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| Section | Weight | Objectives |
|---|---|---|
| AI Infrastructure Operations and Troubleshooting | 20% | - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Manage health, logs, and events - Optimize performance, security, and reliability - Implement performance benchmarking and validation - Troubleshoot network, compute, storage, and orchestration issues |
| AI Infrastructure Deployment and Data Management | 30% | - Integrate AI frameworks and applications with Cisco infrastructure - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Deploy and manage AI infrastructure with orchestration tools - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Implement data management and lifecycle for AI workloads |
| AI Infrastructure Components and Architecture | 30% | - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability - Evaluate power, cooling, and efficiency requirements - Evaluate hybrid and multi-cloud AI integration - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures |
| AI Infrastructure Fundamentals | 20% | - Explain Cisco AI infrastructure solutions and portfolio - Describe AI and machine learning concepts - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Describe AI use cases in data center environments - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring |
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NEW QUESTION # 69
A data center team enables jumbo frames in a Cisco AI cluster. What is the primary benefit of increasing the MTU for east-west GPU traffic?
Answer: B
Explanation:
Jumbo frames reduce the number of packets needed to transmit large AI datasets, decreasing CPU interrupts and protocol overhead. This improves throughput and efficiency for GPU communication. Larger MTUs do not directly affect convergence or eliminate buffering, and they typically reduce rather than increase processing overhead.
NEW QUESTION # 70
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?
Answer: D
Explanation:
Cisco UCS X-Series is designed for scalable, modular compute environments that support GPU- enabled workloads, high memory capacity, virtualization, and coexistence with existing infrastructure. Its modular architecture allows the enterprise to expand resources as AI workload demands grow.
NEW QUESTION # 71
An engineer notices excessive broadcast traffic inside a legacy AI server VLAN. Which technology should be implemented to reduce flooding and improve scalability?
Answer: A
Explanation:
VXLAN EVPN reduces unknown unicast and broadcast flooding by using control-plane learning with BGP EVPN. This improves scalability in modern AI data centers. RIP is outdated for large- scale fabrics, while PAT and GRE tunneling do not address broadcast domain limitations.
NEW QUESTION # 72
How does RAG enhance the capabilities of LLMs?
Answer: B
Explanation:
RAG enhances LLMs by retrieving relevant external or proprietary information at generation time and using that context to produce more accurate, current, and domain-specific responses without changing the model's core parameters.
NEW QUESTION # 73
Drag and Drop Question
Refer to the exhibit. When a new AI backend network that supports Cisco UCS-based GPU servers with NVIDIA Connect-X network adapters is benchmarked, the traffic distribution observed has unacceptable variability across the interfaces. Drag and drop the code snippets from the bottom onto the boxes in the code to configure the switch to resolve the issue.
Answer:
Explanation:
NEW QUESTION # 74
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