One of the things I enjoy most about running a homelab is taking random pieces of technology and turning them into something genuinely useful (or at least really cool).
Recently, I set out to build a system that could answer a simple question:
“What aircraft is closest to my house right now?”
That question turned into a full-blown project involving:
Like many people running a homelab, I found myself with a growing collection of self-hosted services—Grafana for monitoring, Uptime Kuma for alerts, Portainer for container management, and more.
Each service worked well on its own, but there was one problem:
every service had its own login.
It wasn’t just inconvenient—it also didn’t scale. Managing users, credentials, and access across multiple applications quickly becomes messy.
Early in my career I worked as an intelligence analyst, a role that taught me how to work with incomplete information, evaluate sources, and build narratives from scattered data points. Over the years I’ve found myself applying those same skills in unexpected places. One of the most interesting examples has been genealogy — the study of family history.
My maternal grandmother developed a deep interest in our ancestry late in her life and passed that curiosity on to me. My original goal was simple: learn more about where my family came from and who my ancestors were. But as my research evolved, I realized I was approaching genealogy the same way I approached intelligence work — identifying patterns, validating evidence, and following threads wherever they led.
Yesterday morning, I had discovered that my automatic feeder on my aquarium had dumped its entire hopper in the aquarium (not a big deal, it was almost empty), and was unable to retract the hopper to the original position. I initiated a manual feed via a button on the back, and the hopper would just spin and never return to initial start position.
I initially thought that the gear mechanism had just gotten misaligned or stuck, I disassembled the feeder and reset the gears so that everything was in the correct initial state. Upon testing I ended up with the same result. This now meant that I had to figure out how the feeder knows when to retract the hopper back to the initial state at the end of the feed cycle.
The Dunning-Kruger Effect is often used to explain overconfidence, but I don’t think we talk enough about its opposite effect.
As someone who’s spent years as a “jack of many trades,” I’ve found myself well past the “Peak of Mt. Stupid” in several areas, now sitting somewhere between the “Valley of Despair” and the “Slope of Enlightenment.” With experience comes perspective, and with perspective comes the uncomfortable awareness of just how much there is to learn.