vcluster VS kubernetes

Kubernetes? You mean the container orchestration system where they forgot to add Multi-tenancy? And no namespaces are not Multi-tenancy...

https://www.vcluster.com/

Whats the difference between this and vcluster (https://github.com/loft-sh/vcluster)?

Yep, as we see it they compliment each other quite well. DevPod takes your workspace to the cloud and DevSpace let's you develop against your Kubernetes cluster - potentially the same one you used to start your workspace.

Internally we use both in our development setup, spinning up remote workspaces using DevPod, installing DevSpace and kind into the devcontainer, then using DevSpace to develop against the cluster. See the vcluster setup[1] as an example

[1]https://github.com/loft-sh/vcluster/tree/main/.devcontainer

The tenants are internal dev teams so yeah maybe not. I was considering multi-tenanting different environments isolated at the kube layer with vCluster and have the vCluster pods running in Kata containers giving maximum isolation but still having a single management cluster. Ideally also avoiding the need to buy a second set of hardware for a dev environment

Vcluster

Looks interesting. How does this solution compare to vcluster?

sounds like the best option for you , is a tool called VCluster by loft ( https://www.vcluster.com/) , this way you can install as many k8s cluster as you want in the same k8s host cluster , those cluster share workers nodes and networking, but each has a separated "api server" , so it looks like you have a dedicated cluster with their own namespaces and tools . take a look at the docs to get a better understanding and how they work.

We're about to run a PoC with vcluster for isolated sandboxes, this might be relevant to you too

I think namespaces, RBAC and network policies are sufficient to partition users from the same organisation. I would investigate the use of vcluster ig you want to give your users even more isolation and capability (such as installing CRDs)

Depends on the use case. Namespaces provides soft isolation (so it means they share same Apiserver, PV's and global resources such as CRD's), but can be restricted with network policies. So it means, there's still potential in breaking other namespaces if you change PV's or CRD's which are used by other namespaces. Multi-Cluster solution can provide full isolation, but its also really expensive in resource consumption and maintenance/management effort. If namespaced-isolation isnt enough for your use case, you can consider vclusters (https://www.vcluster.com/)

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.

If you do kubectl explain deployment than (surprise!) you'll get a description for extensions/v1beta1. Because kubectl explain works the same way, just like kubectl get:

Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).

In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.

The single most important development in hosting since the invention of EC2 is defined by its own 3-letter acronym: k8s. Kubernetes has won the “container orchestrator” space, becoming the default way that teams across industries are managing their compute nodes and scheduling their workloads, from data pipelines to web services.