Score Higher on Verified 300-640 | Implementing Cisco Data Center AI Infrastructure (DCAI) Exam Questions with Answers

The exhibit reports etherErrStats rcvDelta for switch-B/slot-1/switch-ether/port-11 and shows that the receive-error delta has exceeded the configured threshold. This is a physical Ethernet interface error condition on Fabric Interconnect B, port 11. The first troubleshooting action should therefore target the Layer 1 components associated with that port .

Cisco troubleshooting guidance for Fabric Interconnect interfaces recommends checking the physical layer when interfaces report errors or bad packets, including verifying that transceivers are functioning correctly, cabling is intact, and optics are compatible. This establishes option C as the appropriate first action.

Option A begins at the application and compute layers even though the fault identifies a network-interface receive-error condition. Option B examines port-channel configuration, but the alarm identifies physical port 11 rather than a logical port-channel state problem. Option D would be appropriate when PFC congestion or excessive pause behavior is indicated; the exhibit instead reports Ethernet receive errors.

A disciplined troubleshooting sequence begins with the fault domain explicitly identified by telemetry. Physical errors should be eliminated before higher-layer QoS, port-channel, or application analysis is undertaken.

Study Guide Reference: AI Infrastructure Operations and Troubleshooting — UCS network faults, interface telemetry, physical-layer troubleshooting, and network performance analysis.

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NVMe over RoCE uses Remote Direct Memory Access over Converged Ethernet and can employ Priority Flow Control (PFC) to provide lossless behavior between directly connected Ethernet devices. PFC is a link-level IEEE 802.1Qbb mechanism: a congested interface can transmit pause frames for a specific priority to its directly connected upstream peer. This allows the RoCE traffic class to pause without stopping unrelated Ethernet classes.

Cisco's current Intersight guidance for NVMe over RoCEv2 explicitly requires a consistent no-drop class across the network. Cisco recommends enabling the Platinum QoS class, disabling packet drops for that class, and using jumbo MTU values for NVMe/RoCE traffic.

NVMe/TCP and iSCSI operate over conventional TCP/IP. TCP provides end-to-end transport reliability and congestion control, but these protocols do not depend on PFC-based lossless Ethernet between adjacent devices. Fibre Channel has its own native credit-based flow-control mechanisms, but it is not an IP-based storage transport, eliminating option D.

The key distinction is therefore the combination of IP transport, RDMA, and Ethernet priority-based link flow control , which identifies NVMe/RoCE.

Study Guide Reference: AI Infrastructure Components and Architecture — storage technologies including NVMe; high-performance storage networking and RoCE.

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Cisco Nexus Hyperfabric's full-stack AI infrastructure integrates compute, GPU acceleration, high-performance networking, optional enterprise storage, and centralized cloud-based lifecycle management. Cisco identifies the principal components as the Nexus Hyperfabric cloud controller, Cisco 6000/Nexus switching platforms, Cisco UCS GPU/DPU servers equipped with NVIDIA accelerators, and optional Cisco UCS-based VAST storage.

Option C therefore contains the essential architecture: Cisco UCS servers with NVIDIA GPUs, Cisco switching, optional VAST Data storage, and cloud-managed networking .

Option A omits the cloud-controller architecture and does not specifically identify the NVIDIA-based accelerated compute model that characterizes the full-stack AI solution. Option B incorrectly describes cloud management as optional. Cloud-based fabric design, deployment, visibility, and lifecycle control are fundamental elements of Nexus Hyperfabric. Option D omits GPU compute entirely and reduces the solution to networking and software-defined storage, which does not represent the integrated AI stack.

Cisco's architecture is intended to reduce the complexity associated with constructing AI infrastructure manually. Validated cluster templates coordinate compute, networking, storage, optics, cabling, and lifecycle operations while aligning with NVIDIA enterprise AI reference architectures.

Study Guide Reference: AI Infrastructure Components and Architecture — Cisco Hyperfabric, GPU compute, AI networking, storage integration, scalability, and cloud management.

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