My Home Lab: Why I Bother (And You Might Too)

My home lab, isn't a toy. Ok, in some way it is. It’s where I run crypto nodes, play with tools new tools and this is cheaper long term and gives me total control.

The Sandbox: Break and Learn Stuff

Cloud's great until you want to do something really experimental. Or something that might, you know, get your account flagged.

• Bitcoin ETL to ClickHouse: This was a fun one. Ran out of space. Fast. Didn't just scale up storage like you would in AWS. I had to dig into ClickHouse compression algorithms. Changed ZSTD to something more aggressive. Freed up a ton of space for all ETL that was required by the project. That's a real-world optimization skill you don't learn by clicking "increase disk size."
• Crypto Projects: Try running some heavy-duty crypto node or experimental blockchain project on a major cloud provider. See how long it takes to get a warning, or worse, a ban. Or best case scenario to ask for a quota increase and try to explain what you are trying to do.

RAM and Storage: It’s Not Just For Media Server

People ask, "What do you do with 64GB of RAM and 10TB of storage?"

Majority of the disk space is taken by the crypto nodes and a datawarehouse of extracted and transformed crypto data. I store it in ClickHouse for local analytics. I started with bitcoin and now expanding into other crypto nodes.

The Cost Argument: Numbers Don't Lie

"But the power bill!" Yeah, it's a thing. My rig, when it's on (it's not always maxed out), pulls around 150W. At €0.20/kWh, that's manageable. Compare that to a cloud VM with similar specs:

The hardware pays for itself. Long term, it’s cheaper. Plus, I own the metal.

Bottlenecks & Hybrid Plays

Have I hit a wall? Not really. Sometimes I wish I had a dedicated GPU for faster ML/LLM inference. But for what I do, it's usually overkill. If I really need serious GPU horsepower for a short burst, I'll spin up a cloud instance. Hybrid approach. The trick is not to pull massive datasets out of the cloud, to not pay for egress costs.

"Starter Kit"? Just Start.

Got a Raspberry Pi? Install Raspbian. Mess with Linux. Greenhouse controller, media server, IoT playground - whatever. The "must-have" is an "achiever mindset." With today’s AI tools, figuring stuff out has never been easier.

Backups? Not A Problem for now.

My current projects? Data is recreatable or derived. So, no complex backup strategy yet. When I need it, I'll probably encrypt and throw it in a cloud bucket – archival storage is cheap if you don't touch it often. Again, pragmatic.

Cloud is a tool.

Cloud is a tool. A home lab is a workshop. For a DevOps/Platformer, it’s invaluable. You get deep, hands-on experience you just can’t buy with a credit card. You learn how things really work, from the metal up. Main challenge is that you can't scale that quickly nor easily, you gotta work with what you have and solutions and speed of the solution are more valuable.