I think the constant thought in the back of my mind is… Docker containers and Nginx is definitely enough for my needs. At work, it’s a different story, but more most things, it can be over kill.
So something that could be run with $5 droplet, suddenly requires $200.
They you want to install grafana, ELK, service mesh and whatnot.
You won't get a private LAN (so you'll need some firewall rules on the hoster side) and you'll have to do some setup to get everything served up on the right public IP address(es), but you don't need a dedicated load balancer product. Unless you expect your virtual servers to go down randomly, I suppose.
I've set up k0s on Oracle's free service to mess with. It doesn't need nearly as much as 12GiB of RAM. Give it 500MiB per machine to be happy and it _should_ run fine with 10.5GiB to spare unless you're adding tons of overlays and additional services on top of your applications.
As far as I can tell, the biggest cost with Kubernetes is maintaining the system and keeping up to date with the advancements and deprecations in the Kubernetes field. You can't just upgrade the Kubernetes version and expect everything to work, and every new concept that replaces anything old comes with Kubernetes layers of complexity.
I honestly don't know what so many companies are using all those resources Kubernetes provides for. I have a feeling people are so caught up in the "modern server management" world that they've forgotten how powerful and reliable a $25 VPS is these days.
[1] https://registry.terraform.io/modules/kube-hetzner/kube-hetz...
I have a nice server that I used for 10-20 applications like Time Machine backup, media streaming, file syncing, home automation, etc. I was looking into k8s, but it seemed way too complicated when I only have one physical server, so I went with Docker + Docker Compose instead.
All in all, I still think docker, docker compose and nginx is the way to go for hobbyist stuff. I doubt my ISP would let me host anything at a huge scale off my home router anyways.
If you start having more servers, a k8s cluster can do something like automatically transfer workloads when one machine has an issue for example, or dynamically allocating storage (even cloud) when needed, or allowing you to issue a single command to spin up more instance of whatever task you'd want to run more in parallel, or updating a version in a config file and letting the cluster do the job of stopping/updating/restarting things.
But what you also have to do is ensure the underlying networking between machines works, all versions of the binaries on all the machines of the cluster are in close agreement with each others, encryption of data via certificates and CAs is satisfactory, and your master(s) might require different maintenance from the workers - but you'll end up reading the docs to know how to roll updates step by step.
In your use case I would stick with a smart use of docker-composes, perhaps just centralized in a private repo, with cron jobs on top. If you buy/rent a couple machines of any kind (from raspberry pis to cloud instances) to put on your network and run things for you, then a cluster becomes increasingly interesting as the amount of tasks needed/wanted and amount of computing available grows.
My context: I have some limited experience with work (including some scary "abstractions" on top of K8s & Helm) and a recent CKA (certified kubernetes administrator hands-on certification) from LinuxFoundation.