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Cisco 300-640 Exam Syllabus Topics:

Section	Objectives
Topic 1: AI Infrastructure Deployment and Operations	- Deployment models 1. Hybrid AI infrastructure integration 2. On-premises AI clusters - Operations and lifecycle management 1. Performance tuning and optimization 2. Monitoring and observability
Topic 2: Compute and Storage for AI Infrastructure	- Storage systems 1. High-throughput storage for AI training data 2. Distributed storage concepts - Compute architecture 1. GPU-based compute nodes 2. HPC-style scaling considerations
Topic 3: Data Center AI Infrastructure Fundamentals	- AI/ML workload requirements in data centers 1. Compute, GPU, and acceleration concepts 2. Data pipeline and workload characteristics
Topic 4: Security and Governance in AI Data Centers	- Infrastructure security 1. Secure access to AI workloads 2. Network segmentation and policy enforcement
Topic 5: Data Center Networking for AI Workloads	- Cisco Data Center networking technologies 1. Cisco Nexus platform concepts 2. Cisco ACI integration concepts - High-performance fabric design 1. Leaf-spine architecture in AI environments 2. Low-latency switching and routing considerations

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q43-Q48):

NEW QUESTION # 43
Drag and Drop Question
An engineer must configure vNIC templates for a UCS X-Series deployment. Drag and drop the policy types from the left onto the corresponding configuration settings on the right. Not all options are used.

Answer:

Explanation:

NEW QUESTION # 44
A solutions architect must implement a monitoring strategy for a new AI/ML data center infrastructure built on Cisco UCS X-Series servers with NVIDIA H100 GPUs, managed by Cisco Intersight. The main objectives are to gain deep visibility into GPU performance, identify resource bottlenecks for AI training workloads, and ensure the overall health and efficiency of the compute environment. Which Cisco Intersight capability is most critical for effectively monitoring this AI- centric infrastructure?

A. Analyze feature automating the deployment and scaling of AI application containers and their underlying Kubernetes infrastructure, which reduces manual monitoring efforts
B. comprehensive health and performance monitoring, which provides real-time telemetry data for UCS servers, including granular metrics for NVIDIA GPUs, which enables direct insights into AI workload execution
C. integration with Cisco Nexus Dashboard for advanced network flow analytics and anomaly detection across the data center fabric, which ensures high-speed data transfer between GPU nodes
D. basic server health reporting, which is limited to CPU and memory statistics, and requires specialized third-party tools for any GPU-specific performance monitoring or diagnostics

Answer: B

Explanation:
Cisco Intersight provides health and performance monitoring for UCS servers, including real-time telemetry and GPU-specific metrics for NVIDIA GPUs. This visibility is essential for identifying bottlenecks, tracking AI training workload behavior, and maintaining the health and efficiency of GPU-accelerated UCS X-Series infrastructure.

NEW QUESTION # 45
A global enterprise is deploying a new AI-driven analytics platform that requires high-performance GPU acceleration, large memory capacity, and robust virtualization support. The current compute environment must co-exist with the newly purposed GPU-enabled workload. This environment will continue to grow, so the customer wants to scale out the resources as needed. Which Cisco product meets the requirements?

A. UCS M-series
B. UCS C-series Standalone
C. Unified Edge
D. UCS X-series

Answer: D

Explanation:
Cisco UCS X-Series is designed for scalable, modular compute environments that support GPU- enabled workloads, high memory capacity, virtualization, and coexistence with existing infrastructure. Its modular architecture allows the enterprise to expand resources as AI workload demands grow.

NEW QUESTION # 46
A network engineer analyzes RoCEv2 traffic flows in an AI training cluster and notices that all RoCEv2 packets have the Don't Fragment bit set in the IP header. Why must RoCEv2 set the DF bit in all packets?

A. to indicate to intermediate switches that the packet contains RDMA traffic requiring special handling
B. to ensure that packets always take the same path through ECMP routing for consistent latency
C. to prevent IP fragmentation that would break the InfiniBand sequence numbering and ordering guarantees
D. to enable Path MTU Discovery so that the optimal packet size can be negotiated

Answer: C

Explanation:
RoCEv2 carries InfiniBand transport semantics over UDP/IP, and IP fragmentation would disrupt the expected packet sequencing and ordering behavior required by RDMA. Setting the Don't Fragment bit prevents intermediate devices from fragmenting RoCEv2 packets, preserving reliable RDMA transport behavior across the AI training fabric.

NEW QUESTION # 47
Refer to the exhibit. Users report delayed response times and network latency when running certain AI workloads on a specific Cisco UCS Intersight Managed Mode Domain. Based on the fault message and reported symptoms, which troubleshooting action must be taken first to address the network latency issues?

A. Review the pause frame counters for signs of congestion on Fabric Interconnect B Port 11.
B. Check the physical cabling and SFP+ transceivers on port 11 of switch B for potential hardware failures or incorrect configurations.
C. Examine the UCS fabric interconnect configuration for port-channel 11 on Fabric Interconnect B.
D. Review the AI workload configuration to optimize resource allocation (CPU, memory, GPU) for the affected applications.

Answer: B

Explanation:
The fault shows a receive error statistics threshold crossing on switch B port 11. Because receive errors on a physical interface commonly indicate cabling, transceiver, or physical-layer issues, the first troubleshooting step is to inspect the physical connection and SFP+ components on the affected port before investigating workload or higher-layer configuration.

NEW QUESTION # 48
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