dstack ☆
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Description:
ML workflow orchestration system designed for reproducibility and collaboration
Type: Formula  |  Latest Version: 0.20.0@0  |  Tracked Since: Dec 17, 2025
Links: Homepage  |  @dstackai  |  formulae.brew.sh
Category: Ai ml
Tags: ai ml orchestration devops reproducibility
Install: brew install dstack
About:
dstack is an open-source orchestration system that enables developers to define and run ML workflows using Python. It abstracts infrastructure management, allowing seamless execution across local machines, cloud providers, or on-premise clusters. The platform focuses on reproducibility and collaboration, making it easier for teams to develop and share AI applications.
Key Features:
  • Declarative YAML or Python API for defining workflows
  • Automatic provisioning of cloud and local infrastructure
  • Built-in support for dev environments, tasks, and services
  • Git integration for version control and reproducibility
Use Cases:
  • Developing and training ML models in reproducible cloud environments
  • Running large-scale batch inference jobs on spot instances
  • Collaborating on AI projects with shared, versioned configurations
Alternatives:
  • Kubeflow – Kubeflow is Kubernetes-native and more complex, while dstack offers a simpler, cloud-agnostic experience.
  • Weights & Biases – W&B focuses on experiment tracking, whereas dstack provides full environment and workflow orchestration.
Version History
Detected Version Rev Change Commit
Dec 17, 2025 10:59am 0 REVISION_ONLY bfd5c911
Dec 17, 2025 8:15am 2 VERSION_BUMP a5df2c85
Dec 6, 2025 1:58am 1 VERSION_BUMP 8031c33c
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