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OP here. There definitely is a place for running things on your local machine. Exactly as you say: one can get a great deal of consistency using VMs.

One of the benefits of moving away from Kubernetes, to a runner-based architecture , is that we can now seamlessly support cloud-based and local environments (https://www.gitpod.io/blog/introducing-gitpod-desktop).

What's really nice about this is that with this kind of integration there's very little difference in setting up a dev env in the cloud or locally. The behaviour and qualities of those environments can differ vastly though (network bandwidth, latency, GPU, RAM, CPUs, ARM/x86).



> The behaviour and qualities of those environments can differ vastly though (network bandwidth, latency, GPU, RAM, CPUs, ARM/x86).

For example, when you're running on your local machine you've actually got the amount of RAM and CPU advertised :)


"Hm, why does my Go service on a pod with 2.2 cpu's think it has 6k? Oh, it thinks it has the whole cluster. Nice; that is why scheduling has been an issue"


Something that's not clear from the post is whether you're running these environments on your own hardware, or layering things on top of something from a cloud provider (AWS, etc)?


Hi Christian. We just deployed Gitpod EKS at our company in NY. Can we get some details on the replacement architecture? I’m sure it’s great but the devil is always in the details.


Need middleware libs that react to eBPF data and signal app code to scale up/down forks in their own memory VM, like V8

Kubernetes is another mess of userspace ops tools. Userspace is for composable UI not backend. Kube and Chef and all those other ops tools are backend functionality being used like UI by leet haxxors




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