Bridge by Armada + NVIDIA Run:ai: Commercial or Open Source, Your Call
· 4 min read
On October 13, NVIDIA released the complete Run:ai platform as open source. KAI Scheduler, the scheduling engine behind Run:ai, has been open source since 2025. The new release adds the rest of the platform:
- Run:ai control plane and cluster services, so the full integrated platform can be self-hosted, and installed from a single Helm chart
- GPU Fractioning Operator, which brings CUDA-native GPU fractions with hard memory isolation to Kubernetes, plus per-pod metrics
- KAI Resource Management, the organizational layer of projects, departments, quotas, and node pools
- Workload Map, a common contract for managing PyTorchJob, RayCluster, KServe, Dynamo, and custom workload types without hardcoding each one
Production-grade GPU orchestration no longer requires a license.
For neoclouds and sovereign cloud providers building on Armada Bridge, that's good news. Bridge already integrates with commercial NVIDIA Run:ai, and the same integration now extends to the open source release. Tenants who want Run:ai can get it without a procurement step, and every Bridge deployment gets a lower total cost of ownership.