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2026

Building a Fantasy Football Draft Engine for Seven Leagues at Once

·6974 words·33 mins
I play in seven fantasy football leagues. Five on Sleeper, two on Yahoo. Six snake drafts and one auction. Team counts of 10 and 12. PPR, half-PPR, and one league that pays a point for every first down. One of them scores individual defensive players. One scores kickers purely on field goal yardage with no penalty for a miss. Five are ordinary redrafts, one is a keeper league, and one is a dynasty league where rosters carry over whole.

How K3s Silently Grew a 40 GB SQLite Database and Took Down My Cluster

·1255 words·6 mins
My cluster — a single-node K3s instance running about 60 ArgoCD-managed applications — had been slowly dying for months. Pods crash-looped with “context deadline exceeded” errors. Leader elections failed. The metrics server stopped working entirely. I assumed it was resource pressure and tuned probe timeouts. The real problem was underneath all of it: K3s’s SQLite datastore had silently grown to 40 GB.

Whole-Home Audio with Music Assistant: Kubernetes Gotchas and a Silent Raspberry Pi

My music setup had accreted into a mess. Across two Kubernetes clusters I was running Navidrome, Lyrion Music Server (LMS), beets, and my own AI radio station (SUB/WAVE) - plus a Raspberry Pi running piCorePlayer wired into a Dayton DAX66 matrix amp for whole-home audio. Four things that all “played music,” none of which talked to each other, and no single place to control any of it from Home Assistant.

Mac Studio as a Kubernetes Compute Satellite

·1077 words·6 mins
My K3s cluster runs on six Intel NUCs. They’re great for the 50+ containers that make up my homelab — Plex, Home Assistant, Frigate, Paperless, the usual suspects. But they’re terrible at machine learning. Four Skylake cores and 32 GB of RAM per node doesn’t get you far when Immich wants to classify 80,000 photos or Frigate wants a vision model to describe who’s at your door.