Many of the posts I read here are about Docker. Is anybody using Kubernetes to manage their self hosted stuff? For those who’ve tried it and went back to Docker, why?
I’m doing my 3rd rebuild of a K8s cluster after learning things that I’ve done wrong and wanted to start fresh, but when enhancing my Docker setup and deciding between K8s and Docker Swarm, I decided on K8s for the learning opportunities and how it could help me at work.
I use k8s at work and have built a k8s cluster in my homelab… but I did not like it. I tore it down, and currently using podman, and don’t think I would go back to k8s (though I would definitely use docker as an alternative to podman and would probably even recommend it over podman for beginners even though I’ve settled on podman for myself).
K8s itself is quite resource-consuming, especially on ram. My homelab is built on old/junk hardware from retired workstations. I don’t want the kubelet itself sucking up half my ram. Things like k3s help with this considerably, but that’s not quite precisely k8s either. If I’m going to start trimming off the parts of k8s I don’t need, I end up going all the way to single-node podman/docker… not the halfway point that is k3s.
If you don’t use hostNetworking, the k8s model of traffic routes only with the cluster except for egress is all pure overhead. It’s totally necessary with you have a thousand engineers slinging services around your cluster, but there’s no benefit to this level fo rigor in service management in a homelab. Here again, the networking in podman/docker is more straightforward and maps better to the stuff I want to do in my homelab.
Podman accepts a subset of k8s resource-yaml as a docker-compose-like config interface. This lets me use my familiarity with k8s configs iny podman setup.
Overall, the simplicity and lightweight resource consumption of podman/docker are are what I value at home. The extra layers of abstraction and constraints k8s employs are valuable at work, where we have a lot of machines and alot of people that must coordinate effectively… but I don’t have those problems at home and the overhead (compute overhead, conceptual overhead, and config-overhesd) of k8s’ solutions to them is annoying there.
I’d suggest Podman over docker if someone is starting fresh. I like Podman running as rootless, but moving an existing docker to Podman was a pain. Since the initial docker setup was also a pain, I’d rather have only done it once :/
For me the use case of K8s only makes sense with large use cases (in terms of volume of traffic and users). Docker / Podman is sufficient to self-host something small.
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I use k8s at work and have built a k8s cluster in my homelab… but I did not like it. I tore it down, and currently using podman, and don’t think I would go back to k8s (though I would definitely use docker as an alternative to podman and would probably even recommend it over podman for beginners even though I’ve settled on podman for myself).
Overall, the simplicity and lightweight resource consumption of podman/docker are are what I value at home. The extra layers of abstraction and constraints k8s employs are valuable at work, where we have a lot of machines and alot of people that must coordinate effectively… but I don’t have those problems at home and the overhead (compute overhead, conceptual overhead, and config-overhesd) of k8s’ solutions to them is annoying there.
I’d suggest Podman over docker if someone is starting fresh. I like Podman running as rootless, but moving an existing docker to Podman was a pain. Since the initial docker setup was also a pain, I’d rather have only done it once :/
For me the use case of K8s only makes sense with large use cases (in terms of volume of traffic and users). Docker / Podman is sufficient to self-host something small.