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// Automate workflows

dstack0.22.3

A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.

Open source Maintained For developers

Official site ↗ GitHub ↗

IN ONE PARAGRAPH

dstack is A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.

Good for: Developers and teams who want to automate workflows.

01How to start

  1. 1Read the official quick-start (link above).
  2. 2Install from the official package registry: pip install dstack
  3. 3Try it on a small example before wiring it into a project.

PyPI: dstack

02Alternatives & comparison

Compare side by side →
airflow Apache Airflow - A platform to programmatically author, schedule, and monitor workflows ★ 47k skypilot The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster. ★ 11k ray Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads. ★ 44k prefect Prefect is a workflow orchestration framework for building resilient data pipelines in Python. ★ 24k dagster An orchestration platform for the development, production, and observation of data assets. ★ 16k
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