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| Section | Weight | Objectives |
|---|---|---|
| AI Infrastructure Deployment and Data Management | 30% | - Integrate AI frameworks and applications with Cisco infrastructure - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Deploy and manage AI infrastructure with orchestration tools - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Implement data management and lifecycle for AI workloads |
| AI Infrastructure Components and Architecture | 30% | - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures - 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 |
| AI Infrastructure Fundamentals | 20% | - Describe AI use cases in data center environments - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Describe AI and machine learning concepts - Explain Cisco AI infrastructure solutions and portfolio |
| AI Infrastructure Operations and Troubleshooting | 20% | - Optimize performance, security, and reliability - Troubleshoot network, compute, storage, and orchestration issues - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Manage health, logs, and events - Implement performance benchmarking and validation |
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NEW QUESTION # 69
A server administrator must monitor the performance and utilization of GPUs in Cisco UCS servers running AI workloads. Which two metrics must be used in Cisco Intersight to accomplish these goals? (Choose two.)
Answer: B,E
Explanation:
Cisco Intersight provides GPU-focused telemetry for UCS servers, including utilization and performance metrics. These measurements allow the administrator to monitor how heavily the GPUs are being used and whether the AI workload is receiving the expected GPU performance.
NEW QUESTION # 70
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?
Answer: A
Explanation:
For UCS C885A M8 servers running LLM training and inference workloads, the surrounding Nexus fabric design is critical because GPU-dense systems depend on low-latency, high- bandwidth, lossless network connectivity for scale-out performance. Selecting and configuring the correct Nexus fabric minimizes communication delays between compute nodes and enables the AI infrastructure to scale efficiently.
NEW QUESTION # 71
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?
Answer: C
Explanation:
A rail-optimized design is used for large AI/ML clusters because it aligns GPU-to-GPU communication paths across the fabric, minimizes latency, and supports high-throughput lossless Ethernet for distributed training workloads.
NEW QUESTION # 72
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?
Answer: C
Explanation:
Cisco UCS C885A M8 with NVIDIA H200 GPUs is designed for high-performance AI workloads that require dense GPU acceleration, large memory capacity, and direct GPU-to-GPU communication through NVIDIA NVLink. This combination supports demanding analytics, training, and inference workloads where high-bandwidth GPU interconnect is required.
NEW QUESTION # 73
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?
Answer: B
Explanation:
In Cisco Intersight Managed Mode, the fabric interconnect management DNS and NTP settings are controlled through the UCS domain profile. If the settings are changed locally from the device console UI, the deployed domain profile must also be updated in Intersight so the corrected configuration is not overwritten during the next policy deployment or compliance remediation.
NEW QUESTION # 74
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