macOS
Homebrewverified · 100%
brew install dstacklocal Homebrew formula metadata
brew / rank 3864
Install dstack with Homebrew
ML workflow orchestration system designed for reproducibility and collaboration. Version 0.20.29 via Homebrew; verified 2026-07-25.
install
Additional install commands
overview
Package summary
ML workflow orchestration system designed for reproducibility and collaboration
Project links
Commands and aliases
- dstack
history
Project history and usage
dstack is an open-source control plane and CLI for provisioning and orchestrating GPU and AI workloads across cloud providers, Kubernetes, and on-premises machines. Its package-manager identity is a Python-distributed ML infrastructure tool that gives users a local `dstack` command, a server, and YAML workload definitions.
Project history
The package trail starts on PyPI in September 2021, while the GitHub repository was created in January 2022. The project evolved from a reproducible ML workflow tool into a broader GPU orchestration system covering development environments, training tasks, services, fleets, volumes, and backends.
By 2026 the README described dstack as a unified control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters, with support for NVIDIA, AMD, Google TPU, and Tenstorrent accelerators. The docs and README also show the project adapting to agentic workflows through dstack skills for tools such as Claude, Codex, and Cursor.
Adoption history
Distribution is source-backed through PyPI and Homebrew. PyPI metadata records hundreds of releases and version 0.20.26 in June 2026, while the Homebrew formula uses the same release from the Python source distribution.
Homebrew analytics are modest compared with general-purpose infrastructure tools, but the formula matters because it gives macOS and Linux users a package-manager path into a Python ML orchestration stack without starting from a source checkout.
How it is used
Typical usage starts with installing the CLI or server, running `dstack server`, adding a project with a server URL and token, and applying YAML configurations from a repository. The official README documents `.dstack.yml` workload files and user or server configuration under `~/.dstack`.
The package is aimed at teams that want one workflow for development environments, batch tasks, training jobs, services, and GPU fleet management across different compute backends.
Why package nerds care
dstack is notable as part of the modern wave of ML infrastructure CLIs that package cloud, Kubernetes, GPU scheduling, and developer workflow into a single local command. It sits in the same package-manager lane as tools that developers install before a full platform is available.
For package nerds, its interesting wrinkle is the mix of Python packaging, Homebrew distribution, server configuration, repo-local YAML definitions, and rapidly changing AI accelerator support.
Timeline
- 2021-09: PyPI records the first dstack release artifacts.
- 2022-01: The current GitHub repository is created.
- 2025-12: dstack 0.20.0 release line emphasizes fleet-first UX and events.
- 2026-06: PyPI and Homebrew package dstack 0.20.26.
Related projects
- Kubernetes is one of the supported orchestration backends.
- PyPI is the upstream package distribution channel used by the Homebrew formula.
- Claude, Codex, and Cursor are named in the README as agent clients that can use dstack skills.
Sources
security posture
Risk level: orange
infrastructure mutation or orchestration signal.
Risk classifier
orange risk · medium confidence · infrastructure
Why
- infrastructure mutation or orchestration signal
Signals
- text:orchestration
Install behavior
- No Homebrew bottle metadata was recorded.
Recommended review
Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.
local files
Configuration and credential file locations
These source-backed paths show where this package keeps local settings or durable credentials. Automic Vault can use them as review targets for secret scanning, migration, and command approval.
Configuration files
Config paths the tool may read or write during local use.
- Unix
.dstack.yml~/.dstack/config.yml~/.dstack/server/config.yml
Credential files
Credential-bearing paths to review before unattended agent runs.
- Unix
~/.dstack/config.yml~/.dstack/server/config.yml
executables
Installed executables
| Command | Kind | Exposure | Note |
|---|---|---|---|
dstack | executable | indexed executable | Discovered from the local executable index. |
freshness
Version and freshness
These signals separate page generation age, package-manager activity, and upstream release comparison. Version lag is warned only when an evidence URL and comparable versions are present.
page generated2026-08-03
manager version0.20.29
manager updated2026-07-25
local dataunknown
upstreamnot available
latest detectednot detected
- okNo freshness warnings were generated.
install metadata
Package metadata
| Package key | brew:dstack |
|---|---|
| Version | 0.20.29 |
| Package manager | Homebrew |
| Homepage | https://dstack.ai/ |
| Last updated | 2026-07-25T12:52:13Z |
| Pulse | updated |
| Bottle | not recorded |
| Service | none declared |
source trail
Generated from repository data
This page is generated by av-web from the private package SQLite artifact built by scripts/generate-pkg-sqlite.py.
Combined YAML source
View the package source record on GitHub.
Used sources
- Geiger risk classifier
- cross-ecosystem install command graph
- curated configuration and credential file locations
- curated package history
- pkg.so package database
- pkgdb category and tag curation