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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Infrastructure Deployment and Data Management | 30% | - Deploy and manage AI infrastructure with orchestration tools - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Integrate AI frameworks and applications with Cisco infrastructure - Implement data management and lifecycle for AI workloads |
| Topic 2: AI Infrastructure Operations and Troubleshooting | 20% | - Implement performance benchmarking and validation - Troubleshoot network, compute, storage, and orchestration issues - Manage health, logs, and events - Optimize performance, security, and reliability - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts |
| Topic 3: AI Infrastructure Fundamentals | 20% | - Explain Cisco AI infrastructure solutions and portfolio - 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 - Describe AI and machine learning concepts |
| Topic 4: AI Infrastructure Components and Architecture | 30% | - 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 - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS |
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質問 # 19
An engineer configures Cisco Nexus Dashboard Fabric Controller for AI infrastructure automation. The company wants centralized policy management and simplified fabric provisioning across multiple pods. Which capability provides this benefit?
正解：D
解説：
Intent-based fabric automation simplifies deployment and policy consistency across large AI infrastructures. Nexus Dashboard Fabric Controller automates provisioning, validation, and operational management. Distributed ACLs and local VLAN switching are operational features but do not centralize orchestration. Manual CLI verification is error-prone and unsuitable for rapidly scaling AI environments.
質問 # 20
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?
正解：B
解説：
The fault shows a receive error statistics threshold crossing on switch B port 11. Because receive errors on a physical interface commonly indicate cabling, transceiver, or physical-layer issues, the first troubleshooting step is to inspect the physical connection and SFP+ components on the affected port before investigating workload or higher-layer configuration.
質問 # 21
A network architect wants to provide high availability for AI compute nodes connected to dual Cisco Nexus switches. Which technology enables active-active uplink forwarding without STP blocking?
正解：A
解説：
Virtual Port Channel (vPC) allows devices to use active-active uplinks across two Nexus switches while avoiding spanning-tree blocking. This increases bandwidth utilization and resiliency for AI clusters. GLBP and VRRP provide gateway redundancy, while PVST+ still relies on blocking redundant paths.
質問 # 22
A corporate network administrator manages a HyperFabric AI environment and wants to receive email notifications about assertions in the fabric. The administrator sets up a recipient email endpoint under the notification endpoints in the controller, but notifications are not received.
Which two configurations cause the issue? (Choose two.)
正解：B、C
解説：
Email endpoints must be verified before they can receive HyperFabric notifications, and the endpoint must also be included with the relevant fabric in the notification policy. Creating the email endpoint alone does not activate assertion notifications for a fabric until both of these notification requirements are completed.
質問 # 23
A network architect designs a Cisco AI fabric with spine-leaf topology. What is the primary advantage of this architecture for AI training workloads?
正解：A
解説：
AI workloads generate massive east-west traffic between compute nodes. Spine-leaf designs provide predictable latency and scalable bandwidth because each leaf switch maintains equal- cost paths to all spines. Routing protocols are still required, IP addressing remains necessary, and wireless integration is unrelated to AI fabric performance requirements.
質問 # 24
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