Pass the Cisco CCNP Data Center 300-640 Questions and answers with Dumpstech

RoCEv2 transports the InfiniBand transport protocol over UDP/IP, allowing RDMA traffic to traverse Layer 3 networks. The RDMA transport layer preserves packet-level sequencing, reliability, and ordering semantics that are inappropriate for arbitrary IP fragmentation. Consequently, RoCEv2 traffic is designed to traverse the network without IP fragmentation, making option D the intended technical answer. NVIDIA documentation confirms that RoCEv2 places the InfiniBand transport protocol behind UDP and IP rather than using the native InfiniBand network-layer header.

A consistent end-to-end MTU is therefore essential in GPU fabrics. AI clusters commonly use jumbo frames, and every switch interface, port channel, Layer 3 interface, and server NIC along the path must support the configured packet size. Unexpected fragmentation is incompatible with the deterministic behavior required by high-performance RDMA workloads.

Option A identifies a general IPv4 consequence of setting DF—Path MTU Discovery can use DF—but it is not the fundamental RoCE transport requirement tested here. Option B is incorrect because DF does not classify packets as RDMA. Option C is also incorrect because ECMP path selection is normally determined by packet-header hashing; the DF flag does not force packets onto a single path.

Study Guide Reference: AI Infrastructure Deployment and Data Management — RoCEv2, MTU design, lossless transport, and high-performance Ethernet.

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A UCS Domain Profile provides the configuration model for a pair of Cisco UCS Fabric Interconnects operating in Intersight Managed Mode. Cisco explicitly states that the Domain Profile allows configuration of FI ports and port channels and defines the VLANs and VSANs used by the domain. This makes option C an exact match for the functionality described.

The Domain Profile references reusable policies rather than embedding every setting directly. VLAN and VSAN policies are associated during the VLAN and VSAN configuration stage, Port Policies are assigned during port configuration, and additional management or compute-related domain policies are attached subsequently. When the Domain Profile is deployed, Intersight applies the assembled configuration to the assigned Fabric Interconnect domain.

A Chassis Profile configures chassis-specific properties and cannot replace domain-level network configuration. A Server Profile configures an individual server's identity, boot configuration, vNICs, vHBAs, firmware, BIOS, storage, and similar server-specific characteristics. Unified Edge uses its own distributed edge management model and is not the FI configuration object in question.

This distinction is fundamental in Intersight Managed Mode: Domain Profiles configure the Fabric Interconnect domain, while Server Profiles configure individual compute resources attached to that domain.

Study Guide Reference: AI Infrastructure Deployment and Data Management — Cisco Intersight, UCS Domain Profiles, VLAN/VSAN policies, and port configuration.

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Cisco's validated guidance for connecting VAST Data storage through an ACI fabric explicitly configures the RDMA storage class with Weighted Random Early Detection and Congestion Notification enabled . This makes option A directly consistent with Cisco's documented configuration.

In Cisco's VAST Data ACI design example, storage traffic arrives marked with DSCP 26 and is assigned to the Level2 QoS class. PFC is enabled for the corresponding no-drop DSCP, bandwidth is reserved for storage traffic, the congestion algorithm is configured as WRED, and congestion notification is enabled.

WRED and ECN-style congestion notification work together to detect developing queue pressure before buffers overflow. Rather than waiting for tail-drop conditions, the network can mark congestion-capable traffic so RoCEv2 endpoints reduce their transmission rates. PFC provides the complementary no-drop behavior when congestion becomes sufficiently severe.

Option B disables the required congestion signaling. Options C and D use Tail Drop, which Cisco's documented VAST RDMA storage class does not use. Tail Drop is instead shown in the same Cisco design for control-plane and ordinary traffic classes where lossless RDMA behavior is not required.

This configuration is therefore not merely a generic QoS preference; it directly follows Cisco's published ACI-to-VAST storage design.

Study Guide Reference: AI Infrastructure Deployment and Data Management — QoS, ECN/WRED, PFC, RDMA storage, and lossless fabric configuration.

NVIDIA Collective Communications Library (NCCL) is the appropriate framework for validating communication performance between NVIDIA GPU nodes. NCCL provides highly optimized implementations of collective operations such as AllReduce, AllGather, Reduce, Broadcast, and ReduceScatter. These operations closely represent the communication patterns generated by distributed AI training and therefore provide much more meaningful validation of GPU-cluster performance than conventional network-throughput tests.

NCCL-based benchmarks can reveal whether GPU-to-GPU communication is achieving expected bandwidth and latency across NVLink, PCIe, and the external backend network. They are particularly useful when validating RoCEv2 fabrics because distributed training performance depends on collective communication efficiency rather than simple host-to-host TCP throughput.

iPerf measures conventional TCP or UDP network performance between hosts and is useful for basic network validation, but it does not exercise NVIDIA GPU collective communications. Spirent and Ixia provide sophisticated packet-generation and network-testing platforms, yet they test the network primarily from a packet-forwarding perspective rather than measuring actual GPU collective-operation behavior.

For a newly deployed NVIDIA AI cluster, NCCL benchmarking therefore provides workload-representative validation of the end-to-end GPU communication architecture and can expose problems involving topology, NIC configuration, congestion control, bandwidth imbalance, or fabric design.

Study Guide Reference: AI Infrastructure Operations and Troubleshooting — performance benchmarking, NVIDIA GPU communications, backend-fabric validation, and distributed AI workload testing.

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Traffic Analytics and Flow Telemetry are mutually exclusive flow-collection modes within Cisco Nexus Dashboard. Cisco's current Nexus Dashboard documentation identifies both under Flow Collection settings and states that Flow Telemetry must be disabled at the fabric level before Traffic Analytics can be enabled.

Traffic Analytics automatically discovers services and visualizes conversations based primarily on Layer 4 information. It provides visibility into network characteristics such as congestion, latency, and drops, which directly matches the monitoring requirements in the scenario. Cisco's Nexus Dashboard Insights guidance likewise states that if Flow Telemetry is already active, it must first be disabled for the relevant sites before Traffic Analytics is selected.

Delta Analysis is an assurance/comparison capability and is not the mutually exclusive collection mode described here. Connectivity Analysis performs reachability and path-oriented diagnostics. SNMP traps remain a separate event-notification mechanism and are not displaced by Traffic Analytics.

The operational distinction matters because Traffic Analytics and Flow Telemetry use different approaches to flow collection and analysis. An administrator cannot simply enable both collection modes simultaneously and expect them to operate in parallel on the same fabric configuration.

Study Guide Reference: AI Infrastructure Operations and Troubleshooting — Nexus Dashboard monitoring, telemetry, congestion analysis, latency, and packet-drop visibility.

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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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In Cisco Intersight Managed Mode, Fabric Interconnect physical port roles and port-channel definitions are configured through the Port Policy . Cisco's current Intersight configuration documentation states that a Port Policy configures ports and port roles on a Fabric Interconnect and permits administrators to enable or disable individual ports or port channels. Supported roles include Ethernet uplinks and Ethernet uplink port channels.

The Port Policy is subsequently associated with the UCS Domain Profile. Cisco documents that a Domain Profile configures an FI pair through reusable policies and controls ports, port channels, VLANs, and VSANs. During Domain Profile creation, the administrator attaches the appropriate Port Policy to each Fabric Interconnect.

A LAN Connectivity Policy is used primarily at the server-profile level to define vNIC connectivity. A Network Connectivity Policy configures DNS-related server-management settings rather than FI uplink topology. An Ethernet Network Group Policy defines VLAN groups associated with Ethernet connectivity and can be referenced by uplink configurations, but it does not itself create the FI port channel.

Consequently, the policy that must be changed to build the multiple-100-GbE uplink port channel is the Port Policy .

Study Guide Reference: AI Infrastructure Deployment and Data Management — Intersight Managed Mode, UCS Domain Profiles, Fabric Interconnect port configuration, and uplink resiliency.

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When an AI environment contains both local and external resources, workload distribution enables computational jobs to be placed or divided across multiple locations according to performance, capacity, latency, data residency, security, and cost requirements. This is a defining capability of hybrid AI infrastructure rather than an isolation mechanism.

Cisco defines hybrid AI infrastructure as combining on-premises and cloud resources within a common operating model. Workloads can use cloud capacity for burst training or experimentation while sensitive data or steady inference operations remain on premises. Cisco further identifies workload mobility, secure connectivity, and data synchronization as explicit requirements for hybrid AI deployment in DCAI objective 2.5. Cisco material on AI workload orchestration likewise describes workload execution across on-premises, cloud, and hybrid environments.

Option A unnecessarily isolates functions rather than distributing them. Option C contradicts hybrid automation by restricting operations locally. Option D describes security-policy enforcement, which is important but does not define workload distribution.

Accordingly, B is the technically correct response. It also corrects the answer indicated in the supplied source document, which lists C despite Cisco's current hybrid-infrastructure guidance.

Study Guide Reference: 1.0 AI Fundamentals and Applications — 1.4.b Hybrid; 2.5 Hybrid AI deployment and workload mobility.

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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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A rail-optimized topology is specifically engineered for large GPU clusters where collective communication performance and minimum inter-GPU latency are critical. In a rail-optimized design, corresponding GPU/NIC interfaces across compute nodes attach to the same rail switch. This allows communication between GPUs of the same rank to remain on a single leaf or rail switch whenever possible, eliminating unnecessary spine traversal and reducing network hops.

Cisco's AI/ML networking guidance gives a directly applicable design example: a rail-optimized, nonblocking architecture connecting 512 GPUs in 64 nodes, with eight GPUs per node . The design uses eight rail/leaf switches and four spine switches and maintains nonblocking bandwidth while optimizing GPU collective communication. Cisco explicitly states that rail-optimized design is recommended for NVIDIA GPU environments.

A conventional leaf-spine architecture can certainly provide high performance and nonblocking bandwidth, but option C is more specific to the requirement for the lowest possible GPU-to-GPU latency at this scale. Flat Layer 2 does not provide the required scalable fabric architecture, while a traditional three-tier model introduces additional hops and potential oversubscription.

Study Guide Reference: 2.0 AI Infrastructure Components and Architecture — 2.1 Evaluate network deployment based on bandwidth, latency, redundancy, scalability, and security.