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What is dstack?

dstack is an open-source framework for orchestrating machine learning workflows and deploying models across different cloud providers and on-premises infrastructure. It simplifies the process of training, fine-tuning, and serving AI models by abstracting away infrastructure complexity. The tool is designed for data scientists, ML engineers, and teams who want to focus on model development rather than managing cloud resources, Kubernetes clusters, or deployment pipelines. dstack supports popular frameworks like PyTorch, TensorFlow, and Ollama, and allows users to define workflows as code, making experiments reproducible and shareable across teams.

Key features

Workflow orchestration

Define and run multi-step ML pipelines using simple configuration files

Multi-cloud support

Deploy to AWS, Azure, GCP, Lambda, or on-premises infrastructure with unified interface

Model serving

Package and serve models with automatic scaling and monitoring

Version control integration

Track experiments and models alongside code in Git repositories

Resource management

Allocate GPU, CPU, and memory efficiently across jobs

Team collaboration

Share workflows, models, and results with team members

Pros & cons

Advantages

  • Open-source and free to use with no vendor lock-in
  • Works with existing ML frameworks and tools without requiring rewrites
  • Reduces time spent on infrastructure setup and deployment configuration
  • Supports both cloud and on-premises deployments flexibly

Limitations

  • Steeper learning curve than some commercial ML platforms for users new to infrastructure-as-code
  • Requires some understanding of cloud providers and their cost models to optimise effectively
  • Community-driven support rather than dedicated enterprise support in free tier

Use cases

Training and fine-tuning large language models on cloud GPUs

Running distributed machine learning experiments across multiple machines

Deploying ML models to production with automatic scaling

Sharing reproducible ML workflows across distributed teams

Managing cost-efficient training by using spot instances and auto-scaling

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Pricing

Open Source

Free

Full access to dstack framework, self-hosted deployment, community support

dstack Sky (Cloud Hosted)

Free tier available; paid plans from $9/month

Managed cloud platform, simplified multi-cloud orchestration, team features, monitoring dashboard

Get started with dstack

Click through to dstack and start using it now.

Try dstack free
  • Free plan available
  • No credit card