When people ask why I run Kubernetes at home, I tell them: you can’t truly understand a tool until you run it in production. And what better production than your home lab? After years of managing Kubernetes clusters professionally and personally, here are my hard-earned lessons.

Why Kubernetes at Home?

Professional Development

  • Stay current with K8s trends
  • Test new features in a safe environment
  • Practice incident response

Personal Projects

  • Host multiple applications
  • Learn infrastructure-as-code
  • Build home automation

My Home Lab Setup

Hardware

  • 3x Raspberry Pi 4 (4GB) or old laptops
  • Synology NAS for persistent storage
  • Ubiquiti Dream Machine for networking

Software

  • k3s (lightweight Kubernetes)
  • Metallb for load balancing
  • Longhorn for storage
  • Traefik for ingress

Architecture

┌─────────────────────────────────────────┐
│           Home Network                   │
├─────────────────────────────────────────┤
│  ┌───────────────────────────────────┐  │
│  │    k3s Cluster (3 nodes)          │  │
│  │  ┌─────┐  ┌─────┐  ┌─────┐       │  │
│  │  │ Pi1 │  │ Pi2 │  │ Pi3 │       │  │
│  │  └─────┘  └─────┘  └─────┘       │  │
│  └───────────────────────────────────┘  │
│              ↓ ↓ ↓                      │
│  ┌───────────────────────────────────┐  │
│  │  Services                         │  │
│  │  - Plex                           │  │
│  │  - Home Assistant                 │  │
│  │  - GitLab                         │  │
│  │  - Portfolio sites                │  │
│  └───────────────────────────────────┘  │
└─────────────────────────────────────────┘

Key Lessons

Lesson 1: Storage is Hard

Problem: Container storage is ephemeral Solution: Use Longhorn or NFS for persistent volumes

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: data-pvc
spec:
  storageClassName: longhorn
  resources:
    requests:
      storage: 10Gi

Lesson 2: Networking Takes Time

Problem: Pods can’t communicate Solution: CNI plugins matter. Use Calico or Flannel.

# Install k3s with flannel
curl -sfL https://get.k3s.io | INSTALL_K3S_EXEC="--flannel=wireguard" sh

Lesson 3: Backups are Essential

Problem: Lost data is lost forever Solution: Velero for cluster backups

velero backup create home-cluster-backup
velero schedule create daily-backup --schedule="0 0 * * *"

Lesson 4: Resource Limits Save You

Problem: One app consumes everything Solution: Always set resource requests and limits

resources:
  requests:
    memory: "256Mi"
    cpu: "250m"
  limits:
    memory: "512Mi"
    cpu: "500m"

Lesson 5: GitOps Changes Everything

Problem: Manual deployments are error-prone Solution: ArgoCD or Flux

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: my-app
spec:
  source:
    repoURL: https://github.com/irfancode/manifests
    path: apps/my-app
  destination:
    server: https://kubernetes.default.svc
  project: default

Useful Tools

CLI Tools

  • k9s — Terminal UI for Kubernetes
  • kubectl — Official CLI
  • kubectx — Switch clusters easily

Monitoring

  • Prometheus + Grafana — Metrics and visualization
  • Loki — Log aggregation
  • Alertmanager — Alerts

Security

  • Kyverno — Policy engine
  • Trivy — Vulnerability scanning

Common Mistakes

Mistake Fix
No resource limits Always set requests/limits
Running as root Use security contexts
No backups Velero + Longhorn snapshots
No monitoring Prometheus from day one
Manual deployments GitOps from day one

What’s Running at Home

My current home lab runs:

  • Plex media server
  • Home Assistant for smart home
  • GitLab for version control
  • Portfolio websites
  • Pi-hole for DNS ad-blocking
  • Vault for secrets management

Conclusion

Kubernetes at home isn’t about flexing—it’s about learning. The principles you learn managing a homelab directly translate to production environments.

Start small. One node. Add complexity as you learn. And remember: the goal isn’t perfection—it’s understanding.

What’s in your homelab? Let’s connect and share experiences!

Connect: LinkedIn GitHub