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

> How to connect on-premise and cloud OpenShift clusters via direct L3/L4 WireGuard tunnels using RHACM and Submariner.

- **Date de publication** : 2026-09-11T08:30:00.000Z

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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](https://docs.redhat.com/en/documentation/red_hat_advanced_cluster_management_for_kubernetes/)
* **Submariner Open Source Project:** [Submariner Architecture & Guides](https://submariner.io/)
* **Kubernetes Multi-Cluster Services (MCS) API:** [Kubernetes SIG Multi-Cluster](https://github.com/kubernetes-sigs/mcs-api)

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*Source : https://aperta.io/radar/2026-09-11-rhacm-submariner-multi-cluster-networking-hybrid-ai/ — Aperta Scientia Tech Radar*