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Cisco 300-640 Exam Syllabus Topics:

SectionWeightObjectives
AI Infrastructure Operations20%- Monitoring and Management Tools
- Capacity Planning
- Troubleshooting Common Issues
- Performance Optimization
AI Infrastructure Security and Compliance10%- Security Best Practices
- Compliance Considerations
- Access Control and Authentication
AI Infrastructure Deployment25%- Network Switch Configuration
- Storage Configuration for AI
- Hardware Installation and Configuration
- GPU Server Configuration
- Cabling and Connectivity
Cisco AI Infrastructure Architecture30%- Network Architecture for AI Workloads
- Hyperconverged Infrastructure for AI
- Cisco UCS AI Infrastructure Solutions
- Storage Architecture Considerations
AI Infrastructure Fundamentals15%- AI Infrastructure Requirements
- AI Ecosystem Components
- GPU Architecture and Types
- AI Workload Characteristics

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q45-Q50):

NEW QUESTION # 45
A corporate network administrator manages a HyperFabric AI environment and wants to receive email notifications about assertions in the fabric. The administrator sets up a recipient email endpoint under the notification endpoints in the controller, but notifications are not received.
Which two configurations cause the issue? (Choose two.)

Answer: A,D

Explanation:
Email endpoints must be verified before they can receive HyperFabric notifications, and the endpoint must also be included with the relevant fabric in the notification policy. Creating the email endpoint alone does not activate assertion notifications for a fabric until both of these notification requirements are completed.


NEW QUESTION # 46
Which components are part of the HyperFabric AI solution?

Answer: C

Explanation:
HyperFabric AI combines Cisco UCS servers with NVIDIA GPUs, Cisco Nexus 6000 Series switches, optional VAST Data storage, and cloud-managed networking to provide an integrated AI infrastructure solution for training and inference workloads.


NEW QUESTION # 47
A data center is deploying an AI infrastructure for LLM training and model inference. This infrastructure requires high GPU density, low-latency interconnects, and the ability to scale compute resources. When considering the Cisco UCS C885A M8 Rack Server for the deployment, which design aspect is the most critical for achieving optimal performance and scalability in this environment?

Answer: D

Explanation:
For UCS C885A M8 servers running LLM training and inference workloads, the surrounding Nexus fabric design is critical because GPU-dense systems depend on low-latency, high- bandwidth, lossless network connectivity for scale-out performance. Selecting and configuring the correct Nexus fabric minimizes communication delays between compute nodes and enables the AI infrastructure to scale efficiently.


NEW QUESTION # 48
A network architect designs a Cisco AI fabric with spine-leaf topology. What is the primary advantage of this architecture for AI training workloads?

Answer: D

Explanation:
AI workloads generate massive east-west traffic between compute nodes. Spine-leaf designs provide predictable latency and scalable bandwidth because each leaf switch maintains equal- cost paths to all spines. Routing protocols are still required, IP addressing remains necessary, and wireless integration is unrelated to AI fabric performance requirements.


NEW QUESTION # 49
An administrator configures VXLAN EVPN in a Cisco AI data center fabric. The requirement is to provide Layer 2 adjacency across multiple leaf switches while maintaining scalable control-plane learning. Which protocol fulfills this function?

Answer: B

Explanation:
BGP EVPN provides scalable control-plane MAC and IP route advertisement for VXLAN fabrics.
It eliminates excessive flooding associated with traditional Layer 2 networks and supports efficient multi-tenant AI infrastructures. STP only prevents loops, OSPF is a Layer 3 routing protocol, and HSRP provides gateway redundancy rather than overlay endpoint learning.


NEW QUESTION # 50
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