)
kubectl patch pvc postgres-data -p '{"spec":{"resources":{"requests":{"storage":"100Gi"}}}}'

# Some drivers need pod restart for filesystem resize
kubectl delete pod <pod-using-pvc>
# Pod recreates and filesystem expands on mount

graph TD
    A[Storage Strategy] --> B[Dev: gp3, Delete, cheap]
    A --> C[Staging: gp3, Retain, encrypted]
    A --> D[Prod: gp3 high-IOPS, Retain, encrypted, snapshots]
    D --> E[Daily snapshots]
    D --> F[Cross-region replication]

Frequently Asked Questions

What happens if my PV’s AZ doesn’t match my pod’s node?

The pod stays Pending because the volume can’t be attached. Use WaitForFirstConsumer binding mode to create the PV in the same AZ as the pod’s node.

Best Practices

• Start with the simplest approach that solves your problem
• Test thoroughly in staging before production
• Monitor and iterate based on real metrics
• Document decisions for your team

Key Takeaways

• This is essential Kubernetes operational knowledge
• Production-readiness requires proper configuration and monitoring
• Use kubectl describe and logs for troubleshooting
• Automate where possible to reduce human error