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What I Wish I Knew Before Running AI Workloads on Bare Metal Kubernetes

by davidcrilly | Jul 1, 2026 | AI, Home Lab

This one’s shorter than usual — less narrative, more a list I wish someone had handed me before I started running inference on Moya. If you’re about to do the same thing on your own cluster, save yourself the weekends I lost. 1. Your GPU desktop is now a...

Configuring Moya’s Desktop Nodes for Local LLM Inference

by davidcrilly | Jul 1, 2026 | AI, Home Lab

Last post I covered the why behind running private AI on Moya. This one is the how — specifically, getting GPU-backed inference working cleanly on a bare-metal Kubernetes cluster instead of just running a model on a desktop with a script and calling it a day. If...

Why I Run Private AI on Moya (and What It Actually Does)

by davidcrilly | Jun 29, 2026 | AI, Home Lab, Moya

When I teased “private AI workloads on Moya” in my first post, a few people asked me the same question: why bother? Cloud AI is one API call away, it’s cheap, and somebody else deals with the GPUs catching fire. Fair question. Here’s my honest...

Working With Your Brain, Not Against It: ADHD-Friendly Homelab Strategies

by davidcrilly | Jun 22, 2026 | Home Lab, Musings

Last post covered why homelabs and Kubernetes specifically seem to be such a good (or dangerous) match for ADHD-style novelty-seeking and hyperfocus. This one is more practical: what the research and the ADHD community actually suggest for working with that pattern,...

The Homelab Never Finishes, and Maybe That’s the Point

by davidcrilly | Jun 21, 2026 | Home Lab, Musings

I’ve never met a homelab that was “done.” Mine certainly isn’t — Moya gets a new workload, Talyn gets torn down and rebuilt to test an idea, Pilot’s storage layout gets reorganized for the third time this year because I read one blog post...

Project Moya: Inside the 90TB, Multi-Cluster Farscape Home Lab

by davidcrilly | Jun 19, 2026 | Home Lab, Moya, Pilot, Talyn

If you are anything like me, you cannot look at a perfectly functioning piece of technology—or a solid kitchen wall—without immediately thinking: “How does that work?” That foundational itch to tear things down, figure them out, and re-engineer them is...

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