k0s VS kind

I am myself studying it and going through the official documentation and toying with k8s flavors like kind, k3s and k0s.

There's a whole community of hobbyists building Raspberry Pi clusters, porting things to work on various Arm processors, exploring and contributing to minimalist distros like k0s and microk8s, etc.

root@localhost:~# curl -sSLf https://get.k0s.sh | sudo sh Downloading k0s from URL: https://github.com/k0sproject/k0s/releases/download/v1.25.4+k0s.0/k0s-v1.25.4+k0s.0-amd64 k0s is now executable in /usr/local/bin root@localhost:~# k0s install controller --single root@localhost:~# k0s start root@localhost:~# k0s status Version: v1.25.4+k0s.0 Process ID: 1064 Role: controller Workloads: true SingleNode: true Kube-api probing successful: true Kube-api probing last error: root@localhost:~# k0s kubectl cluster-info Kubernetes control plane is running at https://localhost:6443 CoreDNS is running at https://localhost:6443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'. 443/TCP 97s root@localhost:~# k0s kubectl get nodes -o wide NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME localhost Ready control-plane 100s v1.25.4+k0s 172.105.131.23 Ubuntu 22.04.1 LTS 5.15.0-47-generic containerd://1.6.9 root@localhost:~# curl -LO https://storage.googleapis.com/kubernetes-release/release/v1.25.4/bin/linux/amd64/kubectl && chmod +x kubectl && mv kubectl /usr/bin/ % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 42.9M 100 42.9M 0 0 75.2M 0 --:--:-- --:--:-- --:--:-- 75.3M root@localhost:~# k0s kubeconfig admin > ~/.kube/config root@localhost:~# type kubectl kubectl is hashed (/usr/bin/kubectl) root@localhost:~# kubectl get po,svc -A NAMESPACE NAME READY STATUS RESTARTS AGE kube-system pod/kube-proxy-clxh7 1/1 Running 0 3m56s kube-system pod/kube-router-88x25 1/1 Running 0 3m56s kube-system pod/coredns-5d5b5b96f9-4xzsl 1/1 Running 0 4m3s kube-system pod/metrics-server-69d9d66ff8-fxrt7 1/1 Running 0 4m2s NAMESPACE NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE default service/kubernetes ClusterIP 10.96.0.1 443/TCP 4m20s kube-system service/kube-dns ClusterIP 10.96.0.10 53/UDP,53/TCP,9153/TCP 4m8s kube-system service/metrics-server ClusterIP 10.98.18.100 443/TCP 4m2s

I use k0s btw ,and it is fantastic.

Here is link number 1 - Previous text "k0s"

So for example, in my own personal infra repos and for projects I do, Make orchestrates Pulumi, dnscontrol (Holy shit is that tool underrated), ansible, k0s/k0sctl (I run that distro), and all the kubernetes stuff.

I wasn’t able to run Kubernetes in NAS last time I tried it. https://github.com/k0sproject/k0s/issues/1184. As for public access you don’t want to do it for security reasons and instead rely on vpn. Tailscale and ZeroTier are easy to setup.

I prefer k0s, https://k0sproject.io/ .

actually that is not really true - i strongly urge you to try out http://k3s.io/ or https://k0sproject.io/

these are full-fledged, certified k8s distributions that run on raspberry pi as well as all the way in production.

https://www.youtube.com/results?search_query=raspberry+pi+k3...

To get started, you'll need to install clusteradm and kubectl and start up three Kubernetes clusters. To simplify cluster administration, this article starts up three kind clusters with the following names and purposes:

Kind: is a tool for running local Kubernetes clusters using Docker container "nodes." It was primarily designed for testing Kubernetes itself but can also be used for local development or continuous integration.

Fortunately, just as projects like kind and Minikube enable developers to spin up a local Kubernetes environment in no time, CRC, also known as OpenShift Local and a recursive acronym for "CRC - Runs Containers", offers developers a local OpenShift environment by means of a pre-configured VM similar to how Minikube works under the hood.

I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.

Features compared to https://kind.sigs.k8s.io/

Kind allows you to run a Kubernetes cluster inside Docker. This is incredibly useful for developing Helm charts, Operators, or even just testing out different k8s features in a safe way.

Check out KinD

If you're just messing around, just use kind (https://kind.sigs.k8s.io) or minikube if you want VMs (https://minikube.sigs.k8s.io). Both work on ARM-based platforms.

You can also use k3s; it's hella easy to get started with and it works great.

We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.

yes I know there is lens, but it does not allow me to see logs of multiple pods at same time and what is even more important it is not friendly for ephemeral clusters - in my case with help of kind I am recreating whole cluster each time from scratch