devspace-plugin-loft VS k3s

I'm biased but I do think what you're describing is a good use case for Kubernetes. I work for Loft Labs, we're the company that created vcluster. We do have a commercial product called Loft that lets you manage vclusters and offer them self-service to developers. If you want to get more info on that, the web site is loft.sh.

There are some products available, for example Loft who open sourced vcluster

We run on EKS and use https://loft.sh/ to deploy development environments. The engineer runs the single service locally that they want to modify. Any other services or databases that service connects to run remotely in our Development EKS cluster using Loft and port forwards to the engineers local environment.

Lastly, one day my employer will let my run Loft so that I can provide on-demand ephemeral k8s clusters to my dev + test teams.

Have a look at https://github.com/loft-sh/kiosk and maybe the paid version https://loft.sh/

How many friends? I would recommend evaluating Loft which is free for up to 3 users.

Automate the setup of new k8s environments, ideally they should be ephemeral, disposed regularly and rebuilt by the devs themselves, on demand. This will also keep costs in check, devs don't work 24/7 so why should their cloud infrastructure? A tool worth checking would be Loft

Loft solves this + much more. There are cost-saving features too, so it might actually pay for itself. Don't hesitate to book a demo.

Loft.sh provides self-serve Kubernetes solutions for cost optimization, CI/CD, policy enforcement, user management, collaboration, and more. It helps save on Kubernetes costs by using quotas and space constraints which helps while sharing your clusters among multiple users and teams. Auto delete for idle namespaces and sleep mode for idle workloads also saves costs.

In this demo, we will be using k3d a lightweight wrapper to run k3s (Rancher Lab’s minimal Kubernetes distribution) in docker, to create 4 separate clusters named control-plane, cluster-1, cluster-2, and cluster-3 respectively.

To run the demo locally, we recommend k3d a lightweight wrapper to run k3s (Rancher Lab’s minimal Kubernetes distribution) in docker.

I've been messing around with k8s (k3s) lately, and got to the "issue" of downtime/inconsistencies caused by one of multiple workers being down, who had pods running on them. I found a couple useful parameters here that helped me reduce the time needed to redeploy the old pods on other nodes, as well as stop sending requests to the NotReady node. But that got me thinking, how long should k8s wait before doing these things? Or is there perhaps a better option for increasing avaliability?

Local Kubernetes clusters are clusters that are running on the individual computer of the developer. There are many tools that provide such an environment, such as Minikube, microk8s, k3s, or kind. While they are not all the same, their use as a development environment is quite comparable.

Since the developer is the only one who has to access this cluster for development, local clusters can be a feasible solution for this purpose. Over time, several solutions have emerged that are particularly made for running Kubernetes in local environments. The most important ones are Kubernetes in Docker (kind), MicroK8s, minikube and k3s. For a comparison of these local Kubernetes options, you can look at this post.

With local Kubernetes environments such as minikube or k3s, developers can create their own Kubernetes clusters on their local computers. This often leads to developers struggling with the management and setup of these pared-down Kubernetes technologies that are also not completely realistic compared to “real-world”, cloud-based environments. The upside of this approach is that the developers have full control over their environment and can independently create it whenever they need it.

K3d - a lightweight wrapper to run k3s in docker.