I mean that with k3s you can get a kubernetes cluster running with 0 effort on a single machine. It is easier to maintain, because it handles restarting containers, updating containers, managing ports, provisioning storage, creating databases, etc for you. I've found the logs and events system to be super useful for troubleshooting compared to Dockerd, but maybe it can be tricky if it does something you don't expect it to.

Obviously you need to learn how to use that automation to take advantage of it, and stuff like networking and persistent volumes can be confusing if you don't have a good guide on it. The fact that there are different drivers for networking, storage, database management, etc can also take a bit of time. That said, networking and storage can be confusing on Docker too if you don't have a good guide, and Docker-compose also has a learning curve, so I honestly don't think Kubernetes is that much more effort. The main thing is that most guides are written for Docker, but the Kubernetes documentation is really good too.

If you just want to just run containers for jellyfin and home-assistant, Docker compose will be good enough. But if you want databases, reverse proxy, certificates, dns, self-healing, etc, for running bigger stuff like nextcloud and lemmy, then I would spend the extra 50% effort and do it on Kubernetes, it'll save you time and headaches in the long run.

Asking an LLM like Lllama or ChatGPT might be a good way to learn the basics with Kubernetes, but things move fast once you start getting into the newest operators like CNPG and Gateway API.