Scale-Out Storage Network Planes

Scale-out Storage Network Planes Huawei scale-out storage architecture, such as the OceanStor 9000 or FusionStorage, relies on three distinct physical or logical network planes to isolate traffic and guarantee predictable performance. These standard planes are the management network, the front-end service network, and the back-end storage network. Consequently, options A, B, and D are the correct choices.

Traffic Roles and Separation Each plane has a dedicated role. The management network handles administrative tasks like CLI/GUI access, SNMP monitoring, and system control traffic. The front-end service network carries the actual client data payloads—application read/write requests connecting hosts or application servers to the storage cluster. The back-end storage network handles internal cluster communication, such as data replication, erasure coding parity calculations, and rebalancing between storage nodes. Keeping these isolated prevents management or client traffic from interfering with critical intra-cluster synchronization.

The "Back-end Service" Distractor Option C ("Back-end service network") is a fabricated distractor designed to confuse candidates who blend the naming conventions of the two data planes. The back-end plane carries internal storage traffic, not service traffic. As noted in community feedback, the back-end network does not provide any service to external clients; it is strictly for intra-cluster data synchronization. If the scenario were flipped to ask about a "front-end storage network," that would similarly be an invalid distractor.

Operational Consequences Failing to properly separate these networks or misassigning ports (for example, routing client traffic onto the back-end plane) drastically degrades cluster performance and stability. If client service traffic floods the back-end storage network, inter-node replication and rebuild operations will be delayed. During a node or disk failure, this congestion severely impacts data protection and system resilience, potentially leading to data unavailability or loss if rebuild times exceed the system's fault tolerance limits.