azure-k3s-cluster VS kind

If anyone wants a ready-to-go Azure template to play around, here you go:

https://github.com/rcarmo/azure-k3s-cluster

(I tweak this every now and then since I both used it as a training sample for my customers/peers and as a way to run my own batch processes as cheap as possible)

The runtime controller is uwsgi, which acts as supervisor for all processes of an app _or_ embeds the right interpreter-it's pretty much perfect for that, as it also has a cron scheduler and an on-demand, fire-up-an-interpreter-upon-request mode.

As to the k3s stuff, it's all here: https://github.com/rcarmo/azure-k3s-cluster. I update this from time to time as I occasionally nuke the entire cluster and rebuild it (I use AKS for non-hobby workloads, but a single master is just fine for most of my stuff).

Have you tried https://kind.sigs.k8s.io/? If so, how does it compare to k3s for testing?

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.