A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.
- Recommended by
- 3
- GitHub stars
- 2.3k
- Licence
- MPL-2.0
- Language
- Python
- Last commit
- 2 Nov 2026
What people said
“A nice project—I hadn’t seen it before. I’m working on a similar concept but as an open-source project. We see it as an alternative to K8s/Slurm and would be interested in hearing thoughts from other ML engineers.”
“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 o…”
“I can completely relate to anyone abandoning K8s. I'm working with dstack, an open-source alternative to K8s for AI infra. We talk to many people who are frustrated with K8s, especially for GPU and AI workloads.”
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