Question for the #homelab nerds out there.
I have a running family of projects (well more like a breakfast club of misfits) that I've been deploying to my "lab" (by which I mean, currently, a mediocre #raspberrypi), currently stitched together with docker-compose.
An important underlying theme to this effort, and a reason why I'm sticking with the pi, is a focus upon resource-constrained, high-efficiency, self-contained, open-source computing. Kinda the opposite of the vibe of the times, I know, but I think it's important.
I suspect I'm far from alone in this, and I'm curious: what are other folks working on projects like this use for observability? So far, I'm cobbling my own together with shell scripts and instrumentation in the code (using #tokio tracing if it matters).
I don't really want to go down the "standard" bobsled run that ends with an army of proxmox vms and various free-tier accounts on cloud-based services... again, resource-constrained and self-contained. It feels like we used to have tools like this, when every server was a pet; surely those haven't gone away?
Search results, unfortunately, are twenty pages of "The N best homelab observability stacks in 2026! (Number N-M will suprise you)" AI-generated marketing blogslop, all of which I've sampled launch an aforementioned sled.
So, asking here. Tips solicited. Retoots welcome.