Kubernetes Storage Review

When to Use

• Choosing the right StorageClass for a data workload
• Diagnosing PVC stuck in Pending state
• Planning storage for stateful workloads (Kafka, databases, Spark history)
• Setting up volume snapshots for backup
• Auditing orphaned PVs costing money

---

PVC Lifecycle and Status

# List all PVCs with status
kubectl get pvc -A

# PVC stuck in Pending — why?
kubectl describe pvc <pvc-name> -n <namespace>
# Look for: Events section — "no nodes available matching...", "StorageClass not found"

# List PersistentVolumes
kubectl get pv

# Find unbound PVs (orphaned, potentially costing money)
kubectl get pv | grep -v Bound

# Find PVCs not mounted by any pod
kubectl get pvc -A -o json | jq -r '
  .items[] |
  select(.status.phase == "Bound") |
  "\(.metadata.namespace)/\(.metadata.name)"
'

PVC Status Reference

Status	Meaning
Pending	Waiting for volume to be created/bound
Bound	Successfully bound to a PV
Lost	Underlying PV deleted or unavailable
Released	PV released but not yet reclaimed

---

StorageClass Design

AWS EBS StorageClasses

# gp3 — general purpose SSD (default, best cost/performance)
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: gp3
  annotations:
    storageclass.kubernetes.io/is-default-class: "true"
provisioner: ebs.csi.aws.com
parameters:
  type: gp3
  iops: "3000"
  throughput: "125"
  encrypted: "true"
reclaimPolicy: Delete
allowVolumeExpansion: true
volumeBindingMode: WaitForFirstConsumer  # bind to AZ where pod is scheduled

---
# io2 — high IOPS for databases
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: io2-high-iops
provisioner: ebs.csi.aws.com
parameters:
  type: io2
  iops: "10000"
  encrypted: "true"
reclaimPolicy: Retain            # Retain for databases — manual cleanup
allowVolumeExpansion: true
volumeBindingMode: WaitForFirstConsumer

GKE StorageClasses

# Standard SSD
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: ssd
provisioner: pd.csi.storage.gke.io
parameters:
  type: pd-ssd
reclaimPolicy: Delete
allowVolumeExpansion: true
volumeBindingMode: WaitForFirstConsumer

# Extreme for high-throughput databases
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: extreme-ssd
provisioner: pd.csi.storage.gke.io
parameters:
  type: hyperdisk-extreme
  provisioned-iops-on-create: "100000"
allowVolumeExpansion: true

---

StatefulSet Volume Management

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: kafka
spec:
  serviceName: kafka
  replicas: 3
  selector:
    matchLabels:
      app: kafka
  template:
    spec:
      containers:
      - name: kafka
        image: confluentinc/cp-kafka:7.5.0
        volumeMounts:
        - name: data
          mountPath: /var/lib/kafka/data
  volumeClaimTemplates:             # one PVC created per replica
  - metadata:
      name: data
    spec:
      accessModes: ["ReadWriteOnce"]
      storageClassName: gp3
      resources:
        requests:
          storage: 500Gi

# List PVCs for a StatefulSet
kubectl get pvc -l app=kafka -n kafka

# StatefulSet PVC naming: <pvc-name>-<statefulset-name>-<ordinal>
# e.g., data-kafka-0, data-kafka-1, data-kafka-2

---

Access Modes

Mode	Description	Use Case
ReadWriteOnce (RWO)	Single node read-write	Databases, Kafka, most stateful
ReadOnlyMany (ROX)	Multiple nodes read-only	Shared configuration, static assets
ReadWriteMany (RWX)	Multiple nodes read-write	NFS, CephFS, shared ML model storage
ReadWriteOncePod	Single pod read-write	Strict single-writer enforcement

# RWX for shared ML model storage
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: model-store
spec:
  accessModes: ["ReadWriteMany"]
  storageClassName: efs-sc          # AWS EFS or CephFS for RWX
  resources:
    requests:
      storage: 100Gi

---

Volume Expansion

# Expand a PVC (StorageClass must have allowVolumeExpansion: true)
kubectl patch pvc <pvc-name> -n <namespace> \
  -p '{"spec": {"resources": {"requests": {"storage": "200Gi"}}}}'

# Check expansion progress
kubectl describe pvc <pvc-name> -n <namespace> | grep -A 5 "Conditions"

# For EBS: expansion is online (no pod restart needed in Kubernetes 1.16+)
# For filesystem resize inside pod:
kubectl exec -it <pod> -- resize2fs /dev/xvda  # ext4
kubectl exec -it <pod> -- xfs_growfs /data     # xfs

---

Volume Snapshots and Backup

# Create a volume snapshot
apiVersion: snapshot.storage.k8s.io/v1
kind: VolumeSnapshot
metadata:
  name: kafka-data-snapshot-20240115
spec:
  volumeSnapshotClassName: csi-aws-vsc
  source:
    persistentVolumeClaimName: data-kafka-0

---
# Restore from snapshot
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: kafka-data-restored
spec:
  storageClassName: gp3
  dataSource:
    name: kafka-data-snapshot-20240115
    kind: VolumeSnapshot
    apiGroup: snapshot.storage.k8s.io
  accessModes: ["ReadWriteOnce"]
  resources:
    requests:
      storage: 500Gi

---

Longhorn — Cloud-Native Distributed Storage

For on-premise or bare-metal clusters without cloud storage:

# Install Longhorn
helm repo add longhorn https://charts.longhorn.io
helm install longhorn longhorn/longhorn -n longhorn-system --create-namespace

# Create StorageClass
# Longhorn provides this automatically: storageclass.kubernetes.io/is-default-class: "true"

# Access Longhorn UI
kubectl -n longhorn-system port-forward svc/longhorn-frontend 8080:80

---

Audit Orphaned Storage

# Find Released PVs (PVC deleted but PV still exists)
kubectl get pv | grep Released

# Delete orphaned PVs (check reclaimPolicy first!)
# If Retain: manually delete and clean up cloud volume
kubectl delete pv <pv-name>

# Find large PVCs consuming expensive SSD
kubectl get pvc -A -o json | jq -r '
  .items[] |
  "\(.spec.storageClassName) \(.spec.resources.requests.storage) \(.metadata.namespace)/\(.metadata.name)"
' | sort -k2 -rh | head -20

---

Storage Performance Guidelines

Workload	Recommended StorageClass	Min IOPS	Notes
Kafka	gp3 / pd-ssd	3000	Sequential write; throughput matters more
PostgreSQL	io2 / pd-ssd	5000+	Random IOPS critical
Spark shuffle	Local SSD / NVMe	10000+	Use node local storage when possible
Elasticsearch	gp3 / pd-ssd	3000	Mixed random/sequential
Logs / archival	gp2 / pd-standard	100	Cost-optimize with cheap storage
ML models (shared)	EFS / CephFS (RWX)	N/A	Throughput for batch inference

---

Anti-Patterns

1. reclaimPolicy: Delete for databases — if a PVC is accidentally deleted, data is gone; use Retain for production databases.
2. volumeBindingMode: Immediate — PVC binds before pod schedules, can bind to wrong AZ causing pod to stay Pending; use WaitForFirstConsumer.
3. No volume expansion allowed — allowVolumeExpansion: false means manual PV recreation to resize; always enable it.
4. Using NFS for write-heavy workloads — NFS introduces network latency for every write; use block storage (EBS/PD) for databases and Kafka.
5. Not snapshotting before StatefulSet updates — no rollback without snapshot; snapshot before every major update.
6. Shared PVs for multiple pods — EBS is RWO; multiple pods mounting the same PVC causes corruption; use RWX storage or separate PVCs.

---

References

• Kubernetes storage: kubernetes.io/docs/concepts/storage/
• CSI drivers: kubernetes-csi.github.io/docs/
• Longhorn: longhorn.io/docs/
• Volume snapshots: kubernetes.io/docs/concepts/storage/volume-snapshots/
• Related skills: [[infra-kubernetes-cluster-health]], [[infra-kubernetes-cost-optimizer]]