We went through these loops where I work due to the "you have to use k8s now" thing. Your control plane and worker node can be the same machine. Rancher + Ran

We went through these loops where I work due to the "you have to use k8s now" thing. Your control plane and worker node can be the same machine. Rancher + Rancher Kubernetes Engine made it a lot easier for us to manage as maintaining that is simply "run this docker container" and it deploys all the k8s gubbins for you. And k3s is a lot more lightweight on resources than k8s. Stuff like certificate rotation and kubernetes version upgrades are handled for us, it's reduced to clicking buttons on UI. Storage can be local, it's just not / wasn't well explained in the documentation. PersistentVolume[Claim]s can use directories on the host, those PVs/PVCs can be shared between many pods and you can mount subdirectories into each pod using `subPath`. You can get it all running on a laptop using a couple hundred MB of memory, all in all. So, not going to be ideal for running on a Raspberry Pi, but on par with a lightweight linux desktop environment in terms of resource usage. I hate the complexity sometimes, but then I still end up having the same learning curves with things like SystemD when I use them anyway - every "run a bunch of stuff on my machine and restart it if it breaks" system seems to be rife with edge cases and behaviours which you have to dig deep into the documentation to see - and we don't _want_ to RTFM if we don't expressly _have_ to :-) ^ Although, okay, SystemD doesn't require you to have random HTTPS authenticated endpoints to talk to it and TLS certificates which expire every year and consists of _one_ init process rather than like 7 interdependent docker containers which can restart at any time and rely on container infrastructure to be running and argh. Okay yeah the flashbacks are happening and I agree with everything you've said again.