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.
What’s your story?
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Kubernetes is useful if you have gone full cattle over pets. And that is very uncommon in home setups. If you only own one or two small machines you cannot destroy infra easily in a “cattle” way, and the bloatware that comes with Kubernetes doesn’t help you neither.
In homelabs and home servers the pros of Kubernetes are not very useful: high availability, auto-scaling, gitops integrations, etc: Why would you need autoscaling and HA for a SFTP used only by you? Instead you write a docker-compose.yml and call it a day.
The one exception to this is if you’re using your homelab to learn kubernetes.
That was the only time I used K8s and k3s on my homelab.
And for anything that I do want to set up in a HA/cattle kind of way, I use Docker Swarm, as it feels like a more comfortable extension of docker compose.
This right here
This mostly, I haven’t seen a compelling reason to leave my docker setup.
I think the biggest reasons for me have been growth and professional development. I started my home cluster 8 years ago as a single node of basically just running the hack/ scripts on my Linux desktop. I’ve been able to grow that same cluster to 6 hosts as I’ve replaced desktops and as I got a bit into the used enterprise server scene. I’ve replaced multiple routers and moved behind cloudflare, added a private CA a few times, added solid persistence with rook+ceph, and built my ideal telemetry stack, added velero backups into Backblaze b2, and probably a lot more I’m not thinking of.
That whole time, I’ve had to do almost zero maintenance or upgrades on the side projects I’ve built over the years, or on the self hosted services I’ve run. If you ignore the day or so a year I’ve spent cursing my propensity to upgrade a tad too early and hit snags, though I’ve just about always been able to resolve them pretty quickly and have learned even more from those times.
And on top of that, I get to take a lot of that expertise to work where it happens to pay quite well. And I’ve spent some time working towards building the knowledge into a side gig. Maybe someday that’ll pay the bills too.
One line from your comment struck a chord. The part about maintenance and upgrades. I feel like I get stuff set up and working and go about my life and then a failure happens at the most inopportune moment. Mostly, the failures are when I have a few hours free and decide to upgrade the OS and everything breaks and all the dependencies fall apart and some feature is no longer supported. That’s where I started looking to K8s to just roll back until I have time to manage it.
While you’re probably right overall, there are many good reasons to use k8s. The api provides all sorts of benefits. Kubectl, k9s, and other operational UIs . Good deployment models and tools like argo. Loads of helm charts that are (theoretically) ready to use.
No, those things aren’t free. There’s a lot of overhead to running k8s.
I run k3s and all my stuff runs in it no need to deal with docker anymore.
I’m not very familiar with kubernetes or k3s but I thought it was a way to manage docker containers. Is that not the case? I’m considering deploying a k3s cluster in my proxmox environment to test it out.
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You can use kubernetes on any OCI container deployment.
So if you don’t want/need to install the docker program, you can go with containerd.
Kubernetes is abbreviated K8s (because there’s 8 letters between the “k” and the “s”. K3s is a “lite” version. Generally speaking, kubernetes manages your containers. You basicaly tell K8s what the state should be and it does what it needs to do to get the environment as you’ve declared. It’ll check and start or restart services, start containers on a node that can run them (like ensuring enough RAM is available). There’s a lot more, but that’s the general idea.
Could you list some of your “stuffs” that you run on your k3s? I’m curious.
Oh it is not that much, I run adguard DNS with adblocking, searxng as my search engine, vaultwarden as my password manager. All combined with Argo CD as GitOps engine, nginx ingress with cert-manager for lets encrypt certificates, longhorn as storage layer and metallb as loadbalancer solution. I am planning to completely replace my current setup (which is an old sandy bridge powered HP microserver) with a turing pi 2 clusterboard with 4 RPi4 CMs as soon as they get cheaper.
Wow you’re self-hosting a password manager! Don’t you feel scared if something went wrong?
I’m also running Adguard as my DNS-level adblocker on my Pi 3. Feels way more content than Pihole.
How did you write your templates? Did you use Kompose to translate from Docker compose files, or did you write them from scratch?
I manage like 200 servers in Google cloud k8s but I don’t think I’d do that for home use. The core purpose is to manage multiple servers and assign processes between them, auto scaling, cluster internal network - running docker containers for single instance apps for personal use doesn’t require this kind of complexity
My NAS software has a docker thing just built into it. I can upload or specify a package and it just runs it on the local hardware. If you have a Linux shell, I guess all you really have to do is run
dockerdto start the daemon, make sure your network config allows connections, and upload your docker containers to it for runningMy thinking is the same, I see lots of k8s mentions on here and from coworkers at home and all I use is docker and VMs because I don’t want all that complexity I have to deal with at work.
Kubernetes is great if you run lots of services and/or already use kubernetes at work. I use it all the time and I’ve learned a lot on my personal cluster that I’ve taken to work to improve their systems. If you’re used to managing infra already then it’s not that much more work, and it’s great to be able to shutdown a server for maintenance and not have to worry about more than a brief blip on your home services.
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.
Kubernetes is awesome for self hosting, but tbh is superpower isn’t multi-node/scalability/clustering shenanigans, it’s that because every bit of configuration is just an object in the API, you can really easily version control everything - charts and config in git, tools like Helm make applying changes super easy, use Renovate to do automatic updates, use your CI tool of choice to deploy on commit, leverage your hobby into a DevOps role, profit
Seems a bit overkill for a personal use selfhosting set-up.
Personally, I don’t need anything that requires multiple replicas and loadbalencers.
Do people who have homelabs actually need them? Or is it just for learning?
I find mine useful as both a learning process and as a thing need. I don’t like using cloud services where possible so I can set things up to replace having to rely on those such as next loud for storage, plex and some *arr servers for media etc. And I think once you put the hardware and power costs vs what I’d pay for all the subs (particularly cloud storage costs) it comes out cheaper at least with hardware I’m using.
Yes, those are all great uses of it. But could all still be achieved with docker containers running on some machines at home, right?
Have you ever had a situation where features provided by kubernetes (like replicas, load balancers, etc) came in handy?
I’m not criticizing, I’m genuinely curious if there’s a use-case for kubernetes for personal self-hosting (besides learning).
I was a big proponent of k3s in the homelab, but I’m starting to think otherwise these days. I still expel choice words towards Docker’s networking, but it starts becoming more of a philosophical issue with what the company is doing and whoever decided this kind of networking is nice.
Is the networking on Podman any better? I understand using k8s at home to learn, but what if you don’t care about learning? I have never seen a point to k8s in homelabs other than in home-datacentres, and I’m starting to veer away from k3s too, since I don’t need extreme HA over 3 machines for my services (I would have used Proxmox if I wanted that).
Yeah, could someone give me a primer on how Podman is better than Docker? I’m adamant that I don’t want to use anything with the name “Docker” in my lab.
Not sure if it’s exactly what you’re looking for, but here’s a “primer” on Podman for Docker users: https://lemmy.world/post/213870
Thank you!
A lot of people thought this was the case for VMs and docker as well, and now it seems to be the norm.
A lot of people thought this was the case for VMs and docker as well, and now it seems to be the norm.
Yes, but docker does provide features that are useful at the level of a hobbyist self-hosting a few services for personal use (e.g. reproducibility). I like using docker and ansible to set up my systems, as I can painlessly reproduce everything or migrate to a different VPS in a few minutes.
But kubernetes seems overkill. None of my services have enough traffic to justify replicas, I’m the only user.
Besides learning (which is a valid reason), I don’t see why one would bother setting it up at home. Unless there’s a very specific use-case I’m missing.
For me, I find that I learn more effectively when I have a goal. Sure, it’s great to follow somebody’s “Hello World” web site tutorial, but the real learning comes when I start to extend it to include CI/CD for example.
As far as a use case, I’d say that learning IS the use case.
Went swarm instead. I dont need a department of k8s consultants.
The Lemmy instance I’m speaking from right now is running in my k8s cluster.
Acronyms, initialisms, abbreviations, contractions, and other phrases which expand to something larger, that I’ve seen in this thread:
Fewer Letters More Letters DNS Domain Name Service/System Git Popular version control system, primarily for code HA Home Assistant automation software ~ High Availability HTTP Hypertext Transfer Protocol, the Web LXC Linux Containers NAS Network-Attached Storage SSD Solid State Drive mass storage SSH Secure Shell for remote terminal access VPN Virtual Private Network VPS Virtual Private Server (opposed to shared hosting) k8s Kubernetes container management package nginx Popular HTTP server
11 acronyms in this thread; the most compressed thread commented on today has 11 acronyms.
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HA is high availability. Home Assistant is usually shortened to HASS.
It does list that as another possible meaning, if I’m reading the table correctly
Good catch! I didn’t notice that.
I am insane and use bare bone LXC.
Stupid ramblings you can probably ignore:
spoiler
Usually though it’s because I run most stuff bare metal anyway so LXC is for temporary or random cases where I need a weird dependency or I want to run a niche service.
Only use docker for when I actually want faster setup like docker-osx which does all the vm stuff for running a virtual Mac for you.
I don’t really mind docker, but for homelab I just find myself rewriting dockerfile anytime I want to change something which I don’t really need to do if I’m not publishing it or even reusing it.
Kubernates is really more effective for actual load services, which you never need in homelab lol. It’s great to use to learn k8s cluster, but the resources get eaten fast.
I like the concept, but hate the configuration schema and tooling which is all needlessly obtuse (eg. helm)
Helm is one of the reasons I became interested in Kubernetes. I really like the idea of a package where all I have to do is provide my preferences in a values file. Before swarm was mature, I was managing my containers with complicated shell scripts to bring stuff up in the right order and it became fragile and unmaintainable.
Nomad all the way. K8s is so bloated. Docker swarm can only do docker. Nomad can do basically anything.
It’s a damn shame it’s going not free open source, I Just switched my lab over to nomad and consul last year and it has been incredibly smooth sailing.
Nomad is a breath of fresh air after working with k8s professionally.
Don’t get me wrong, love k8s, but it’s a bit much (until you need it)
I’ve been reading into k3s out of curiosity, which as I understand is supposed to be one of the simpler ones, and even as someone who works as a developer and maintains a small homelab, it just makes me feel utterly clueless lol. Which is to say, I’ll definitely be giving Nomad a good look.
Oh and if you do happen to have any other more newbie friendly suggestions, I’d love to hear about them!
There are dozens of us!
Seriously though I changed to nomad/consul/gluster and it’s been wonderful. I still have some other things running on my nas software like Jellyfin and audiobookshelf, but that’s just for performance and simplicity.
I was a bit put off by Hashicorps license change, but I don’t think I’m changing back to k3s anytime soon. Nomad is just so nice and easy.
I run a 2 node k3s cluster. There are a few small advantages over docker swarm, built-in network policies to lock down my VPN/Torrent pod being the main one.
Other than that writing kubernetes yaml files is a lot more verbose than docker-compose. Helm does make it bearable, though.
Due to real-life my migration to the cluster is real slow, but the goal is to move all my services over.
It’s not “better” than compose but I like it and it’s nice to have worked with it.
I love kubernetes. At the start of the year I installed k3s von my VPS and moved over all my services. It was a great learning opportunity that also helped immensely for my job.
It works just as well as my old docker compose setup, and I love how everything is contained in one place in the manifests. I don’t need to log in to the server and issue docker commands anymore (or write scripts / CI stages that do so for me).
Are most of your services just a single pod? Or do you actually have them scaled? How do you then handle non-cloud-native software?
