kind VS crossplane

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

did anyone adopt in production https://crossplane.io ?

- https://github.com/crossplane/crossplane/blob/master/design/one-pager-composition-environment.md

In the overall scheme of things , look at services like backstage.io , crossplane.io and opslevel.com to get ideas. This is not necessarily an endorsement of the services. If all you want is to handle cloud resources and that's it, Terraform can be enough with what ever flavor of web technologies you and your team are comfortable with and can support it along the way. Doesn't take much to create a js based website to collect data from a form, or use other means to collecting data as long as its recorded and transparent for accountability.

XRs are written in a fully declarative manner. And when I am building my XR from underlying managed resources provided by some crossplane provider I need to parametrize resources, use conditionals and create arrays of resuorces The issues of declarativeness in the world of automation are well known- we typically resort to some form of templating and we invent some imperative expressions into that templating language/format. This is currently not very well supported with Crossplane however Crossplane team realizes this issue and they are conteptualizing solution here

I have an idea for a project that would interface with Crossplane. The project has some code that would save tons of time if I could use it directly in my project, but it is located in the internal directory. I can't import the modules directly, but the project is open sourced under an Apache 2.0 license, so the code itself is available for use under that license.

There are always new projects like crossplane that sit on top on architecture systems like terraform, vagrant. The pressure to abstract away any sort of resources is mounting, companies can save a lot by for example by alt hosting S3 endpoints. The train is going the direction not to tie anything to a specific platform implementation if its not a must. Most of the companies I work with use AWS as a hosting provider, but Microsoft for github and related CI matters. As I learned, AWS quality is very dependent on location, eu-central-1 is dead stable for our use cases serving about millions requests a day.

Practically, you'll be replacing stock k8s resources (deployments) with custom ones like Argo Rollouts with Keda autoscaling, so you have to plan the respective Gitops CD pipeline (fluxcd/argocd with some crossplane), as well.