dstack is an open-source orchestration engine for running AI workloads on any cloud or on-premises.
dstack is a streamlined alternative to Kubernetes and Slurm, specifically designed for AI. It simplifies container orchestration
for AI workloads both in the cloud and on-prem, speeding up the development, training, and deployment of AI models.
dstack is easy to use with any cloud provider as well as on-prem servers.
dstack supports NVIDIA, AMD, Google TPU, and Intel Gaudi accelerators out of the box.
Before using
dstackthrough CLI or API, set up adstackserver. If you already have a runningdstackserver, you only need to set up the CLI.
To use dstack with cloud providers, configure backends.
For using dstack with on-prem servers, create SSH fleets instead.
Once the backends are configured, proceed to start the server:
$ pip 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 guide.
To point the CLI to the dstack server, configure it
with the server address, user token, and project name:
$ pip install dstack
$ dstack config --url http://127.0.0.1:3000 \
--project main \
--token bbae0f28-d3dd-4820-bf61-8f4bb40815da
Configuration is updated at ~/.dstack/config.yml
dstack supports the following configurations:
Configuration can be defined as YAML files within your repo.
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.
For additional information and examples, see the following links:
You're very welcome to contribute to dstack.
Learn more about how to contribute to the project at CONTRIBUTING.md.
FAQs
dstack is an open-source orchestration engine for running AI workloads on any cloud or on-premises.
We found that dstack demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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