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Cisco 300-640 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| AI Infrastructure Fundamentals | 20% | - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Describe AI use cases in data center environments - Explain Cisco AI infrastructure solutions and portfolio - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Describe AI and machine learning concepts |
| AI Infrastructure Operations and Troubleshooting | 20% | - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Troubleshoot network, compute, storage, and orchestration issues - Implement performance benchmarking and validation - Manage health, logs, and events - Optimize performance, security, and reliability |
| AI Infrastructure Components and Architecture | 30% | - Evaluate hybrid and multi-cloud AI integration - Evaluate power, cooling, and efficiency requirements - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures |
| AI Infrastructure Deployment and Data Management | 30% | - Deploy and manage AI infrastructure with orchestration tools - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Implement data management and lifecycle for AI workloads - Integrate AI frameworks and applications with Cisco infrastructure |
Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:
1. An end customer plans to deploy an AI fabric in a new data center. Their engineers are more familiar with CLI-based networks and require the capability to automate standardized configuration templates and monitor flows for the fabric. Which data center automation tool meets the requirements?
A) Intersight
B) Nexus Dashboard
C) Digital Network Architecture Center
D) HyperFabric
2. An Intersight administrator plans to deploy new server solutions to several small branch offices across the country. Each location needs at least one chassis. The servers must have redundant CPUs, memory, and 200 Gbps of unified fabric connectivity per compute node. Which hybrid AI compute solution meets the requirements?
A) Cisco UCSXE Unified Edge
B) Cisco UCS C885A M8
C) Cisco UCS S3260
D) Cisco UCS X-Direct
3. An engineer notices excessive broadcast traffic inside a legacy AI server VLAN. Which technology should be implemented to reduce flooding and improve scalability?
A) PAT
B) VXLAN EVPN
C) RIP
D) GRE tunneling
4. A Cisco Nexus switch experiences head-of-line blocking in an RDMA environment. Which mechanism is most effective in reducing this condition?
A) PortFast
B) Virtual output queuing
C) NAT overload
D) Weighted Random Early Detection
5. 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 AI workload configuration to optimize resource allocation (CPU, memory, GPU) for the affected applications.
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) Check the physical cabling and SFP+ transceivers on port 11 of switch B for potential hardware failures or incorrect configurations.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: D |
