kind VS skaffold

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

A nice middle ground is using a tool like Google's Skaffold, which provides "Bazel-like" capabilities for composing Docker images and tagging them based on a number of strategies, including file manifests. In my case, I also use build args to explicitly set versions of external dependencies.

While I am in a Typescript environment with this setup at the moment, my personal experience that Skaffold with Docker has a lighter implementation and maintenance overhead than Bazel. (You also get the added benefit of easy deployment and automatic rebuilds.)

I quite liked using Bazel in a small Golang monorepo, but I ran into pain when trying to do things like include third-party pre-compiled binaries in the Docker builds, because of the unusual build rules convention. The advantage of Skaffold is it provides a thin build/tag/deploy/verify layer over Docker and other container types. Might be worth a look!

Kudos to the Google team building it! https://skaffold.dev

To get a similar experience of preevy up, first we’ll need to split the build and deploy using process or alternatively employ tools that orchestrate build-tag-push-update-sync flow like Skaffold/Tilt.

We will be using docker and microk8s from Canonical. For running our software during development, we will be using skaffold which is a great tool developed by Google.

To add more context, if you are developing containers in a local dev environment, the minimum you should have is the Google Cloud SDK and Skaffold. The SDK will allow you to programmatically interact with Googleapis e.g. auth, services, resources. Skaffold will allow you to build and deploy to the cloud similar to working with a local dev environment.

I have used both Skaffold and Devspace. I prefer the latter.

I wonder if it has some overlap with https://skaffold.dev/.

K3d and Skaffold for local development

skaffold.dev - build in k8s - no more asking for the database password. All the plumbing to the backend is just done so it's easier for them to test and demo any branch