talos VS kind

Super cool. I always enjoy reading about systems that challenge, well, "ossified" assumptions. An OS not providing a shell, for example? Madness! ... or is it genius, if the OS has a specific purpose...? It's thought-provoking, if nothing else.

I'm a bit skeptical of parts. For instance, the "init" binary being less than 400 lines of golang - wow! And sure, main.go [1] is less than 400 lines and very readable. Then you squint at the list of imported packages, or look to the left at the directory list and realize main.go isn't nearly the entire init binary.

That `talosctl list` invocation [2] didn't escape my notice either. Sure, the base OS may have only a handful of binaries - how many of those traditional utilities have been stuffed into the API server? Not that I disagree with the approach! I think every company eventually replaces direct shell access with a daemon like this. It's just that "binary footprint" can get a bit funny if you have a really sophisticated API server sitting somewhere.

[1]: https://github.com/siderolabs/talos/blob/main/internal/app/m...

[2]: https://www.talos.dev/v1.6/reference/cli/#talosctl-list

Where `kube.cue` sets reasonable defaults (e.g. image is /). The "cluster" runs on a mini PC in my basement, and I have a small Digital Ocean VM with a static IP acting as an ingress (networking via Tailscale). Backups to cloud storage with restic, alerting/monitoring with Prometheus/Grafana, Caddy/Tailscale for local ingress.

[1] https://www.talos.dev/

[2] https://cuelang.org/

Looks somewhat similar to the talos Linux project[1]

[1] https://www.talos.dev/

Talos Linux basically implements their entire userspace in Go and its similar to BottleRocketOS, because it is designed to host Kubernetes.

https://www.talos.dev/

You might be surprised to find that Talos os (linux distro for kubernetes) mostly uses Go: https://github.com/siderolabs/talos

I've been using a 3 nuc (actually Ryzen devices) k3s on SuSE MicroOS https://microos.opensuse.org/ for my homelab for a while, and I really like it. They made some really nice decisions on which parts of k8s to trim down and which Networking / LB / Ingress to use.

The option to use sqlite in place of etcd on an even lighter single node setup makes it super interesting for even lighter weight homelab container environment setups.

I even use it with Longhorn https://longhorn.io/ for shared block storage on the mini cluster.

If anyone uses it with MicroOS, just make sure you switch to kured https://kured.dev/ for the transactional-updates reboot method.

I'd love to compare it against Talos https://www.talos.dev/ but their lack of support for a persistent storage partition (only separate storage device) really hurts most small home / office usage I'd want to try.

If you’re interested in something not AWS check out Talos https://www.talos.dev/

It’s been around longer than Bottlerocket

Can't talk about work, but my homelab is Azure and Oracle managed k8s (AKS/OKE), with onprem Talos soon (Turing Pi 2). My Flux monorepo has the details. OKE performs noticably worse (update cycle, features, control plane performance), but it provides 4 ARM cores and 24GB RAM free so I can't complain

Talos

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