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Cisco 300-640 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Infrastructure Deployment and Data Management | 30% | - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Deploy and manage AI infrastructure with orchestration tools - Implement data management and lifecycle for AI workloads - Integrate AI frameworks and applications with Cisco infrastructure - Configure compute and storage using Cisco UCS: profiles, policies, Intersight |
| Topic 2: AI Infrastructure Operations and Troubleshooting | 20% | - Manage health, logs, and events - Optimize performance, security, and reliability - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Implement performance benchmarking and validation - Troubleshoot network, compute, storage, and orchestration issues |
| Topic 3: AI Infrastructure Components and Architecture | 30% | - Evaluate hybrid and multi-cloud AI integration - 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 - Evaluate power, cooling, and efficiency requirements |
| Topic 4: AI Infrastructure Fundamentals | 20% | - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Explain Cisco AI infrastructure solutions and portfolio - Describe AI and machine learning concepts - Describe AI use cases in data center environments |
Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:
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. Unified Edge
- B. UCS M-series
- C. UCS X-series
- D. UCS C-series Standalone
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An engineer made changes to the corporate DNS, which caused a Cisco UCS X-Series domain to lose connectivity to Intersight. To restore connectivity, the management interface DNS and NTP settings must be updated using the device console UI. Which configuration change must be made in Intersight to allow the updated DNS configuration to persist?
- A. Create a device connector policy and apply it to the blade chassis.
- B. Create a network connectivity policy and apply it to the blade chassis.
- C. Edit the IMC access policy associated to the fabric interconnects.
- D. Edit the domain profile deployed to the fabric interconnect.
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A network team is configuring quality of service (QoS) for RoCEv2 traffic on a VXLAN fabric. The team must ensure that congestion notification packets (CNP) generated by storage targets are never dropped in the network, as these packets are critical for congestion control feedback. How must CNP packets be handled in the QoS configuration to ensure reliable delivery?
- A. Classify CNP packets to a high-priority queue using their DSCP marking.
- B. Configure CNP packets to use the same queue as regular RoCEv2 data traffic.
- C. Enable Priority Flow Control specifically for CNP packets on a dedicated CoS value.
- D. Apply traffic shaping to CNP packets to prevent them from causing additional congestion.
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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 compute and GPU resources selected must provide direct GPU to GPU access leveraging NVLink technology.
Which set of products meets the requirements?
- A. UCS C845A M8 with AMD MI210 GPU
- B. UCS C885A M8 with NVIDIA H200 GPU
- C. UCS C220 M8 with NVIDIA A16 GPU
- D. UCS C240 M8 with NVIDIA L40 GPU
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A network architect designs a Cisco AI fabric with spine-leaf topology. What is the primary advantage of this architecture for AI training workloads?
- A. Reduced need for IP addressing
- B. Simplified wireless integration
- C. Predictable low-latency east-west traffic
- D. Elimination of routing protocols
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