Last Updated: Jul 23, 2026
No. of Questions: 82 Questions & Answers with Testing Engine
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| Section | Weight | Objectives |
|---|---|---|
| AI Infrastructure Components and Architecture | 30% | - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate hybrid and multi-cloud AI integration - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability - Evaluate power, cooling, and efficiency requirements - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures |
| AI Infrastructure Fundamentals | 20% | - Describe AI use cases in data center environments - 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 - Explain Cisco AI infrastructure solutions and portfolio |
| AI Infrastructure Deployment and Data Management | 30% | - Deploy and manage AI infrastructure with orchestration tools - Integrate AI frameworks and applications with Cisco infrastructure - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Implement data management and lifecycle for AI workloads - Configure compute and storage using Cisco UCS: profiles, policies, Intersight |
| AI Infrastructure Operations and Troubleshooting | 20% | - Optimize performance, security, and reliability - Manage health, logs, and events - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Implement performance benchmarking and validation - Troubleshoot network, compute, storage, and orchestration issues |
1. Which network design approach should be used to build a high-performance, nonblocking AI/ML data center fabric that supports 64 fully equipped UCS C885A nodes and provides the lowest possible latency and lossless Ethernet?
A) rail optimized
B) traditional three-tier
C) flat Layer 2
D) leaf-spine
2. Drag and Drop Question
A network engineer is designing congestion management for an AI cluster using RoCEv2 transport. Based on Cisco best practices, the engineer must understand how ECN and PFC work together to provide lossless Ethernet transport. Drag and drop the congestion management mechanisms from the left onto the corresponding descriptions on the right. Not all options are used.
3. What is a function of NVLink technology within a high-performance AI server or cluster?
A) to establish a secure, encrypted channel for data transfer between the AI server and external storage
B) to enable remote access and virtualization of GPU resources for distributed AI development teams
C) to manage power distribution and thermal regulation across all installed GPU units
D) to provide a high-speed, low-latency direct interconnect for GPU-to-GPU communication
4. An engineer deploys BGP EVPN in a Cisco VXLAN fabric. Which route type advertises MAC and IP binding information for endpoints?
A) Type 1
B) Type 4
C) Type 5
D) Type 2
5. How does RAG enhance the capabilities of LLMs?
A) by providing access to proprietary data
B) by retaining the LLM by altering its core parameters
C) by removing the data preparation and cleaning step
D) by removing inherent biases from LLM outputs
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: Only visible for members | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: A |
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