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2025

Introducing GPU blocks and proxy jump for SSH fleets

Recent breakthroughs in open-source AI have made AI infrastructure accessible beyond public clouds, driving demand for running AI workloads in on-premises data centers and private clouds. This shift offers organizations both high-performant clusters and flexibility and control.

However, Kubernetes, while a popular choice for traditional deployments, is often too complex and low-level to address the needs of AI teams.

Originally, dstack was focused on public clouds. With the new release, dstack extends support to data centers and private clouds, offering a simpler, AI-native solution that replaces Kubernetes and Slurm.

Supporting NVIDIA and AMD accelerators on Vultr

As demand for AI infrastructure grows, the need for efficient, vendor-neutral orchestration tools is becoming increasingly important. At dstack, we’re committed to redefining AI container orchestration by prioritizing an AI-native, open-source-first approach. Today, we’re excited to share a new integration and partnership with Vultr .

This new integration enables Vultr customers to train and deploy models on both AMD and NVIDIA GPUs with greater flexibility and efficiency–using dstack.