dstack
@dstackai
A unified control plane for GPU orchestration across cloud, Kubernetes, & on-prem — for development, training, & inference — cutting costs & avoiding lock-in.
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Introducing Fleets: a new open-source tool to manage cloud and on-prem clusters for AI. No more Kubernetes, KubeFlow, Slurm, etc. Fleets enable researchers and engineers to develop AI seamlessly, without friction with Ops teams. dstack.ai/docs/fleets/
Since launching fleets last year, they’ve become one of the most impactful ways to simplify GPU provisioning across cloud and on-prem. Over the past year, we've added: * Native @kubernetesio support * Elastic fleets that auto-scale as team needs change Read more about how…
Ten years ago, Kubernetes reshaped how we deployed software. Now, GPU orchestration is about to do the same for AI infrastructure. At dstack, we're lucky to be early — working with @nvidia, @AMD, @LambdaAPI, @nebiusai, @runpod, @awscloud, @googlecloud, @HotAisle, and…
Since launching fleets last year, they’ve become one of the most impactful ways to simplify GPU provisioning across cloud and on-prem. Over the past year, we've added: * Native @kubernetesio support * Elastic fleets that auto-scale as team needs change Read more about how…
Met @andrey_cheptsov in SF I loved talking about @dstackai with him PS: you can see jet lag on my face ;)
We’re building dstack to make it simple to run on any GPU — cloud or on-prem. Exciting to see so many teams already using it. We’re 56 stars from 2K on GitHub — let’s make it happen! github.com/dstackai/dstac…
dstack keeps getting no better and better. Quick and amazing execution.
Shoutout to the @dstackai team for adding support for our instant clusters! More ways to orchestrate your multi-node workloads 🚀
Enjoyed meeting the team at @LambdaAPI and discussing open-source and GPU orchestration. Thanks @chuanli11 for the warm welcome and tour! 💜
dstack now supports multi-node scheduling on @runpod! Run your jobs on B200, H200, H100, and A100 GPU instant clusters - InfiniBand up to 3200 Gbps 🚀
Noticing a shift toward open, self-hosted GPU orchestration tools. @dstackai seems worth a look if you’re avoiding lock-in. It's available under MPL-2.0 licence: github.com/dstackai/dstac…
What @nebiusai really is, under the hood! Not just GPUs, but a full stack of open-source orchestration tools and seamless integrations.
Join @AleksandrPatr and me tomorrow for a virtual session on multi-cloud AI infrastructure with @nebiusai and @dstackai! We’ll cover how to get the most out of cloud GPUs using GPU-native orchestration. 🗓 Oct 30, 9am PDT / 5pm CET 🔗 nebius.com/events/webinar…
nebius.com
Multi-cloud AI infrastructure in action — with Nebius and dstack
Discover the most efficient way to build, tune and run your AI models and applications on top-notch NVIDIA® GPUs.
Multi-cloud AI infrastructure in action - with @nebiusai and dstack⚡️ Join @AleksandrPatr and @andrey_cheptsov for a deep dive on: * Why GPU container orchestration matters, and what's beyond Kubernetes and Slurm * Deploying distributed training job * Cost-optimization an…
Last week’s @PyTorch Conf was packed with great discussions on GPU orchestration, model training, and inference🚀 Our meetup was a real highlight - tons of builders, deep technical chats on AI infra, and open-source models.
Andrey is awesome, if anything just go have a chat with him and learn about what he's up to.
In SF this and next week! Want to meet people building AI infra - GPU orchestration, large-scale training, inference systems. DM or tag someone building interesting stuff.
In SF this and next week! Want to meet people building AI infra - GPU orchestration, large-scale training, inference systems. DM or tag someone building interesting stuff.
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