Bridge by Armada now integrates with Dataiku, the enterprise AI platform data teams use to prepare data, build models, and govern AI projects. Neoclouds and sovereign GPU cloud providers that use Bridge can now offer Dataiku to their tenants directly from the Bridge Marketplace, running on the provider's own GPU infrastructure.
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:
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.
How Armada's GPU-as-a-Service Management Platform Orchestrates AI Token Factories at Scale
The phrase "token factory" has moved from marketing metaphor to operational reality. Neoclouds and sovereign cloud providers are assembling clusters of hundreds — or thousands — of GPU nodes, connecting them over high-speed interconnect fabrics, shared across dozens of tenants simultaneously: each with their own isolated network, dedicated storage quota, optional private NVLink or IB partition, and bespoke mix of training, fine-tuning, and inference workloads.
Relying solely on Kubernetes Namespaces or vClusters for multi-tenant isolation in GPU clouds is risky — especially when hosting untrusted or external workloads.
In September 2024, Wiz discovered a critical NVIDIA Container Toolkit vulnerability (CVE-2024-0132) that allowed GPU containers to escape soft isolation and gain root access to the host. This flaw impacted over one-third of GPU-enabled environments and exposed the limits of Kubernetes-based isolation.
Soft isolation is not secure isolation. For environments like Neoclouds, NVIDIA Cloud Partners (NCPs), or regulated industries, only hard or hybrid isolation strategies — such as dedicated Kubernetes clusters, MIG-based GPU partitioning, VPCs, VxLAN, VRFs, KVM virtualization, IB P-KEY, and NVLink partitioning — can protect against container escapes.