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Description

The Industry Standard Universal Binary Repository Management Manager. All major package types supported (over 27 and growing), including Maven, npm. Python, NuGet. Gradle. Go and Helm, Kubernetes, Docker, as well as integration to leading CI servers or DevOps tools you already use. Additional functionalities include: - High availability that scales to infinity through active/active clustering in your DevOps environment. This scales as your business grows - On-Prem or Cloud, Hybrid, Multi-Cloud Solution - De Facto Kubernetes Registry for managing application packages, operating systems component dependencies, open sources libraries, Docker containers and Helm charts. Full visibility of all dependencies. Compatible with a growing number of Kubernetes cluster provider.

Description

dstack simplifies GPU infrastructure management for machine learning teams by offering a single orchestration layer across multiple environments. Its declarative, container-native interface allows teams to manage clusters, development environments, and distributed tasks without deep DevOps expertise. The platform integrates natively with leading GPU cloud providers to provision and manage VM clusters while also supporting on-prem clusters through Kubernetes or SSH fleets. Developers can connect their desktop IDEs to powerful GPUs, enabling faster experimentation, debugging, and iteration. dstack ensures that scaling from single-instance workloads to multi-node distributed training is seamless, with efficient scheduling to maximize GPU utilization. For deployment, it supports secure, auto-scaling endpoints using custom code and Docker images, making model serving simple and flexible. Customers like Electronic Arts, Mobius Labs, and Argilla praise dstack for accelerating research while lowering costs and reducing infrastructure overhead. Whether for rapid prototyping or production workloads, dstack provides a unified, cost-efficient solution for AI development and deployment.