AI container orchestration
for everyone
dstack is an open-source alternative to Kubernetes, designed to simplify development and deployment of AI. It works with top cloud providers and on-prem servers, and supports NVIDIA, AMD, and TPU.
Dev environments
Dev environments allow you to provision a remote machine, set up with your code and favorite IDE, with just one command.
Dev environments are perfect for interactively running code using your favorite IDE or notebook before scheduling a task or deploying a service.
Tasks
A task allows you to schedule a job or run a web app. It lets you configure dependencies, resources, ports, and more. Tasks can be distributed and run on clusters.
Tasks are ideal for training and fine-tuning jobs or running apps for development purposes.
Services
Services allow you to deploy web apps or models as private or public auto-scalable endpoints. You can configure dependencies, resources, authorizarion, auto-scaling rules, etc.
Once deployed, the web app or a model can be used by anyone on the team.
Fleets
Fleets enable efficient provisioning and management of clusters and instances, both in the cloud and on-prem.
Once a fleet is created, it can be reused by dev environments, tasks, and services.
Why ML engineers dstack
Andrew Spott
ML Engineer at Stealth Startup
Thanks to @dstack, I get the convenience of having a personal Slurm cluster and using budget-friendly cloud GPUs, without paying the super-high premiums charged by the big three.
Alvaro Bartolome
ML Engineer at Argilla
With @dstack it's incredibly easy to define a configuration within a repository and run it without worrying about GPU availability. It lets you focus on data and your research.
Park Chansung
ML Researcher at ETRI
Thanks to @dstack, I can effortlessly access the top GPU options across different clouds, saving me time and money while pushing my AI work forward.
Eckart Burgwedel
CEO at Uberchord
With @dstack, running LLMs on a cloud GPU is as easy as running a local Docker container. It combines the ease of Docker with the auto-scaling capabilities of K8S.
Peter Hill
Co-Founder at CUDO Compute
@dstack simplifies infrastructure provisioning and AI development. If your team is on the lookout for an AI platform, I wholeheartedly recommend @dstack.
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FAQ
dstack is used by both small teams and large enterprises.
Small teams use dstack as an alternative to Kubernetes or Slurm for the ease of development, training, and deployment of AI. One of the advantages for small teams is that dstack allows to access GPUs from a variety of providers at most affordable rate.
Large enterprises use dstack as an alternative to Kubernetes or cloud platforms such as SageMaker, Vertex AI, or Azure ML, for development simplicity and flexibility while also avoiding vendor lock-in, and the ability to combine multiple clouds and on-prem servers.
Both dstack and Kubernetes are container orchestrators that can be used with cloud and on-prem.
First of all, dstack offers an interface tailored for AI, allowing AI engineers to use it out of the box for development, training, and deployment without needing additional tools or help from the Ops team.
dstack, out of the box, supports multiple cloud providers and offers all the features of a managed version of Kubernetes. It's very easy to integrate dstack with new cloud providers.
dstack is much easier to use for running containers on on-prem servers. If you have a cluster of on-prem servers, you just need to provide dstack with their hostnames and SSH credentials. dstack will automatically add them as a fleet that you can reuse to run containers.
If you already use Kubernetes, you can set up the dstack server to run containers via Kubernetes. In that case, dstack provides your AI engineers with a simple interface for running dev environments, tasks, and services without involving your Ops team or using any other tools.
Often mature teams use dstack and Kubernetes side by side, where dstack is used for anything related to AI development and Kubernetes for production-grade deployment.
dstack is being developed as an open-source project under the MPL-2.0 licence by a team of senior system engineers with lots of experience building container orchestration and managing infrastructure.
dstack is a Munich-based company backed by european VCs.
While dstack helps enterprises adopt dstack, it's primarily committed to developing dstack as an open-source project, open to third-party contribution from individuals and large vendors.
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