kubeplus VS kind

We went through this migration/upgrade in our KubePlus project (https://github.com/cloud-ark/kubeplus). It has an embedded webhook in it, fyi.

You might want to check out - KubePlus (https://github.com/cloud-ark/kubeplus), which has already been referenced in the thread and is exactly designed for building managed application services. I am the originator and core contributor to this project. KubePlus is a Kubernetes Operator that takes an application Helm chart and represents it as a Kubernetes API (CRD) on the cluster. This API allows you to create instances of the application in separate namespaces automatically ensuring a secure perimeter around each instance using NetworkPolicy, Resource Quota, and RBAC. These soft multi-tenancy measures are already mentioned in the thread along with the namespace. KubePlus has automated all of them for you under an API. This API not only allows the creation of the application instances but also supports day-2 operations such as monitoring, troubleshooting, and upgrades to simplify the end-to-end functioning of any managed application service. We are currently seeing interest from teams that want to create managed services for different types of containerized applications, including open-source platforms such as WordPress, Moodle, Ozone/OpenMRS, AI/ML workloads, etc. KubePlus has been tested successfully with all (90+) Bitnami Helm charts. For anyone who wants to deliver a managed application with minimal / no Kubernetes access to their customers, KubePlus can help by accelerating the implementation of namespace-based multi-tenancy on Kubernetes. With the ability to set NetworkPolicy and Resource Quota per application instance, the blast radius is restricted, if something goes wrong in an application instance. KubePlus does not need admin permissions on your cluster. This makes it possible to use KubePlus to manage your application instances on your customer's cluster as well.

We have an FAQ about Operators here: https://github.com/cloud-ark/kubeplus/blob/master/Operator-F...

It should be helpful if you are new to the Operator concept.

Operators are generally useful for handling domain-specific actions - for example, performing database backups, installing plugins on Moodle/Wordpress, etc. If you are looking for application deployment then a Helm chart should be sufficient.

If you are currently delivering your SaaS as a separate instance of your application per customer, you might want to check out our open-source project KubePlus - https://github.com/cloud-ark/kubeplus

A more commerical offering is from Cloudark who have designed a specific solution for operating your Helm application as a SaaS offering. I have never used it (ArgoCD being my poison) but you might find it fits your usecase better

As part of your data platform are you planning to create a separate instance of the database for your end customer? If so, you might find our KubePlus Operator helpful. Check it out here: https://github.com/cloud-ark/kubeplus

We have been helping organizations build such multi-instance multi-tenant cloud-native applications. We start with an application Helm chart and create separate release of it per customer/user of that organization. We have an open source Kubernetes Operator that aids in this: https://github.com/cloud-ark/kubeplus

You might also want to checkout Operator guidelines and Operator FAQ: - Operator Maturity Model guidelines: https://github.com/cloud-ark/kubeplus/blob/master/Guidelines.md

The project that is getting some traction recently is our KubePlus Operator that delivers Helm charts as-a-service: https://github.com/cloud-ark/kubeplus

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