Audience

Machine learning teams and enterprises seeking a unified, cost-efficient orchestration layer to manage GPU-based development, training, and inference across cloud, Kubernetes, and on-prem environments

About dstack

dstack is an orchestration layer designed for modern ML teams, providing a unified control plane for development, training, and inference on GPUs across cloud, Kubernetes, or on-prem environments. By simplifying cluster management and workload scheduling, it eliminates the complexity of Helm charts and Kubernetes operators. The platform supports both cloud-native and on-prem clusters, with quick connections via Kubernetes or SSH fleets. Developers can spin up containerized environments that link directly to their IDEs, streamlining the machine learning workflow from prototyping to deployment. dstack also enables seamless scaling from single-node experiments to distributed training while optimizing GPU usage and costs. With secure, auto-scaling endpoints compatible with OpenAI standards, it empowers teams to deploy models quickly and reliably.

Integrations

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Company Information

dstack
Founded: 2022
Germany
dstack.ai/

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Product Details

Platforms Supported
Cloud
Training
Documentation
Support
Online

dstack Frequently Asked Questions

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