The bare-metal GPU compute platform built for AI/ML workloads. NVIDIA-native. Kubernetes-first.
EKS + OpenAI Infrastructure + Databricks + CoreWeave -- but self-hosted and bare-metal native. GPU orchestration, RDMA networking, and parallel filesystems in one enterprise platform.
One self-hosted platform delivers what enterprises currently piece together from managed services and proprietary stacks.
Bare-metal GPU performance without cloud hypervisor tax. Your hardware, your data, your margins.
No per-node licensing. Self-hosted from day one. No vendor lock-in on your AI infrastructure.
Self-hosted compute fabric you own. No per-GPU-hour billing surprises on training runs.
Run on your own bare metal. Same GPU density, zero egress fees, full data sovereignty.
Enterprise-grade orchestration with RDMA and parallel filesystems. Production, not just prototyping.
Pre-integrated GPU scheduling, RDMA, and storage. Weeks of integration work eliminated.
NVIDIA GPU-aware scheduling with MIG, time-slicing, and multi-GPU topology support. Maximize utilization across your fleet.
InfiniBand and RoCE v2 support for GPU-to-GPU communication. Sub-microsecond latency for distributed training.
Integrated support for Lustre, GPFS, and BeeGFS. Feed data to GPUs at line rate without storage bottlenecks.
Deploy on bare metal in your datacenter, at the edge, or across cloud providers. One control plane for all GPU compute.
Built on production Kubernetes with custom operators for GPU lifecycle management.
Native integration with NVIDIA GPU Operator, DCGM, and container toolkit for full GPU visibility.
Fully self-hosted. No per-node fees, no GPU-hour billing, no vendor lock-in. Deployed on your terms.
See how KubeFabric delivers bare-metal GPU performance with Kubernetes-native orchestration -- fully self-hosted and enterprise-ready.