dstack
Automate data and training workflows with dstack.
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is dstack?
dstack is an open-core tool designed to automate data and machine learning workflows. It simplifies the process of managing experiments, tracking metrics, and deploying models efficiently.
Key differentiator
“dstack stands out as an open-source tool specifically designed to automate data and training workflows, offering comprehensive tracking and deployment capabilities.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development focuses on Python, secondary languages like TypeScript have community-maintained SDKs with limited features
GitHub repository shows low activity levels compared to more established ML platforms
Fit analysis
Who is it for?
✓ Best for
Teams needing to automate and track complex data science workflows
Projects requiring efficient model deployment and tracking metrics
✕ Not a fit for
Users looking for a fully managed cloud service without self-hosting capabilities
Small projects that do not require extensive workflow automation or tracking features
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Next step
Get Started with dstack
Step-by-step setup guide with code examples and common gotchas.