k3s VS helm

Opinionated meaning it picks, install, patches your CNI/Ingress/Load Balancer/DNS Server/Metrics Server/Monitoring Setup.

k3s is probably most well known as it ships with bunch of preinstall software: https://github.com/k3s-io/k3s so you can just start throwing yaml files at cluster and handling workloads. It's what I use for my homelab.

Paid things I've heard of include OpenStack and SideroLabs. Haven't used personally by SRE coworkers say good things about them.

For self-hosting I've found https://k3s.io to be really good from the SUSE people. Works on basically any Linux distro and makes self-hosting k8s not miserable.

Yes it’s going to depend on which k8s distribution you’re using. We have work in-progress for k3s to natively support nix-snapshotter: https://github.com/k3s-io/k3s/pull/9319

For other distributions, nix-snapshotter works with official containerd releases so it’s just a matter of toml configuration and a systemd unit for nix-snapshotter.

We run Kubernetes outside of NixOS, but yes the NixOS modules provided by the nix-snapshotter certainly make it simple.

K3S: is a lightweight distribution of Kubernetes that is designed for resource-constrained environments. It is an excellent option for running Kubernetes on a virtual machine or cloud server.

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.

Kubernetes - k3s distribution

I’ve created a local cluster with K3S and installing Windmill could not be simpler with just one chart to configure, which already has sane defaults to get started. For this demo we will also configure workers to passthrough environment variables to our scripts so that they have access to the Kubernetes API server for later.

You should be familiar with Kubernetes and have set up a Kubernetes cluster. I recommend k3s.

Applying Kubernetes manifests individually is problematic because files can get overlooked. Packaging your applications as Helm charts lets you version your manifests and easily repeat deployments into different environments. Helm tracks the state of each deployment as a "release" in your cluster.

helm

Explanation here: https://github.com/helm/helm/issues/12681#issuecomment-19593...

Looks like it's a bug in Helm, but actually isn't Helm's fault, the issue was introduced by Fedora Linux.

Helm (Get from here https://helm.sh/)

It’s also well understood that having a k8s cluster is not enough to make developers able to host their services - you need a devops team to work with them, using tools like delivery pipelines, Helm, kustomize, infra as code, service mesh, ingress, secrets management, key management - the list goes on! Developer Portals like Backstage, Port and Cortex have started to emerge to help manage some of this complexity.

Kubernetes orchestrates deployments and manages resources through yaml configuration files. While Kubernetes supports a wide array of resources and configurations, our aim in this tutorial is to maintain simplicity. For the sake of clarity and ease of understanding, we will use yaml configurations with hardcoded values. This method simplifies the learning process but isn’t ideal for production environments due to the need for manual updates with each new deployment. Although there are methods to streamline and automate this process, such as using Helm charts or bash scripts, we’ll not delve into those techniques to keep the tutorial manageable and avoid fatigue — you might be quite tired by that point!

Helm is a package manager that automates Kubernetes applications' creation, packaging, configuration, and deployment by combining your configuration files into a single reusable package. This eliminates the requirement to create the mentioned Kubernetes resources by ourselves since they have been implemented within the Helm chart. All we need to do is configure it as needed to match our requirements. From the public Helm chart repository, we can get the charts for common software packages like Consul, Jenkins SonarQube, etc. We can also create our own Helm charts for our custom applications so that we don’t need to repeat ourselves and simplify deployments.

We can search for charts https://helm.sh/ . Charts can be pulled(downloaded) and optionally unpacked(untar).

Generally I felt as if I was diving in the deepest of waters without the correct equipement and that was horrifying. Unfortunately to me, I had to dive even deeper before getting equiped with tools like ArgoCD, and k8slens. I had to start working with... HELM.

Within the architecture of Cyclops, a central component is the Helm engine. Helm is very popular within the Kubernetes community; chances are you have already run into it. The popularity of Helm plays to Cyclops's strength because of its straightforward integration.