dstackai/dstack
Vendor-agnostic GPU orchestration platform for training, inference, and agentic AI workloads across clouds, Kubernetes, and bare metal.
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dstack provides a unified control plane for GPU provisioning and orchestration that supports NVIDIA, AMD, Google TPU, and Tenstorrent accelerators. It streamlines ML model development by managing GPU infrastructure across clouds, Kubernetes clusters, and on-premises environments. The platform handles the operational complexity of running distributed training jobs and serving inference workloads at scale.
Frequently asked
- What is dstackai/dstack?
- Vendor-agnostic GPU orchestration platform for training, inference, and agentic AI workloads across clouds, Kubernetes, and bare metal.
- Is dstack open source?
- Yes — dstackai/dstack is open source, released under the MPL-2.0 license.
- What language is dstack written in?
- dstackai/dstack is primarily written in Python.
- How popular is dstack?
- dstackai/dstack has 2.2k stars on GitHub.
- Where can I find dstack?
- dstackai/dstack is on GitHub at https://github.com/dstackai/dstack.