What is dstack?¶
dstack is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters.
It streamlines development, training, and inference, and is compatible with any hardware, open-source tools, and frameworks.
Accelerators
dstack supports NVIDIA, AMD, TPU, and Tenstorrent accelerators out of the box.
How does it work?¶
Set up the server¶
Before using
dstack, ensure you've installed the server, or signed up for dstack Sky.
Define configurations¶
dstack supports the following configurations:
- Fleets — Provision and manage clusters across clouds, Kubernetes, and on-prem
- Dev environments — Launch dev environments to be accessed by agents or from your IDE
- Tasks — Run training, batch or other jobs across a single node or clusters
- Services — Deploy model inference as secure and scalable endpoints
- Presets — Agent-driven inference optimization (experimental)
- Volumes — Managing instance and network volumes for persisting data
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 infrastructure provisioning and job scheduling, while also handling auto-scaling,
port-forwarding, ingress, and more.
Where do I start?
- Proceed to installation
- See quickstart
- Browse examples
- Join Discord