Multi-Cluster Networking: RHACM & Submariner for Hybrid AI and Distributed Serving

In modern enterprise architectures, AI training and model serving workloads no longer live on a single Kubernetes cluster. Organizations operate hybrid topologies: sovereign bare-metal GPU clusters on-premise paired with cloud clusters for burst traffic.

Connecting these clusters across standard public Ingress controllers creates severe latency penalties, high egress costs, and security risks. Combining Red Hat Advanced Cluster Management (RHACM) with Submariner establishes a direct, kernel-level networking mesh.

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1. Pitfalls of Public Ingress Gateways in Multi-Cluster Setups

• Latency Overhead: Inter-cluster inference traffic traverses multiple public Load Balancers and ingress controllers, spiking Time-To-First-Token (TTFT) metrics.
• Brittle Service Discovery: Lack of unified DNS requires manual management of external domain routing and public certificates for every model endpoint.
• Public Network Exposure: Sensitive enterprise datasets and inference payloads transit across public gateways, violating zero-trust policies.

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2. The RHACM + Submariner Architecture

Submariner provisions a direct, encrypted overlay network across OpenShift clusters:

• Kernel-Level WireGuard / IPsec Tunnels: Direct L3/L4 pod-to-pod and service-to-service connectivity across infrastructure boundaries.
• Declarative Service Discovery (ServiceExport / ServiceImport): Implementation of the Kubernetes Multi-Cluster Services (MCS) API. A model served on-premise with vLLM is discovered natively across clusters as <service>.<ns>.svc.clusterset.local.
• High-Throughput Routing: Point-to-point data plane connectivity optimizing distributed data pipelines and RAG vector store queries.

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3. Production Engineering in Aperta Curriculums

• AS200 Track (DevOps Platform Engineer — DO432): Centralized multi-cluster operations with RHACM, automated Submariner rollout, OVN-Kubernetes configuration, and policy-based governance.
• AS300 Track (AI Platform Engineer): Federating vLLM/KServe ServingRuntimes across hybrid clusters and securing distributed inference backbones.

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4. Technical Sources & References

• Red Hat Advanced Cluster Management Documentation: RHACM Multi-Cluster Networking
• Submariner Open Source Project: Submariner Architecture & Guides
• Kubernetes Multi-Cluster Services (MCS) API: Kubernetes SIG Multi-Cluster