dstack

dstack is an open-source container orchestrator specifically designed for AI workloads, making GPU orchestration simple and cost-effective for ML teams. Unlike general-purpose solutions, dstack focuses on the unique needs of AI development and deployment.

Key capabilities include:

• Unified compute layer - Works seamlessly with any GPU cloud provider or on-premises cluster, keeping your infrastructure vendor-agnostic
• Dev environments - Connect your desktop IDE to cloud GPU machines for efficient experimentation and development
• Task scheduling - Run training jobs, fine-tuning, and AI workloads on optimized clusters or individual instances
• Model deployment - Deploy models as auto-scaling, OpenAI-compatible endpoints using your custom code and frameworks
• SSH fleets - Connect bare-metal and manually provisioned clusters directly to dstack

Built for ML teams who want to focus on their models rather than infrastructure complexity. dstack integrates natively with Git workflows and supports any open-source or proprietary ML frameworks. The platform provides flexible provisioning with built-in scheduling that optimizes GPU utilization and reduces costs.

Whether you're running quick prototypes or multi-node training across clouds, dstack removes the infrastructure burden while maintaining the flexibility and control your team needs.