Skip to main content

dstack is an open-source orchestration engine for running AI workloads on any cloud or on-premises.

Project description

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 ✨

Installation

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

1. Configure backends

If you want the dstack server to run containers or manage clusters in your cloud accounts (or use Kubernetes), create the ~/.dstack/server/config.yml file and configure backends.

2. 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/

Note It's also possible to run the server via Docker.

The dstack server can run anywhere: on your laptop, a dedicated server, or in the cloud. Once it's up, you can use either the CLI or the API.

3. 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

4. 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:

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dstack-0.18.14.tar.gz (14.9 MB view details)

Uploaded Source

Built Distribution

dstack-0.18.14-py3-none-any.whl (15.1 MB view details)

Uploaded Python 3

File details

Details for the file dstack-0.18.14.tar.gz.

File metadata

  • Download URL: dstack-0.18.14.tar.gz
  • Upload date:
  • Size: 14.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for dstack-0.18.14.tar.gz
Algorithm Hash digest
SHA256 f02c221cd64a5c50489e018169e76c3743a88ba350d4fc4bd0ded5168e951581
MD5 f00bd4f0fd41da047865d8bcf58ed2ff
BLAKE2b-256 b0797c92423ecfcc7ae5f28cbb70bee56c12ad00317c436aad3e7c7533ae3ab4

See more details on using hashes here.

File details

Details for the file dstack-0.18.14-py3-none-any.whl.

File metadata

  • Download URL: dstack-0.18.14-py3-none-any.whl
  • Upload date:
  • Size: 15.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for dstack-0.18.14-py3-none-any.whl
Algorithm Hash digest
SHA256 029e6c03372b51cbb25afd6f820ae5792c03439520551d00f9e034cba846773e
MD5 97636d39eb2c4aad5fcfdf6c76b460fa
BLAKE2b-256 10c55e77a3044399d5949a9126a82b46ae3dbb2c27235bfe1166262bb6d075e5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page