Kubernetes adds a lot of complexity. In return, it allows various teams in your company to work mostly independently, so that your software stack can mirror your org chart better. It trades latency for scalability (adds network calls to things that could have been local function calls). If your “home lab” isn’t serving millions of users, you don’t need Kubernetes to run it.

That said, you might be using your home lab partly as practice for a job at a large company where the tradeoffs of Kubernetes make sense (or at least someone thought they made sense and started using it, which is more common). That means using it at home can provide valuable self training, since you can screw around and not take down the production cluster for anyone other than yourself.

No, it is not worth it. The benefits of k8s really kicks in at scale, which none of us really reach. Most of us would be well served with proxmox or similar.

But then again, if we were all reasonable people most of us wouldn’t have a homelab either.

Anyways, I run K3S. It’s overkill, but that’s fine. But god, helm. Most of the problems I’ve had with my kubernetes setup has been half baked, abandonware helm charts not supported by the project in question. I’m going through a process of removing every instance of helm where the chart isn’t first party created.

K8s can allow you to build a reliable and mostly self sufficient suite of tools for your home lab. There is a lot of upfront cost to get there. However, I’d argue k8s isn’t actually all that more complex than running individual docker containers. In both cases you need to have an understanding of networking, containers, proxies, databases, and declarative config of some form or another. K8s just provides primitives that make it really easy to build more complex container projects up declaratively. It doesn’t mean it has to be complex. I run 5 or 6 different services with individual backing Postgres DBs. I source the containers from docker hub just like you would in docker. Certbot will auto deploy certs for any service I set up this way. HA proxy will auto add domains and upstreams for them too. When I want to setup a new service I often just copy and paste an existing service manifest and do a find and replace with a new service name. At that point I can usually just apply the manifest and wait 5 min. My service will be up, available on the internet, and already have SSL certs.

I’ll add, if you have really complex projects with tons of micro services you can deploy a helm chart for that in two commands. Even with minimal or no knowledge about how it should be setup.

Do you have multiple physical machines and want to turn them off with full uptime? If not, i don’t think it’s worth it. It’s a really amazing system and if you want to learn, go for it, but it’s hard to justify running on just one server

Can someone link to that Adolf Hitler rant about containers running in containers running in a "lightweight " VM video?

Is kubernetes really worth it for the avarage homelab user?

No

K8s is not worth it for the average homelab user. But the whole point of self hosted to do way to complicated stuff for fun so…

10+ years at Google as an SRE. While borg =!= k8s, I’ve seen my fair share of platforms come and go. The trend seems to reward shifts towards declarative automation rather than imperative orchestration models. In the programming world, you’ll hear the term idempotent, similar idea. There is no substitute or wrapper that can take imperative and make it declarative without tons of work. Ansible is imperative where if something goes wrong it is easiest to nuke then try again. K8s is the culmination of various imperative-based automation systems at Google, attempts at replacing them with declarative, then try again, then finally start afresh with an open-source version of borg.

Not many companies need the scale of Google, with thousands of engineers trying to modify production with hardened interfaces that force developers to write their applications in such an opinionated way (stateful applications must use StatefulSet, dynamic configuration should go into a ConfigMap, separate your command line arguments from the command being executed from the environment variables, LoadBalancers are distinct from and are an implementation detail of Services…).

But with the good foundation that k8s provides and imposes, you set yourself up for letting the infrastructure team not care about what is running on what hardware. They can focus on doing hardware, networking, disk swapouts… Ops can focus on service uptime, readiness+liveness probers, standardized monitoring/logging, traffic routing and rollouts. Devs can focus on writing code. These standards reduce the leakage that often happens between these 3 groups.

Taking declarative to the next level, you build CICD pipelines that can take your yaml files in a github repo and automatically push them. To the next level you want to account for importing templates and standard libraries, so you look to Kustomize till you realize that it doesn’t give you the building blocks you need. You then start to adopt more declarative models where the source code (both java and json/yaml config files) can be built and the artifacts of that build step are what are fed into k8s, making your github repo the source of truth. Then all production fiddling is done with PRs rather than clicking buttons in an imperative way on some UI.

The more you see automation tools, the more you realize that declarative offers a more robust interface that can be glued to other declarative systems, albiet adding yet another layer of abstraction. This complexity is often not streamlined enough for people on this subreddit, as well as for lots of people writing self-hosted apps. Helm is about as both streamlined and exhaustive as you’re going to get.

I agree with many here that learning k8s is best if you’re needing to learn it for your job, or you have hopes of getting into the DevOps field.

I’m a DevOps professional and adore Kubernetes. I have a CKAD cert and professional experience…

No

For my homelab, I’m putting most stuff at the Proxmox layer (eg Nextcloud, Kubernetes, Storage-NFS). I’m putting a few things in Kubernetes but at this point it’s just a testbed (eg Argocd). At some point I’ll put up a 2nd “production” K8s and run apps in there forever.

I’ve been doing setups with Ansible and a little Terraform and it’s great. I can build and tweak and rebuild really quickly without having to go in and tweak one little thing. It’s fantastic for my confidence the stack works exactly as I want it.

I plan to use podman at home since I just have one node and I don’t care about HA as much (what will I even do HA with? VMs?).

If you have multiple nodes for an HA setup, sure, go right ahead. It will be a massive learning curve though. But so are most things in life. I think everyone can learn a lot by running kubernetes (godly complex networking in my opinion).

K8s helps me a lot to understand what I don’t know but nothing more than that. You need tons of studying to know what is going on beyond the scope of k8s.

Not only k8s is solid overkill for the homelab but also most of self hosted services are not designed to be deployed in k8s pods. So it won’t just work.

In case you want to learn something through deploying k8s, it doesn’t help you much either. Learning networking is much better option instead.

Come hang out with us https://discord.gg/k8s-at-home

So here’s my take. I’m not a devops guy professionally. I started my homelab with docker. The problem was the number things I was hosting kept growing and I was worried of loading the machine. I had a few other machines lying around that I decided to pull into a k3s. I somehow love it. My entire home lab is now stored with IaC and lives in a GitHub with CI/CD. Any changes I make to the repo are automatically deployed to the cluster. If I need to Takedown a machine I don’t need to worry about loss of service. I also use velero for backups. If things go wrong a few commands and my entire cluster is fully restored from backups. Now I can easily agree that kubernetes is overkill for a homelab. But I feel it offers some convenience in terms of administration. For docker I still had to deploy everything by portainer which I hadn’t found a way to automate. Backup and restore was not fully automated. You could backup the data but you had to manually redeploy your apps and then restore data to it. At least this was what I could implement. With kubernetes everything is fully in code and controlled by the GitHub repo. Granted the learning curve is steep. Took me 3 months to fully port my system to k3s. Also for general apps check out https://bjw-s.github.io/helm-charts/docs/ You can use that chart to make a helm chart for any app that can be deployed via docker compose. So I just create my own helm charts for apps that only habe docker instructions and deploy it.

TLDR; learning curve is steep but there are a few gains in terms of IaC administration and ability to leverage multiple machines

I have maintained my web sites, mail servers, family cloud, home media center, backup solution and a few other services for over 20 years.

My configuration is quite stable, and I appreciate maintaining by hand, tight-knitted, the links between all services, so as to make it easier to make the configurations and services slowly evolve over time (migrating from sendmail to postfix, httpd to apache to ngnix, owncloud to nextcloud, cvs to git, etc).

I wouldn’t recommend the extra sophistication of containers and orchestration of services for this type of usage, which is very stable and meant to slowly evolve to stay current. Those extras layers are meant to serve fast-evolving environments with frequent updates, continuous delivery, and multiple maintainers. They’d be a burden for my usage.

However, if you plan to use your home server to learn and acquire new skills you want to put on your resume, then it’s definitely worth the effort.

Thanks all, for all the great feedback i got. I will definitely be investing more time to keep on learning Kubernetes, the more I read some of your comments the more ideas I’m having on my own use case in my home lab.