
AI Networking: What GPU Infrastructure Really Requires
Learn how AI workloads change network design across GPU clusters, storage, east-west traffic, RDMA/RoCE, Kubernetes placement, and production inference.
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Engineering notes from operating open infrastructure: the failures, design decisions, and upstream work that make open infrastructure better.
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Learn how AI workloads change network design across GPU clusters, storage, east-west traffic, RDMA/RoCE, Kubernetes placement, and production inference.
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Booting a GPU server isn't the same as making it production-ready. How Atmosphere unifies OpenStack, Ironic, and Kubernetes to turn H200 hardware into recoverable, reusable AI infrastructure.
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Compare GPU VMs, bare metal, Kubernetes, and managed inference for AI workloads. Learn which architecture fits your performance, control, scaling, and operational needs.
Read field noteTrends, best practices, and technical deep dives on open source cloud infrastructure.

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