dstack
is an open-source alternative to Kubernetes and Slurm, designed to simplify GPU allocation and AI workload
orchestration for ML teams across top clouds and on-prem clusters.
Accelerators
dstack
supports NVIDIA
, AMD
, Google TPU
, Intel Gaudi
, and Tenstorrent
accelerators out of the box.
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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
(Optional) Configure backends
To use dstack
with cloud providers, configure backends
via the ~/.dstack/server/config.yml
file.
For more details on how to configure backends, check Backends.
For using dstack
with on-prem servers, 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
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:
- 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)
- Fleets — for managing cloud and on-prem clusters
- Volumes — for managing persisted volumes
- Gateways — for configuring the ingress traffic and public endpoints
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