Your Kubernetes Storage is Broken - Here's How to Fix It

Persistent Volume Lifecycle: Available → Bound → Released → Failed (and how each state fucks you differently)

Kubernetes storage breaks for the dumbest reasons. I've been debugging this shit for 3 years, and here's what actually goes wrong and why the error messages are designed to waste your time.

The Persistent Volume Lifecycle (Where Everything Goes Wrong)

The PV lifecycle has four states: Available, Bound, Released, and Failed. The fun part? Your volumes get stuck in Released state constantly.

Here's what happens: Someone deletes a PVC but the PersistentVolume has reclaim policy: Retain. The volume goes into Released state - it keeps your data but becomes completely fucking useless for new claims. I've lost entire weekends debugging "no available volumes" errors when there's literally 500GB of storage just sitting there in Released state doing nothing.

The actual fix is simple but the error message tells you jack shit about it.

Storage Class Configuration Disasters

StorageClass → CSI Driver → Cloud Provider API → Actual Storage (and 47 ways this chain can break)

StorageClass misconfigurations will ruin your weekend. I've seen production outages caused by typos in StorageClass names. Here's the shit that actually breaks:

Invalid Provisioner Names: Typo in the provisioner field? Your PVCs will sit in pending forever. No error message. No indication why. Just pending. Forever. Like waiting for customer support to respond. Check your CSI driver names - the CNCF landscape has all the certified ones.

Parameter Screwups: AWS EBS needs type: gp3, not type: gp2 in 2025. Azure wants skuName: Premium_LRS. GCP uses type: pd-ssd. Get any of these wrong and you'll spend hours debugging cryptic provisioning errors. The AWS EBS types documentation explains which parameters work with which volume types.

RBAC Nightmare: Storage provisioners need specific cluster permissions. Missing one permission? Silent failure. The AWS EBS CSI driver needs like 15 different RBAC rules. Miss one and good luck figuring out which one because Kubernetes sure as hell won't tell you. The RBAC troubleshooting guide has debugging tips if you enjoy pain.

Production story from last month: failed to provision volume with StorageClass "fast-ssd": rpc error: code = InvalidArgument desc = invalid VolumeCapability: unknown access type UNKNOWN - turns out someone used accessModes: ["ReadWriteOnce"] instead of accessModes: ["ReadWriteOnce"]. The quotes matter in some CSI drivers.

Resource Limits That Will Bite You in the Ass

Cloud providers have limits that Kubernetes doesn't tell you about:

Node Attachment Limits: AWS EC2 instances can attach 28 EBS volumes max on Nitro instances. Hit this limit and your pods won't schedule. The error? FailedScheduling: node(s) had volume node affinity conflict. Helpful, right?

Zone Disasters: Pod scheduled in us-west-2a, volume created in us-west-2b? No mount for you. AWS won't attach cross-zone. Use volumeBindingMode: WaitForFirstConsumer or suffer. This GitHub issue has like 200 comments about it. The AWS multi-AZ guide explains cross-zone limitations in detail.

Quota Limits: AWS account quota for EBS volumes exceeded? You get failed to create volume: VolumeCreationError: Maximum number of volumes exceeded. But the AWS docs don't tell you this affects Kubernetes.

Backend Storage Full: I've seen NFS servers run out of space while Kubernetes shows "Available" StorageClass. The error: CreateVolume failed: rpc error: code = ResourceExhausted desc = Insufficient capacity. Kubernetes doesn't know your backend is toast. Set up storage monitoring to track backend capacity before it bites you.

Scheduling Conflicts (The Subtle Killers)

Pod → Scheduler → Node Selection → Volume Topology → Cross-Zone Attachment Failure (every damn time)

Pod scheduling gets complex when storage is involved. These will bite you:

Node Selector Hell: Your pod wants disktype=ssd nodes, but your PVC is bound to a volume that can only attach to disktype=nvme nodes. Deadlock. The scheduler documentation doesn't warn you about this. Use nodeAffinity rules for complex topology requirements.

Anti-Affinity Disasters: StatefulSet with podAntiAffinity can't schedule pod-1 because pod-0 is already on the only node where the volume can attach. I've seen this in production. The fix is ugly node taint juggling.

Topology Constraints: topologySpreadConstraints can force pods away from their storage. Kubernetes will choose topology compliance over storage affinity. Your pod sits in pending while its volume sits unused on the "wrong" node. The pod topology spread guide shows how to balance topology and storage requirements.

Permission Hell

Container permissions with volumes are painful:

File System Permissions: Container runs as UID 1001, volume owned by root. Result: permission denied everywhere. The fix? Add fsGroup: 1001 to your security context. Why isn't this the default? Nobody knows.

SELinux/AppArmor Nightmares: SELinux blocks your volume mounts with permission denied (audit: denied) in the logs. You need seLinuxOptions or fsGroup depending on the phase of the moon. Red Hat's docs are 47 pages long for a reason. The Pod Security Standards explain the security context requirements.

Container Runtime Chaos: Docker mounts volumes one way, containerd does it slightly differently. Migrate from Docker to containerd? Some of your volumes will break. This migration guide mentions it in passing like it's no big deal. Check the runtime comparison guide for specific differences.

Network Failures (The Invisible Killers)

CSI Controller → gRPC → Node Plugin → Kernel Mounts (when network hiccups kill everything)

Network issues with storage are the worst to debug:

API Server Disconnects: CSI controller loses connection to API server for 30 seconds? Volumes get stuck in "Terminating" state for hours. This bug has been open since 2019. Configure API server high availability to prevent single points of failure.

Cloud API Rate Limits: AWS throttles your EBS API calls when you create 50 volumes at once. Half succeed, half fail. Now you have a split-brain clusterfuck. The AWS API docs mention rate limits but not what happens to Kubernetes. Use exponential backoff in your automation.

CSI Driver Bugs: Third-party CSI drivers are barely tested. The Longhorn driver has 500+ open issues. Half are "volume stuck in detaching state". Good luck. Check the CSI driver compatibility matrix before deployment.

This bit me in the ass when: I spent 6 hours debugging why new PVCs wouldn't provision. Turned out the CSI driver pod crashed and restarted in a different namespace, but the RBAC was namespace-scoped. No error messages. Just silent failure. I wanted to throw my laptop out the fucking window.

This isn't theoretical bullshit - these are the actual failures that will ruin your day. Like I mentioned earlier, the error messages usually lie to you, so the next section shows you how to diagnose which specific problem you're dealing with and how to fix it without losing your sanity.

Troubleshooting Decision Tree: kubectl describe → check events → blame the CSI driver → fix RBAC → repeat

Here's how to debug storage failures when you're staring at pending PVCs at 3am while your manager is asking for an ETA. No bullshit theory - just the commands that actually work and the gotchas that nobody bothers to document.

When Your PVC Gets Stuck Pending (Happens All the Time)

PVC stuck in Pending state? Don't panic. Here's the debugging order that actually works:

Step 1: Read the Events (They Actually Tell You Something)

kubectl get pvc -n <namespace>
kubectl describe pvc <pvc-name> -n <namespace>

Ignore everything except the Events section. Here's what the cryptic messages actually mean:

• no persistent volumes available for this claim and no storage class is set = You forgot to specify a StorageClass, genius
• waiting for a volume to be created, either by external provisioner = Your CSI driver is completely fucked
• storageclass \"fast-ssd\" not found = Typo in the StorageClass name (happens more than you'd think)
• failed to provision volume with StorageClass \"standard\": invalid VolumeCapability = Your access modes are wrong (again)

I've debugged this exact scenario: ProvisioningFailed: failed to create volume: VolumeCreationError: InvalidParameter: Encrypted flag cannot be specified with gp2 volumes. Translation: You can't encrypt GP2 volumes in AWS, use GP3.

Step 2: Check If Your StorageClass Actually Exists (And Isn't Broken)

kubectl get storageclass
kubectl describe storageclass <storage-class-name>

The provisioner field must match your actual CSI drivers. Here's what to use in 2025:

• AWS EKS: ebs.csi.aws.com (not the old kubernetes.io/aws-ebs - that's deprecated). Check the EKS storage guide for setup details.
• Azure AKS: disk.csi.azure.com - see the Azure storage documentation
• Google GKE: pd.csi.storage.gke.io - reference the GKE persistent disks guide
• On-prem NFS: Whatever your NFS CSI driver calls itself

Common fuckups:

• Using old provisioner names from 2019 tutorials that are completely outdated - check the CSI migration guide
• Typos (I've literally seen ebs.csi.aw.com in production - someone missed the 's')
• Missing CSI driver pods entirely because nobody installed them - verify with the CSI driver installation guide

Check your CSI drivers are running: kubectl get pods -n kube-system | grep csi

Step 3: Check If You Have Any Volumes at All

kubectl get pv
kubectl describe pv <pv-name>

Look for volumes in Available state. If everything's Bound or Released, that's your problem right there.

Available = good, can bind to new PVCs
Released = stuck with old claim reference, needs manual cleanup
Failed = something's seriously broken, check the PV events - see the troubleshooting guide

Pro tip: kubectl get pv --sort-by=.status.phase shows you all the Available ones first.

Fixing Released Volumes (The Classic Gotcha)

This happens constantly. Someone deletes a PVC but the PV has reclaim policy: Retain, so it sits there in Released state being useless. Learn about reclaim policies to understand why this happens.

The Nuclear Option: Clear the ClaimRef

This fixes 90% of "no available volumes" issues:

kubectl patch pv <pv-name> -p '{\"spec\":{\"claimRef\": null}}'

WARNING: This will make the volume available but you'll lose the data binding. If you need the data, clone it first using volume cloning.

Verify it worked:

kubectl get pv <pv-name>

Status should change from Released to Available. If not, you probably have a typo in the PV name (been there).

Manual Surgery (When Patch Doesn't Work)

Sometimes the patch fails (usually RBAC issues). Edit it manually:

kubectl edit pv <pv-name>

Find this section and delete the whole thing:

spec:
  claimRef:              # Delete from here...
    apiVersion: v1
    kind: PersistentVolumeClaim
    name: old-pvc-name
    namespace: old-namespace
    uid: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx  # ...to here

Save and exit. The PV should go to Available immediately. If it doesn't, check for typos in the YAML (vim will fuck you up with its weird indentation bullshit).

Fixing StorageClass Problems

CSI Driver Components: Controller Pod (creates volumes) + Node Pod (mounts volumes) = Double The Failure Points

When Your Provisioner is Missing or Wrong

First, see what CSI drivers you actually have:

kubectl get csidriver
kubectl get storageclass -o wide

If kubectl get csidriver is empty, you don't have any CSI drivers installed. That's your problem.

Create a StorageClass that actually works:

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: working-storage  # Don't use hyphens if you can avoid it
provisioner: ebs.csi.aws.com  # Must match your CSI driver exactly
parameters:
  type: gp3              # gp3 is cheaper and faster than gp2 in 2025
  fsType: ext4
  encrypted: \"true\"      # Encrypt everything, it's 2025
volumeBindingMode: WaitForFirstConsumer  # Prevents cross-zone disasters
allowVolumeExpansion: true               # You'll need this eventually

Apply it:

kubectl apply -f working-storageclass.yaml

Real gotcha: Some CSI drivers are case-sensitive about parameters. AWS CSI wants \"true\" not true for the encrypted parameter. Check the StorageClass parameter reference for each provisioner type.

RBAC Clusterfuck (When Permissions Are Missing)

CSI drivers need specific RBAC permissions. If they're missing, provisioning fails silently.

Check if your CSI driver pods are running:

kubectl get pods -n kube-system | grep csi
kubectl logs -n kube-system <csi-provisioner-pod-name>

Look for errors like:

• persistentvolumes is forbidden: User \"system:serviceaccount:kube-system:ebs-csi-controller-sa\" cannot create resource
• storageclasses.storage.k8s.io is forbidden

If you see permission errors, RBAC that won't make you cry:

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: csi-provisioner-role
rules:
- apiGroups: [\"\"]
  resources: [\"persistentvolumes\"]
  verbs: [\"get\", \"list\", \"watch\", \"create\", \"delete\", \"patch\"]
- apiGroups: [\"\"]
  resources: [\"persistentvolumeclaims\"]
  verbs: [\"get\", \"list\", \"watch\", \"update\"]
- apiGroups: [\"storage.k8s.io\"]
  resources: [\"storageclasses\", \"csinodes\"]
  verbs: [\"get\", \"list\", \"watch\"]
- apiGroups: [\"\"]
  resources: [\"events\"]
  verbs: [\"list\", \"watch\", \"create\", \"update\", \"patch\"]  # CSI drivers create events
- apiGroups: [\"\"]
  resources: [\"nodes\"]
  verbs: [\"get\", \"list\", \"watch\"]                          # Needed for topology
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: csi-provisioner-binding
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: csi-provisioner-role
subjects:
- kind: ServiceAccount
  name: ebs-csi-controller-sa  # Replace with your CSI driver's service account
  namespace: kube-system

Note: The service account name depends on your CSI driver. Check with kubectl get sa -n kube-system | grep csi. See the RBAC best practices guide for more security configurations.

Addressing Node and Zone Constraints

Multi-Zone Nightmare: Pod in us-east-1a, Volume in us-east-1b, Attachment = Impossible

Multi-Zone Volume Binding Issues

When pods and volumes are scheduled in different availability zones:

1. Check node and volume zones:

kubectl get nodes --show-labels | grep topology.kubernetes.io/zone
kubectl describe pv <pv-name> | grep zone

2. Use topology-aware scheduling:

Add node selector to your pod specification:

spec:
  nodeSelector:
    topology.kubernetes.io/zone: <same-zone-as-volume>

3. Configure volume binding mode:

Set StorageClass to wait for pod scheduling:

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: zone-aware-storage
provisioner: ebs.csi.aws.com
volumeBindingMode: WaitForFirstConsumer  # Critical for multi-zone

Node Volume Attachment Limits

When nodes exceed volume attachment limits:

1. Check current volume attachments:

kubectl describe node <node-name> | grep -A 10 \"Allocated resources\"

2. Identify volume attachment limits:

kubectl get node <node-name> -o yaml | grep -E \"attachable-volumes|maximum.*volumes\"

3. Redistribute workloads or scale nodes:

Either move pods to nodes with available capacity or add nodes to the cluster.

Volume Mount Permission and Security Issues

Container Security Context Problems

When containers cannot write to mounted volumes:

1. Check pod security context:

kubectl describe pod <pod-name> | grep -A 10 \"Security Context\"

2. Add appropriate security context to pod specification:

spec:
  securityContext:
    runAsUser: 1001
    runAsGroup: 1001
    fsGroup: 1001  # Critical for volume permissions
  containers:
  - name: app
    securityContext:
      allowPrivilegeEscalation: false
      runAsNonRoot: true

3. For NFS or shared storage, ensure proper ownership:

## On the storage backend, set appropriate permissions
chown -R 1001:1001 /path/to/nfs/share
chmod -R 755 /path/to/nfs/share

That covers the main ways storage breaks and how to actually fix it. Next up: how to prevent this shit from breaking in the first place.

Production Storage Strategy: Plan → Monitor → Backup → Test → Repeat (or watch it burn at 3am)

I've been running Kubernetes storage in production for 5 years and made every possible mistake. Here's what actually prevents storage disasters, not the theoretical bullshit from vendor whitepapers that nobody reads.

How to Build StorageClasses That Actually Work

Build StorageClasses That Actually Work in Production

Most StorageClasses suck because people copy-paste from tutorials written in 2019. Here's a StorageClass that won't break:

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: production-ssd  # Don't use \"default\" - you'll regret it
  annotations:
    storageclass.kubernetes.io/is-default-class: \"false\"  # Never auto-provision
provisioner: ebs.csi.aws.com
parameters:
  type: gp3              # gp3 is way better than gp2 in 2025
  iops: \"3000\"           # Default 3k IOPS, increase for DB workloads
  throughput: \"125\"      # 125 MB/s, tune based on actual usage
  fsType: ext4           # ext4 is reliable, xfs has weird edge cases
  encrypted: \"true\"      # Always encrypt, it's 2025 ffs
volumeBindingMode: WaitForFirstConsumer  # Prevents cross-zone disasters
allowVolumeExpansion: true               # You WILL need to expand volumes
reclaimPolicy: Retain                    # Don't auto-delete data

Why These Settings Matter:

• WaitForFirstConsumer: Learned this the hard way when I spent 4 hours debugging why pods couldn't mount their volumes. Without it, your volume gets created in us-east-1a and your pod gets scheduled in us-east-1b. No mount for you. The topology-aware provisioning guide has more details.
• Retain Policy: Delete policy has caused more production data loss than ransomware. I've seen entire databases disappear because someone used Delete. Use Retain or hate yourself later. The reclaim policies documentation explains why.
• Encryption: Security team will audit you eventually and ask uncomfortable questions. Encrypt everything now or do it later under pressure when they're breathing down your neck. Follow encryption best practices for compliance.
• Volume Expansion: Your database will grow. Your logs will grow. Everything grows. Enable this now or recreate everything later when you're out of space at 2am. Check the volume expansion guide for supported CSI drivers.

Create Storage Tiers That Make Sense

Don't create 15 different StorageClasses like some teams do. Three tiers work:

• fast-ssd: 10k IOPS, databases only (expensive as hell)
• standard-ssd: 3k IOPS, 95% of workloads (GP3 with sensible defaults)
• slow-hdd: Cheap HDD for logs and backups (SC1 on AWS)

Name them clearly. I've debugged incidents caused by confusion between "premium", "premium-ssd", "premium-fast", and "premium-v2". Follow the naming convention best practices for consistency.

Resource Limits (Before You Hit Cloud Quotas)

Set Storage Quotas Before Someone Bankrupts You

Storage quotas prevent junior devs from provisioning 100TB of GP3 storage for their "test" database:

apiVersion: v1
kind: ResourceQuota
metadata:
  name: storage-quota
  namespace: production  # Set per namespace, not cluster-wide
spec:
  hard:
    requests.storage: \"500Gi\"         # Total storage limit
    persistentvolumeclaims: \"20\"      # Max number of PVCs
    count/fast-ssd.storage: \"5\"       # Limit expensive storage types

Real example: Some junior dev created maybe 50 or 60 massive volumes during "load testing" over the weekend. Nobody noticed until the AWS bill came in. Cost: something like $2100/month. Maybe $2500? Either way, way too fucking much. Had to explain that one to finance and watch the color drain from their faces. Quota would have stopped this shit. Learn more about resource quotas for cost control.

Monitor Storage Before It Kills You

Monitoring That Actually Matters: Capacity % → IOPS Usage → Attachment Limits → Cost Alerts (not pretty graphs)

Set up alerts for the metrics that actually matter:

• Capacity at 80%: Alert before volumes fill up (learned this during a weekend outage)
• IOPS exhaustion: Alert when you hit provisioned IOPS limits
• Attachment limits: Alert at 25 attached volumes per node (AWS limit is 28)
• PVC pending > 2 minutes: Something's broken if PVCs don't bind quickly
• Storage costs: Alert when monthly spend increases 50% (cost control)

Prometheus queries that actually work:

## Volume usage over 80%
kubelet_volume_stats_used_bytes / kubelet_volume_stats_capacity_bytes > 0.8

## PVC pending too long
kube_persistentvolumeclaim_status_phase{phase=\"Pending\"} == 1

Use Grafana dashboards that show storage trends, not just pretty graphs. The monitoring best practices guide explains what metrics matter for storage.

Backups (Because Shit Will Break)

Snapshot Lifecycle: Create → Store → Hope It's Not Corrupted → Test Recovery → Realize It Was Corrupted

Automate Snapshots or Cry Later

Volume snapshots are cheap insurance. Here's a snapshot class that works:

apiVersion: snapshot.storage.k8s.io/v1
kind: VolumeSnapshotClass
metadata:
  name: daily-snapshots
driver: ebs.csi.aws.com
deletionPolicy: Retain      # Keep snapshots even if class is deleted
parameters:
  encrypted: \"true\"         # Snapshot encryption

Schedule snapshots with a CronJob:

apiVersion: batch/v1
kind: CronJob
metadata:
  name: database-backup
spec:
  schedule: \"0 2 * * *\"     # 2 AM daily
  jobTemplate:
    spec:
      template:
        spec:
          containers:
          - name: snapshot
            image: bitnami/kubectl
            command:
            - /bin/sh
            - -c
            - |
              kubectl create volumesnapshot db-snapshot-$(date +%Y%m%d) \
                --from-pvc=database-pvc \
                --volume-snapshot-class=daily-snapshots

Don't use Velero unless you like debugging YAML hell. Native snapshots work fine. Compare backup solutions in the disaster recovery guide.

Actually Test Your Backups (Most Don't)

"Backup exists" != "backup works". Test recovery monthly:

1. Create test PVC from snapshot: kubectl create pvc test-restore --from-snapshot=snapshot-name
2. Mount in test pod: Verify data is intact
3. Application-level validation: Start your app with restored data
4. Measure recovery time: How long does restore actually take?

Classic failure mode: Company had daily snapshots for 2 years. During actual disaster, snapshots were corrupted due to CSI driver bug. They lost like 6 months of data, maybe more. Nobody wants to talk about exactly how much data got vaporized or who got quietly escorted out after that meeting.

Test your backups or become another horror story on /r/sysadmin. The backup testing checklist covers validation procedures.

Security and Access Control

Implement Least Privilege Access

Configure Role-Based Access Control (RBAC) to restrict storage operations:

apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  namespace: production
  name: storage-operator
rules:
- apiGroups: [\"\"]
  resources: [\"persistentvolumeclaims\"]
  verbs: [\"get\", \"list\", \"create\", \"update\", \"patch\"]
- apiGroups: [\"storage.k8s.io\"]
  resources: [\"storageclasses\"]
  verbs: [\"get\", \"list\"]

Enable Audit Logging

Enable comprehensive audit logging for storage operations to track changes and investigate issues:

apiVersion: audit.k8s.io/v1
kind: Policy
rules:
- level: Request
  resources:
  - group: \"\
    resources: [\"persistentvolumes\", \"persistentvolumeclaims\"]
  - group: \"storage.k8s.io\"
    resources: [\"storageclasses\"]

Network and Connectivity Reliability

Design for Network Partitions

Implement network-resilient storage configurations:

• Regional Storage: Use regionally replicated storage where available
• Connection Timeouts: Configure appropriate timeout values for storage operations
• Retry Logic: Implement exponential backoff for transient failures
• Health Checks: Monitor storage backend connectivity

Multi-Zone Architecture

Design storage architecture to handle availability zone failures:

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: database
spec:
  template:
    spec:
      topologySpreadConstraints:
      - maxSkew: 1
        topologyKey: topology.kubernetes.io/zone
        whenUnsatisfiable: DoNotSchedule
        labelSelector:
          matchLabels:
            app: database

Operational Excellence

Establish Storage Runbooks

Document standard operating procedures for common scenarios:

• Volume Expansion: Step-by-step procedures for increasing storage capacity
• Migration Procedures: Moving data between storage classes or providers
• Incident Response: Escalation procedures for storage failures
• Maintenance Windows: Procedures for planned storage maintenance

Regular Storage Health Checks

Implement automated health checks:

#!/bin/bash
## Storage health check script
kubectl get pv -o wide | grep -v Bound
kubectl get pvc -A | grep -v Bound  
kubectl get storageclass | grep FAILED
kubectl top nodes --sort-by=.status.capacity.storage

Schedule these checks to run regularly and alert on anomalies.

Version and Change Management

Maintain strict version control for storage configurations:

• GitOps Workflows: Store all storage configurations in version control
• Change Approval: Require reviews for production storage changes
• Rollback Plans: Maintain tested rollback procedures for configuration changes
• Documentation: Keep storage architecture documentation current

Performance Optimization

Right-Size Storage Resources

Optimize storage performance by matching resources to workload requirements:

• IOPS Provisioning: Monitor actual IOPS usage and adjust provisioned values
• Throughput Tuning: Configure throughput based on application bandwidth needs
• Access Patterns: Choose appropriate volume types for sequential vs. random I/O

Implement Storage Performance Monitoring

Track key performance indicators:

• Latency: Monitor read/write response times
• Queue Depth: Track I/O queue utilization
• Error Rates: Monitor for storage-related errors
• Utilization Patterns: Understand peak usage times and patterns

This isn't theoretical advice - it's battle-tested practices from running Kubernetes storage in production for years. Implement these or learn the hard way like I did (and trust me, you don't want to). For more production guidance, check the cluster operator best practices and storage performance tuning documentation.