dstack is a streamlined alternative to Kubernetes, 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 providers as well as on-prem servers.

Accelerators

dstack supports NVIDIA GPU, AMD GPU, and Google Cloud TPU out of the box.

Major news ✨

• [2024/08] dstack 0.18.11: AMD, encryption, and more (Release)
• [2024/08] dstack 0.18.10: Control plane UI (Release)
• [2024/07] dstack 0.18.7: Fleets, RunPod volumes, dstack apply, and more (Release)
• [2024/05] dstack 0.18.4: Google Cloud TPU, and more (Release)
• [2024/05] dstack 0.18.2: On-prem clusters, private subnets, and more (Release)

Installation

Before using dstack through CLI or API, set up a dstack server.

Configure backends

To use dstack with your own cloud accounts, create the ~/.dstack/server/config.yml file and configure backends.

Start the server

Once 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.

Set up the CLI

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

Create SSH fleets

If you want the dstack server to run containers on your on-prem servers, use fleets.

How does it work?

Before using dstack, install the server and configure backends.

1. 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.

2. 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.

More information

For additional information and examples, see the following links:

• Docs
• Examples
• Providers
• Discord

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