Relevant 300-640 Questions & Exam 300-640 Preview

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Cisco 300-640 Exam Syllabus Topics:

Section	Weight	Objectives
AI Infrastructure Fundamentals	15%	- AI Ecosystem Components - AI Infrastructure Requirements - AI Workload Characteristics - GPU Architecture and Types
AI Infrastructure Security and Compliance	10%	- Security Best Practices - Access Control and Authentication - Compliance Considerations
AI Infrastructure Operations	20%	- Performance Optimization - Troubleshooting Common Issues - Monitoring and Management Tools - Capacity Planning
Cisco AI Infrastructure Architecture	30%	- Storage Architecture Considerations - Network Architecture for AI Workloads - Hyperconverged Infrastructure for AI - Cisco UCS AI Infrastructure Solutions
AI Infrastructure Deployment	25%	- Network Switch Configuration - Cabling and Connectivity - GPU Server Configuration - Hardware Installation and Configuration - Storage Configuration for AI

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2026 Cisco High Pass-Rate Relevant 300-640 Questions

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q58-Q63):

NEW QUESTION # 58
To support growing AI workload requirements, a regional medical practice is adding new X9516 X-Fabric module, UCS PCI Mezz cards, and UCS X580p PCIe nodes to their existing X-Series chassis. Which two administrative actions must be taken before the X-Fabric module is added to the chassis? (Choose two.)

A. Power down all IFMs in the chassis.
B. Install UCS PCI Mezzanine cards in X-Series blades.
C. Disconnect cabling between IFMs and fabric interconnects.
D. Disconnect device connector.
E. Power down all blades that would connect to the X-Fabric modules.

Answer: B,E

Explanation:
Before adding the X9516 X-Fabric module, the affected X-Series blades must be powered down because the X-Fabric connectivity path requires hardware installation and cannot be safely introduced while the connected compute nodes are running. The UCS PCI Mezzanine cards must also be installed in the blades so they can physically connect through the X-Fabric module to the X580p PCIe nodes for GPU expansion.

NEW QUESTION # 59
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. Check the physical cabling and SFP+ transceivers on port 11 of switch B for potential hardware failures or incorrect configurations.
B. Examine the UCS fabric interconnect configuration for port-channel 11 on Fabric Interconnect B.
C. Review the pause frame counters for signs of congestion on Fabric Interconnect B Port 11.
D. Review the AI workload configuration to optimize resource allocation (CPU, memory, GPU) for the affected applications.

Answer: A

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 # 60
A company deploys a Cisco UCS environment to host AI inferencing workloads that demand low latency, high throughput, and efficient resource utilization. Which set of actions must be taken to deploy a high-performance fabric within the Cisco UCS infrastructure?

A. Implement a dual-fabric design with two Cisco Fabric Interconnects, and use 100 Gb Ethernet for server-to-fabric connectivity.
Configuring port channels for uplink connections.
B. Use a single Cisco Fabric Interconnect in a standalone configuration.
Connect all UCS servers directly to it using 10 Gb Ethernet.
C. Deploy a Cisco MDS 9000 Series Switch for Fibre Channel connectivity to storage.
Use a Cisco Fabric Interconnect for management traffic only.
D. Connect UCS servers to a Cisco Nexus 3000 Series Switch using 100 Gb Ethernet.
Configure a separate management network using a dedicated Cisco Catalyst switch.

Answer: A

Explanation:
A dual-fabric design with redundant Cisco Fabric Interconnects provides high availability, bandwidth scale, and resilient server-to-fabric connectivity. Using 100 Gb Ethernet and port- channel uplinks supports the low-latency, high-throughput fabric required for AI inferencing workloads while improving utilization and avoiding single points of failure.

NEW QUESTION # 61
Which type of Cisco Intersight profile, when deployed to fabric interconnects, includes the configuration settings for ports, VLANs, and VSANs?

A. UCS Domain profiles
B. UCS Server profiles
C. UCS Chassis profiles
D. Unified Edge profiles

Answer: A

Explanation:
A UCS Domain profile is deployed to fabric interconnects in Cisco Intersight Managed Mode and contains the domain-level configuration, including port policies, VLANs, VSANs, network connectivity, and other fabric interconnect settings.

NEW QUESTION # 62
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?

A. using the maximum number of CPU cores to support the virtualization overhead
B. configuring the server with the minimum amount of RAM to reduce initial costs
C. implementing a redundant power supply configuration to ensure high availability
D. selecting the appropriate Nexus Fabric and its configuration to minimize latency

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 # 63
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