Sovereign AI Mobility for Containerized Workloads
Move AI applications and their state across Kubernetes and OpenShift environments
AI applications need the freedom to move when data residency requirements, provider terms, or capacity needs change. For a private knowledge assistant or an AI agent, changing location also means preserving the business data and application state that make it useful. RackWare SWIFT gives enterprises a repeatable way to move containerized AI services into infrastructure they choose and retain the ability to move again.
The demand for control is measurable. Capgemini’s 2026 research found that 54% of surveyed organizations prioritize data sovereignty.¹ In IBM’s 2026 survey of 1,000 senior executives, 68% found meeting residency and sovereignty requirements across geographies challenging.² Portability makes approved hosting choices practical as those requirements evolve.
Move the service and its knowledge
Retrieval-augmented generation (RAG) lets an AI application search enterprise content before asking a model to answer. Its vector database holds the searchable knowledge index; chat history and configuration preserve the user experience. Agents can add session memory and workflow checkpoints. SWIFT replicates selected application objects and supported persistent-volume data so these components can move together.
How SWIFT enables portability
SWIFT supports cross-cloud, cross-platform, and cross-version moves, mapping storage and service settings to the destination. It runs outside managed clusters without persistent production agents. Encrypted, compressed delta syncs reduce repeated transfers; direct source-to-target sync can avoid a staging storage pool. Optional registry replication helps make container images available. Migration uses a pre-provisioned target cluster with compatible runtimes and access to required model artifacts.
Use case: Moving a private knowledge assistant
An enterprise wants its internal knowledge assistant to run in an approved region or private cloud. The application combines an interface, retrieval services, a vector index, and conversation history. The destination must preserve those assets and keep access to the chosen model.
The team prepares a Kubernetes or OpenShift cluster in that location. SWIFT maps storage and service settings, replicates application objects and persistent data, and sequences required platform services before the application. Successive delta syncs limit the final transfer. The team tests knowledge retrieval and existing conversations before cutover, reducing manual reconstruction while changing where the service runs.
Validated portability with a RAG application
In a RackWare lab, a conversational RAG application replicated from Oracle Container Engine for Kubernetes (OKE) to a pre-provisioned Google Kubernetes Engine (GKE) cluster. The stack included Qdrant for vector search and Qwen model serving through KServe and vLLM. Ordered recovery restored prerequisites, the knowledge index, and conversation data; prior chats were visible on GKE.
Extend mobility across the AI estate
AI also runs in VMs and on physical servers. The RackWare Management Module (RMM) complements SWIFT with mobility for supported server workloads, including moves between hypervisors and bare metal. Supported source and target combinations, AI runtimes, and provisioning integrations determine each migration path.
Continue protection after the move
The same SWIFT deployment can support ongoing backup and disaster recovery. A published, anonymized public-sector example shows portable OKE backups and restore tests in temporary clusters, with workflows retained inside the customer’s Oracle Cloud Infrastructure (OCI) tenancy.
Choose one AI service and demonstrate its move into an approved destination.
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