dstackai/dstack

# GitHub Repository: dstackai/dstack

**URL:** https://github.com/dstackai/dstack
**Author:** dstackai
**Description:** Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.
**Homepage:** https://dstack.ai/docs
**Language:** Python

## Stats
- Stars: 2163
- Forks: 233
- Open Issues: 67
- Commits: 3645
- Created: 2022-01-04T10:29:46Z
- Updated: 2026-06-18T13:24:41Z
- Pushed: 2026-06-18T14:55:50Z

## README
<div style="text-align: center;">
<h2>
  <a target="_blank" href="https://dstack.ai">
    <picture>
      <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/dstackai/dstack/master/mkdocs/assets/images/dstack-logo-dark.svg"/>
      <img alt="dstack" src="https://raw.githubusercontent.com/dstackai/dstack/master/mkdocs/assets/images/dstack-logo.svg" width="350px"/>
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  </a>
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[![Last commit](https://img.shields.io/github/last-commit/dstackai/dstack?style=flat-square)](https://github.com/dstackai/dstack/commits/)
[![PyPI - License](https://img.shields.io/pypi/l/dstack?style=flat-square&color=blue)](https://github.com/dstackai/dstack/blob/master/LICENSE.md)
[![Discord](https://img.shields.io/discord/1106906313969123368?style=flat-square)](https://discord.gg/u8SmfwPpMd)

</div>

`dstack` is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters. 

It streamlines development, training, and inference, and is compatible with any hardware, open-source tools, and frameworks.

#### Accelerators

`dstack` supports `NVIDIA`, `AMD`, `Google TPU`, and `Tenstorrent` accelerators out of the box.

## Latest news ✨
- [2026/04] [dstack 0.20.17: PD disaggregation, Kubernetes volumes](https://github.com/dstackai/dstack/releases/tag/0.20.17)
- [2026/04] [dstack 0.20.16: Performance, SSH proxy](https://github.com/dstackai/dstack/releases/tag/0.20.16)
- [2026/03] [dstack 0.20.13: Exports, Templates](https://github.com/dstackai/dstack/releases/tag/0.20.13)
- [2026/02] [dstack 0.20.12: Crusoe](https://github.com/dstackai/dstack/releases/tag/0.20.12)
- [2026/02] [dstack 0.20.8: Skills](https://github.com/dstackai/dstack/releases/tag/0.20.8)
- [2025/12] [dstack 0.20.0: Fleet-first UX, Events, and more](https://github.com/dstackai/dstack/releases/tag/0.20.0)

## How does it work?

<picture>
  <source media="(prefers-color-scheme: dark)" srcset="https://dstack.ai/static-assets/static-assets/images/dstack-architecture-diagram-v11-dark.svg"/>
  <img src="https://dstack.ai/static-assets/static-assets/images/dstack-architecture-diagram-v11.svg" width="750" />
</picture>

### Launch the server

> Before using `dstack` through CLI or API, set up a `dstack` server. If you already have a running `dstack` server, you only need to [install the CLI](#install-the-cli).

To orchestrate compute across GPU clouds or Kubernetes clusters, you need to [configure backends](https://dstack.ai/docs/concepts/backends).

> When using `dstack` with on-prem servers, backend configuration isn’t required. Simply create [SSH fleets](https://dstack.ai/docs/concepts/fleets#ssh-fleets) once the server is up.

The server can be installed on Linux, macOS, and Windows (via WSL 2). It requires Git and
OpenSSH.

```shell
$ uv tool install "dstack[all]" -U
$ dstack server

Applying ~/.dstack/server/config.yml...

The admin token is "bbae0f28-d3dd-4820-bf61-8f4bb40815da"
The server is running at http://127.0.0.1:3000/
```

> For more details on server configuration options, see the
[Server deployment](https://dstack.ai/docs/guides/server-deployment) guide.

### Install the CLI

<details><summary>If the CLI is not installed with the server</summary>

Once the server is up, you can access it via the `dstack` CLI.

The CLI can be installed on Linux, macOS, and Windows. It requires Git and OpenSSH.

```shell
$ uv tool install dstack -U
```

To point the CLI to the `dstack` server, configure it
with the server address, user token, and project name:

```shell
$ dstack project add \
    --name main \
    --url http://127.0.0.1:3000 \
    --token bbae0f28-d3dd-4820-bf61-8f4bb40815da

Configuration is updated at ~/.dstack/config.yml
```

</details>

### Install agent skills

Install [`dstack` skills](https://skills.sh/dstackai/dstack/dstack) to help AI agents use the CLI and edit configuration files.

```shell
$ npx skills add dstackai/dstack
```

AI agents like Claude, Codex, and Cursor can now create and manage fleets and submit workloads on your behalf.

### Define configurations

`dstack` supports the following configurations:
   
* [Fleets](https://dstack.ai/docs/concepts/fleets) &mdash; for managing cloud and on-prem clusters
* [Dev environments](https://dstack.ai/docs/concepts/dev-environments) &mdash; for interactive development using a desktop IDE
* [Tasks](https://dstack.ai/docs/concepts/tasks) &mdash; for scheduling jobs (incl. distributed jobs) or running web apps
* [Services](https://dstack.ai/docs/concepts/services) &mdash; for deployment of models and web apps (with auto-scaling and authorization)
* [Volumes](https://dstack.ai/docs/concepts/volumes) &mdash; for managing persisted volumes

Configuration can be defined as YAML files within your repo.

### Apply configurations

Apply the configuration via the `dstack apply` CLI command, a programmatic API, or through [AI agent skills](#install-ai-agent-skills).

`dstack` automatically manages provisioning, job queuing, auto-scaling, networking, volumes, run failures,
out-of-capacity errors, port-forwarding, and more &mdash; across clouds and on-prem clusters.

## Useful links

For additional information, see the following links:

* [Docs](https://dstack.ai/docs)
* [Examples](https://dstack.ai/examples)
* [Discord](https://discord.gg/u8SmfwPpMd)

## Contributing

You're very welcome to contribute to `dstack`. 
Learn more about how to contribute to the project at [CONTRIBUTING.md](CONTRIBUTING.md).

## License

[Mozilla Public License 2.0](LICENSE.md)