dstack

Name: dstack
Author: dstackai

Verified

dstack is an open-source control plane for running development, training, and inference jobs on GPUs—across hyperscalers, neoclouds, or on-prem.

2,067stars

219forks

Python

Installation

# Add to your Claude Code skills
git clone https://github.com/dstackai/dstack

Getting Started

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Security ReportVerified

Last scanned: 4/25/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-04-25T05:48:38.912Z",
  "semgrepRan": false,
  "npmAuditRan": true,
  "pipAuditRan": true
}

README.md

Frequently Asked Questions

What is dstack?

dstack is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by dstackai. dstack is an open-source control plane for running development, training, and inference jobs on GPUs—across hyperscalers, neoclouds, or on-prem. It has 2,067 GitHub stars.

Is dstack safe to use?

Yes. dstack passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install dstack?

Clone the repository with "git clone https://github.com/dstackai/dstack" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is dstack written in?

dstack is primarily written in Python. It is open-source under dstackai on GitHub, so you can review or fork the full source.

Are there alternatives to dstack?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh dstack against similar tools.

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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, Intel Gaudi, and Tenstorrent accelerators out of the box.

Latest news ✨

[2025/12] dstack 0.20.0: Fleet-first UX, Events, and more
[2025/11] dstack 0.19.38: Routers, SGLang Model Gateway integration
[2025/10] dstack 0.19.31: Kubernetes, GCP A4 spot
[2025/08] dstack 0.19.26: Repos
[2025/08] dstack 0.19.22: Service probes, GPU health-checks, Tenstorrent Galaxy
[2025/07] dstack 0.19.21: Scheduled tasks
[2025/07] dstack 0.19.17: Secrets, Files, Rolling deployment

How does it work?

Installation

Before using dstack through CLI or API, set up a dstack server. If you already have a running dstack server, you only need to set up the CLI.

Set up the server

Configure backends

To orchestrate compute across GPU clouds or Kubernetes clusters, you need to configure backends.

Backends can be set up in ~/.dstack/server/config.yml or through the project settings page in the UI.

For more details, see Backends.

When using dstack with on-prem servers, backend configuration isn’t required. Simply create SSH fleets once the server is up.

Start the server

You can install the server on Linux, macOS, and Windows (via WSL 2). It requires Git and OpenSSH.

uv

$ uv tool install "dstack[all]" -U

pip

$ pip install "dstack[all]" -U

Once it's installed, go ahead and start the server.

$ 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 guide.

Set up the CLI

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.

uv

$ uv tool install dstack -U

pip

$ pip install dstack -U

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

$ 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

Define configurations

dstack supports the following configurations:

Fleets — for managing cloud and on-prem clusters
Dev environments — for interactive development using a desktop IDE
Tasks — for scheduling jobs (incl. distributed jobs) or running web apps
Services — for deployment of models and web apps (with auto-scaling and authorization)
Volumes — for managing persisted volumes

Configuration can be defined as YAML files within your repo.

Apply configurations

Apply the configuration either via the dstack apply CLI command or through a programmatic API.

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

Useful links

For additional information, see the following links:

Contributing

You're very welcome to contribute to dstack. Learn more about how to contribute to the project at CONTRIBUTING.md.

License

Mozilla Public License 2.0