For two publicly-reachable services I personally run, I decided the way that involved the least work and was most likely to be low-drama -- initially, and ongoi

For two publicly-reachable services I personally run, I decided the way that involved the least work and was most likely to be low-drama -- initially, and ongoing -- was to just put them on separate $5/month Linodes running Debian Stable. My personal wiki has very short notes on how to rebuild each from scratch. (Pretty much: push Linode Web site buttons to make a new Debian Stable instance, get a shell and do this `apt install` command line, and edit config file like so). Data gets pushed/pulled via simple shell scripts run on laptop (usually using SSH and rsync). Separate from those services, my GPU server is a separate box at home, and frequently changing at a low level, so blasting it entirely a few times has made pragmatic sense, so I'm glad it's not sharing config complexity any other resources. And setting up the large ML stacks down to proprietary drivers sometimes is initially very experimental, and I need to do it manually first anyway, not yet ready to make a Dockerfile or set up passthrough for containers, and after the experiment works, there's no reason to do that. Were I making a production setup, or something reproducible by others, I'd do more after the initial experiment setup. Wrangling much more complex layers atop (e.g., K8s, Docker, Terraform, Ansible, NixOS, etc.) sometimes means more things that can go wrong, and sometimes more time spent learning someone else's bureaucracy. Most of tech work now is learning piles of other people's bureaucracy. That makes sense for businesses that actually need that complexity, and for people who just want to copy&paste cargo-cult command lines and hopefully it works, and for people who want to homelab it for experience (which is perfectly valid). But the way I run my important services and my experimental box seemed to be easier overall. Of course, for curiosity/resume/masochism purposes, I do have a separate K8s cluster at home, which runs nothing important, and which I can obliterate and change and experiment with at will, without being encumbered by it running services I actually need.