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Cisco Implementing Cisco Data Center AI Infrastructure : 300-640

Updated: Aug 03, 2026

Q & A: 82 Questions and Answers

300-640 Braindumps VCE
  • Exam Code: 300-640
  • Exam Name: Implementing Cisco Data Center AI Infrastructure

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Cisco 300-640 Exam Syllabus Topics:

SectionWeightObjectives
AI Infrastructure Fundamentals20%- Describe AI use cases in data center environments
- Explain Cisco AI infrastructure solutions and portfolio
- Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring
- Describe AI and machine learning concepts
- Describe types of AI infrastructure: on-premises, cloud, hybrid, edge
AI Infrastructure Operations and Troubleshooting20%- Implement performance benchmarking and validation
- Troubleshoot network, compute, storage, and orchestration issues
- Optimize performance, security, and reliability
- Manage health, logs, and events
- Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts
AI Infrastructure Components and Architecture30%- Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures
- Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS
- Evaluate hybrid and multi-cloud AI integration
- Evaluate power, cooling, and efficiency requirements
- Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability
AI Infrastructure Deployment and Data Management30%- Configure compute and storage using Cisco UCS: profiles, policies, Intersight
- Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics
- Implement data management and lifecycle for AI workloads
- Integrate AI frameworks and applications with Cisco infrastructure
- Deploy and manage AI infrastructure with orchestration tools

Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:

1. A Cisco AI cluster requires segmentation between multiple research teams sharing the same physical infrastructure. Which solution provides scalable tenant isolation?

A) Static NAT
B) Hub-and-spoke WAN
C) VLAN-only design
D) VXLAN overlays


2. 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) 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
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) 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


3. 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.


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


5. Which function is provided through natural language processing?

A) annotation of data transmission protocols for device authorization
B) filtration of duplicate entries from transaction records
C) automated conversion of spoken or written content into structured data
D) compression of large configuration files for storage efficiency


Solutions:

Question # 1
Answer: D
Question # 2
Answer: D
Question # 3
Answer: Only visible for members
Question # 4
Answer: C
Question # 5
Answer: C

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