300-640 Leak Questions

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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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.

Cisco Nexus Dashboard is the appropriate platform for operating and automating Cisco Nexus-based data center fabrics while retaining an NX-OS/CLI-oriented architecture. Nexus Dashboard Fabric Controller provides centralized provisioning, configuration management, automation, templates, monitoring, and lifecycle functions for Nexus fabrics. Cisco explicitly describes NDFC as the comprehensive automation and management platform for Cisco Nexus and MDS infrastructure.

The template requirement is also directly supported. Nexus Dashboard allows policies and configuration templates to be defined centrally and deployed consistently to one or multiple fabrics. For flow visibility, Nexus Dashboard can collect fabric telemetry and reconstruct traffic paths, including packets, drops, anomalies, and flow behavior across multiple switches.

Cisco Catalyst Center—formerly DNA Center—is primarily associated with enterprise campus and access networks rather than Nexus data center AI fabrics. Intersight specializes in compute and infrastructure lifecycle management, particularly UCS. Hyperfabric provides highly automated cloud-managed networking but deliberately abstracts much of the conventional CLI-centric operational model.

Nexus Dashboard therefore best satisfies both requirements: standardized network automation and detailed fabric-flow monitoring while remaining aligned with traditional Nexus operational practices.

Study Guide Reference: AI Infrastructure Deployment and Data Management — Cisco Nexus Dashboard, fabric automation, configuration templates, and telemetry.

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The Cisco UCS C885A M8 contains six 3000-W 54-V AC power supplies and normally supports an N+2 power configuration . In the scenario, three PSUs are connected to each independent power grid. Losing one complete grid therefore leaves only three operational 54-V PSUs.

Cisco's installation and service documentation specifies the resulting behavior precisely: when only three 54-V AC PSUs remain available, the server continues operating but enters a reduced-performance condition in which power to each GPU is capped at 60 percent . Cisco further states that four or more 54-V power supplies allow operation at full performance.

Consequently, the system does not immediately shut down, eliminating option A. A graceful operating-system shutdown is also not automatically initiated, eliminating D. Option C is incorrect because three active supplies are insufficient for full-performance operation on this platform.

This behavior allows the server to remain available during a significant power-domain failure while keeping its consumption within the capacity of the remaining PSUs. The operational tradeoff is reduced accelerator performance until adequate power redundancy is restored.

Study Guide Reference: AI Infrastructure Operations and Troubleshooting — UCS C885A M8 power redundancy, degraded operation, GPU power management, and availability.

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