dstack

About

dstack is an open-source orchestration layer for AI workloads across GPU clouds, Kubernetes, virtual machines, and bare-metal clusters. YAML configurations define fleets, development environments, tasks, services, presets, and volumes; the system handles infrastructure provisioning and job scheduling, including auto-scaling, port forwarding, and ingress. It supports NVIDIA, AMD, TPU, and Tenstorrent accelerators. Documented backends include AWS, Azure, GCP, Kubernetes, GPU cloud providers, remote SSH hosts, and an experimental Slurm backend. Users manage resources with a CLI or HTTP API, and the server can run wherever it can reach the cloud or on-premises clusters in use. Services can publish inference endpoints through gateways with HTTPS, custom domains, auto-scaling, and rate limits. The self-hosted open-source stack is free. Server data and project secrets are stored in plaintext by default unless administrators configure AES-256-GCM encryption. TPU support is limited to single-host instances with at most eight cores.

Who it is for

It suits teams orchestrating AI workloads across cloud and on-premises infrastructure, especially where YAML configuration, CLI use, or an HTTP API fits the workflow. Teams using TPUs should account for the single-host, eight-core limit.

Compared on GPU cluster management software

Free plan

Yesdstack.ai

Deployment model

hybriddstack.ai

Workload scheduling

bothdstack.ai

Kubernetes support

Yesdstack.ai

Quota controls

Nodstack.ai

GPU utilization metrics

Yesdstack.ai

Cloud GPU support

Yesdstack.ai

Facts

What it does

dstack is an open-source orchestration layer for AI workloads across GPU clouds, Kubernetes, VMs, and bare-metal clusters.dstack.ai · 30 Sept 2026

Workload types

It supports fleets, development environments, tasks, services, presets, and volumes configured with YAML files.dstack.ai · 30 Sept 2026

Accelerators

dstack supports NVIDIA, AMD, TPU, and Tenstorrent accelerators out of the box.dstack.ai · 30 Sept 2026

Inference

Services can deploy model inference as endpoints, and gateways support HTTPS, auto-scaling, custom domains, and rate limits.dstack.ai · 30 Sept 2026

Integrations

Documented backends include AWS, Azure, GCP, Kubernetes, multiple GPU cloud providers, remote SSH hosts, and an experimental Slurm backend.dstack.ai · 30 Sept 2026

Framework compatibility

The maker describes dstack as compatible with any hardware, open-source tools, and frameworks.dstack.ai · 30 Sept 2026

Interfaces

Users can manage resources with the dstack CLI or call its HTTP API.dstack.ai · 30 Sept 2026

Platforms

The CLI runs on Linux, macOS, and Windows; the server can be installed on those systems, with Windows using WSL 2.dstack.ai · 30 Sept 2026

Deployment

The server can run on a laptop or another environment with access to the cloud and on-prem clusters being used.dstack.ai · 30 Sept 2026

Security

Server data is stored in plaintext by default; administrators can configure AES-256-GCM encryption for stored data.dstack.ai · 30 Sept 2026

Secrets

Secrets are project-scoped, managed by project admins, and stored in plaintext by default unless server encryption is configured.dstack.ai · 30 Sept 2026

Support

The documentation directs users to report issues on GitHub and ask questions in the dstack Discord server.dstack.ai · 30 Sept 2026

Cost model

dstack Sky does not currently charge for BYOC mode; GPU Marketplace usage is prepaid and resource prices are shown in the console before provisioning.dstack.ai · 30 Sept 2026

Commercial offering

dstack Factory extends the open-source product with advanced multi-tenancy, usage metering, billing automation, and optimized inference presets for frontier open models.dstack.ai · 30 Sept 2026

Purpose

dstack is an open-source orchestration layer for AI workloads on heterogeneous accelerators, including GPU clouds, Kubernetes, VMs, and bare-metal clusters.dstack.ai · 30 Sept 2026

Workloads

It supports fleets, dev environments, tasks, services, experimental presets, and volumes through YAML configurations.dstack.ai · 30 Sept 2026

Provisioning

dstack manages infrastructure provisioning and job scheduling, including auto-scaling, port forwarding, and ingress.dstack.ai · 30 Sept 2026

Frameworks

The tasks guide names accelerate, torchrun, Ray, and Spark as distributed frameworks that work with dstack.dstack.ai · 30 Sept 2026

API

dstack offers an HTTP API for functionality not available in the CLI and for integrations that need to call the server directly.dstack.ai · 30 Sept 2026

Service endpoints

Services can be published with HTTPS, custom domains, auto-scaling, and rate limits through gateways.dstack.ai · 30 Sept 2026

Deployment limit

The TPU guide says dstack currently supports single-host TPUs only, with a maximum of eight cores per TPU instance.dstack.ai · 30 Sept 2026

Hosted pricing

dstack Sky Marketplace pricing is dynamic by provider, shown in the console before provisioning, and billed against prepaid credits.dstack.ai · 30 Sept 2026

Company

The terms identify dstack Inc. as a Delaware corporation with offices in Dover, Delaware, United States.dstack.ai · 30 Sept 2026

Where it ranks on Inferse

• Best GPU Cluster Management Software in 2026#2 of 21

Sources

• dstack.ai/docs/· checked 30 Sept 2026
• dstack.ai/docs/concepts/gateways/· checked 30 Sept 2026
• dstack.ai/docs/concepts/backends/· checked 30 Sept 2026
• dstack.ai/docs/guides/cli-api/· checked 30 Sept 2026
• dstack.ai/docs/installation/· checked 30 Sept 2026
• dstack.ai/docs/guides/server-deployment/· checked 30 Sept 2026
• dstack.ai/docs/concepts/secrets/· checked 30 Sept 2026
• dstack.ai/docs/guides/troubleshooting/· checked 30 Sept 2026
• dstack.ai/terms/· checked 30 Sept 2026
• dstack.ai/products/factory/· checked 30 Sept 2026
• dstack.ai· checked 30 Sept 2026
• dstack.ai/docs/concepts/tasks/· checked 30 Sept 2026