🔧 My Reasoning for the Upgrade

Running Kubernetes on a single machine was a great way to get started. It was easy to manage, simple to test deployments, and perfect for learning. But over time, I ran into several limitations.

With just one node, I couldn’t truly explore:

• 🔁 Scheduling across multiple nodes
• 🛰️ Cluster communication and service discovery
• ⚙️ High Availability (HA) deployments
• 🔥 Disaster recovery scenarios
• 📈 Horizontal scaling and load balancing

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💸 The Upgrade

I decided to invest in a few low-cost Mini PCs to build out a proper cluster. I found a great option on Amazon: the OUMAX Mini PC. These are currently priced at just $141.54 USD.

They offer a solid set of specs for a home lab:

• 🧠 CPU: Intel N150 (4 cores, 4 threads)
• 💾 RAM: 16GB
• 📦 Storage: 500GB NVMe SSD
• 🌐 Networking: 2 x 2.5GbE NICs

🏗️ The New Lab Design

With three of these units, I’m now running a multi-node Kubernetes cluster where each node acts as both a control plane and a worker. The dual NICs let me physically separate:

• 🔒 Internal traffic: cluster and storage communications
• 🌍 External traffic: ingress/egress to the internet

This setup allows me to:

• 🔄 Simulate node failure and recovery
• 🛠️ Add/remove nodes dynamically
• 📡 Test longhorn and NFS over an isolated backend network
• 📊 Analyze service behavior under load

🖥️ What About the Old Machine?

The original system isn’t going away. I’ll be dedicating it to GPU-related workloads. It’s perfect for testing things like:

• 🧠 AI models with the NVIDIA toolkit
• 🎥 Media workloads like transcoding and inference

🧪 What’s Next?

I’m considering picking up a fourth Mini PC and running Windows Server 2019/2022 on it. This would let me experiment with Windows containers and hybrid clusters.

💡 I know Microsoft recommends Azure or Azure Stack HCI for Windows-based pods, but I’m curious to see what’s possible in a pure local setup. Even if it’s not ideal, the experience alone will be valuable.

🧵 TL;DR

My lab just leveled up. Going from one node to a real multi-node Kubernetes setup opens the door to high availability, better simulation of production-grade environments, and hands-on experimentation with real-world scenarios — all without breaking the bank.