Orchestrating GPUs in data centers and private clouds

Hey HN, founder of dstack here. We've been working on this over three months and pretty excited about this release. Basically, the main point is that dstack is an open-source AI-native alternative to Kubernetes, designed to be more lightweight, and focusing just on AI workloads on both cloud and data-centers. With this release we are adding the critical feature that allows to run containers concurrently on same host slicing its resources incl. GPU for a more cost-efficient utilization. Another new thing is the simplified way to run things on private clouds where clusters are often behind a login node. There are many more cool things on our roadmap to ensure dstack is a streamlined alternative to both K8S and Slurm. Our roadmap can be found in [1] Super excited to hear any feedback.

[1] https://github.com/dstackai/dstack/issues/2184

Congrats on the release. Can dstack work with kubernetes? Like say another team owns the infrastructure and I’m required to use k8s, is it interoperable at all?

Thank you! Yup, dstack can also work over K8S too if required. But of course there are many advantages to use dstack’s native orchestrator.

I'm in the process of moving several workloads to dstack and going smoothly so far. It reads as kind of anti-k8s which makes it feel much more straightforward and, I expect, easier to maintain.

The devs are very responsive as well.

Nice one, looking into it.