Demystifying Kubernetes Storage: Lessons from My Homelab
When most people start learning Kubernetes, the focus is on Pods, Deployments, and Services. These concepts are critical, but there’s one area that often catches beginners off guard: storage.
Containers are designed to be ephemeral. Once a Pod stops, everything inside it is gone. That’s fine for stateless applications, but what about databases, logs, or anything that needs to persist across restarts? This is where Kubernetes storage concepts come in.
In this article, I’ll share what I’ve learned about Kubernetes storage while experimenting in my homelab.
1. Ephemeral vs Persistent Data
By default, containers are stateless. If a Pod is deleted or rescheduled, all of its data is wiped away. For workloads like a simple web server, that’s not a big deal. But for applications like MySQL, PostgreSQL, or even a small wiki, data persistence is non-negotiable.
This is why Kubernetes introduces the concept of Persistent Volumes (PVs).
2. Persistent Volumes (PVs) and Persistent Volume Claims (PVCs)
Think of a Persistent Volume (PV) as the actual storage resource made available to the cluster. It could be local disk, NFS, or cloud block storage.
A Persistent Volume Claim (PVC) is like a request ticket from an application that says, “I need 10GB of storage.” Kubernetes then binds the PVC to a PV that meets the request.
This separation makes storage more flexible and reusable.
3. StorageClasses and Dynamic Provisioning
In the early days of Kubernetes, storage was manually provisioned. Admins had to create PVs ahead of time and match them to PVCs.
With StorageClasses, Kubernetes can dynamically provision storage as needed. This is especially useful in cloud environments where volumes can be created on-demand.
In my homelab, I’ve used StorageClasses with NFS and experimented with Longhorn to handle dynamic provisioning. It simplifies the process tremendously.
4. CSI Drivers
The Container Storage Interface (CSI) allows Kubernetes to connect with different storage backends through plugins. Whether you’re on AWS EBS, Google Persistent Disk, Ceph, or just running NFS at home, CSI drivers are what make the connection possible.
For homelabs, this is where you can get creative. You can integrate open-source projects like Longhorn or Rook-Ceph to simulate real-world setups.
5. Backups and Recovery
Even with persistent storage, accidents happen. Nodes can fail, data can get corrupted, and clusters can go down. Having a backup strategy is still essential. Tools like Velero can back up both your cluster configuration and your persistent volumes, making recovery much smoother.
Key Takeaways
✅ Kubernetes storage is critical for running stateful applications.
✅ Persistent Volumes and Claims abstract the complexity of storage.
✅ StorageClasses and CSI drivers open the door to automation and flexibility.
✅ Backups remain non-negotiable, even with persistent volumes.
Final Thoughts
Learning Kubernetes storage in my homelab has given me a new appreciation for the complexity behind keeping data safe and accessible in a cloud-native environment. It’s not just about running containers, it’s about ensuring that the data they depend on is resilient, scalable, and recoverable.
🔍 What storage solutions have you tried in your Kubernetes projects? Do you prefer cloud-native offerings or open-source options like Longhorn and Rook? I’d love to hear about your experiences.