kubeone VS microk8s

I would suggest KubeOne by Kubermatic, this works great on Hetzner Cloud and comes also bundled with machine deployments where you are able to autoscaler your worker nodes. Beside that it also installs additional tools like the Hetzner Cloud CSI drive and the Cloud Controller Manager. You can find at https://github.com/kubermatic/kubeone

Kubeone on Hetzner is honestly one of the smoothest non-managed experiences I've ever had with Kubernetes - better than some managed ones. Includes all of the things Hetzner already provides for Kubernetes (so I'm sure they're working on their own) - internal networking support, load balancers, volumes. And you scale worker nodes with a CRD too.

https://github.com/kubermatic/kubeone/tree/main/examples/ter...

I have a GKE cluster running and two self-setup using https://github.com/kubermatic/kubeone for over a year now. Since no one named kubeone here, I'd like to give them a shout out for their great work. Actually the clusters are managed by kubeone and running them in Hetzner cloud even costs a 10th of GKE.

kubeone currently has the best out of the box experience on Hetzner imo.

In that time thought I migrated to Hetzner Cloud and deployed a cluster using https://github.com/kubermatic/kubeone

kubermatic kubeone is open source and it can do what you need quite easily.

If you want hands-on practice you should have a running Kubernetes cluster (I used MicroK8s for this tutorial) and Helm (see how to install on Installing Helm tutorial). It is important that you understand the basics of these tools to fully understand.

And install microk8s:

MicroK8s is a lightweight, batteries included Kubernetes distribution by Canonical designed for running edge workloads which also happens to be developer-friendly and a great choice for building your own homelab. The following lab covers how to install and run MicroK8s on your own edge node running Ubuntu 22.04 LTS, deploy the NGINX web service and exposing your NGINX website to the Internet with SSL/TLS enabled using AWS resources included within the Free Tier.

One quick and easy win I can recommend, is microk8s.

I had the same problem (and there's a github issue about this: https://github.com/canonical/microk8s/issues/2186). I swapped to k3s and the usage was half of what microk8s used.

microk8s currently has a showstopping issue that makes it guaranteed to have an irrecoverable failure in HA mode. see https://github.com/canonical/microk8s/issues/3227

k0s is better but also has a lot of bugs. it's the closest to vanilla kubernetes among all the distributions.

> like the simplest GPU support

linux users should be ready to install the nvidia device plugin. if they can't do that, they're never going to succeed in running a gpu accelerated application on their cluster anyway.

> like bootstrapping

in my experience, writing all the bootstrap scripts is painful. but now that there's chatgpt, so much of the drudgery as gone away.

MicroK8S to spin up a Kubernetes cluster

They now power my microk8s/x86 cluster (in addition to my 8-node Raspberry Pi4 ARM64 microk8s cluster), microceph cluster and my LXD cluster, and all are configured with WOL, so I can bring up the cluster from any machine in the homelab, on demand.