Integrate once, reach every sovereign cloud provider in Virt8ra

For a federated AI vendor serving regulated industries, customers have already chosen their sovereign provider before the AI vendor arrives IONOS, Arsys, CloudFerro, OKTAWAVE and the others are fixed infrastructure decisions. Without a common deployment substrate, each sovereign European cloud requires its own integration layer: not a practical go-to-market model across a fragmented continental landscape. Three technical requirements had to be met simultaneously at the infrastructure layer: latency tolerance across national backbones and public peering; data sovereignty through VM placement at the designated provider; and workload portability the same VM-level deployment definition spinning up FedX cleanly across heterogeneous hardware mixes of CPU compute, GPU servers, and edge nodes.

OpenNebula plays a clearly defined role in E-Group's stack: it is the layer that deploys FedX virtual machines across multiple European providers through one common interface and manages their lifecycle from there. Latency handling, data sovereignty at the workload layer, and protocol design remain FedX concerns; OpenNebula handles where and how VMs are provisioned. The result: E-Group integrates once with OpenNebula and the Virt8ra ecosystem and reaches IONOS, Arsys (Spain and Germany), CloudFerro, OKTAWAVE, OBIT, Kontron, Infobip, and Gdansk University regardless of the underlying hardware mix, without per-provider engineering.

The Virt8ra deployment proved the model works: a single FedX-on-OpenNebula integration reaches the entire Virt8ra-participating provider ecosystem across six European countries. The roadmap extends this from demo configuration to production: harden the FedX-on-OpenNebula stack across the existing partner footprint so each provider can host a production FedX node; extend the certified provider set as Virt8ra grows; and longer term, offer FedX as a managed service consumable directly through OpenNebula-powered sovereign European infrastructure transforming a project-based deployment into a repeatable, scalable federated AI service.