How to Migrate GPU Inference to a European Sovereign Cloud: Providers, Costs, and the Platform Layer

Migrating GPU inference to a European sovereign cloud requires separating GPU capacity selection from the deployment platform layer, with providers such as Scaleway, OVHcloud, Nebius, IONOS, StackIT, and T-Systems offering varying H100, H200, or newer GPU options. The piece argues that hosting workloads in a European region operated by a US hyperscaler provides data residency but not complete jurisdictional sovereignty because US parent companies may remain subject to the CLOUD Act, while European providers can better align legal control, operations, and data processing with EU requirements. It states that inference performance should generally remain comparable because the underlying NVIDIA hardware is identical, and EU-based serving can reduce latency for European users, although interconnect quality, storage speed, GPU availability, and autoscaling capabilities require validation. Recommended migrations use portable containers, Kubernetes, NVIDIA GPU Operator, open serving runtimes such as vLLM, TGI, or Triton, EU-based supporting services, infrastructure as code, and dual-running production traffic before cutover. Published European GPU prices are described as competitive with AWS, but utilization, batching, quantization, scale-to-zero policies, and reservation planning have greater effects on total cost than hourly rates alone. The article presents cloud-agnostic platforms such as Qovery, alongside tools including KServe, SkyPilot, and NVIDIA Run:ai, as ways to preserve deployment workflows across providers while maintaining a direct cloud contract, and emphasizes documenting every component, subprocessor, access path, log, backup, and control-plane interaction to demonstrate sovereignty to auditors.

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