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Edge & Data Center
One compute plane from core to edge.
Orion orchestrates GPU workloads, VMs, containers, and bare metal across distributed edge locations, with the same unified management you use in your data center. No lightweight trade-offs. No Kubernetes-only limitations.
Edge & data center outcomes
Typically 2–4× more GPU workload density from existing hardware, same nodes, more concurrent workloads via time slicing
Workload provisioning, same speed whether you're operating from the data center or a distributed edge node
Sovereign operation. Orion runs fully on-premises from rack to remote edge, no cloud management plane required.
Cloud smart infrastructure
🌐
Multi-site orchestration
Manage data center cores, regional clusters, and remote edge nodes from a single Orion compute plane. No per-site management stack. Policy, RBAC, and resource quotas propagate automatically to every node.
🔌
Heterogeneous GPU support
NVIDIA GPU operators supported out of the box. AMD and Intel GPU operators available via community plugin (roadmap). Schedule mixed accelerator fleets across edge sites without per-vendor management stacks.
⚡
Bare metal GPU at the edge
Skip the hypervisor tax at constrained sites. Containers get direct PCIe access to the GPU, no virtualization overhead, no nested scheduling, so a 4-GPU edge box behaves like a 4-GPU edge box.
📡
Disconnected edge operation
Edge nodes continue running scheduled workloads during connectivity loss. When the link recovers, Orion syncs state and reconciles configuration automatically, no operator intervention required.
What teams deploy on Orion
AI inference at the edge
Run vision models, LLMs, and inference workloads on GPU-equipped remote nodes. Results stay local, no data leaves the site.
Manufacturing and industrial IoT
Computer vision and real-time analytics on the factory floor, low-latency, no cloud roundtrip, direct connection to plant systems
VMware migration
Migrate existing VM workloads to KubeVirt while containerized workloads run in parallel. Transition at your pace, no production disruption.
On-prem GPU training
Multi-node distributed training clusters on bare metal, no cloud egress, no licensing fees, full GPU utilization via time slicing. Bring your framework via Helm.
Multi-region data center
Route workloads across data center regions based on capacity, cost, and compliance, single management plane, no per-region silos
Hybrid cloud bursting
Failover escalation when a site loses GPU capacity: workloads reroute edge → regional core → cloud automatically, with policy and data residency rules preserved at every hop.
Your data center isn't your only compute location.
Data center, edge, distributed sites, or somewhere in between. Orion runs where your workloads actually are, on one compute plane.
