dstack
Orchestration stack for heterogeneous AI compute.
dstack is an open-source orchestration layer for AI workloads across heterogeneous accelerators. It provides a unified control plane for managing compute and running training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters, helping teams use existing infrastructure without building their own AI compute stack.
Its core modules include Fleets for cluster provisioning and monitoring, Tasks for job scheduling, Services for cache-aware and PD-disaggregated inference, Gateways for HTTPS, auto-scaling, domains, and rate limits, Presets as an agent-based optimization toolkit, and Projects for tenant isolation and usage metering. Backends cover major GPU clouds, SSH fleets, Kubernetes, and an experimental Slurm backend, with support for any framework and any model.
dstack is aimed at cloud tenants, data-center operators, and AI token factories. It is available as self-hosted dstack, the multi-tenant dstack Factory, and the hosted dstack Sky, which provides unified access to GPU clouds with one billing.
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