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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:

1. What is a purpose of Cisco AI PODs?

A) to provide a turnkey, full-stack infrastructure for AI training, fine-tuning, and inferencing
B) to offer a flexible AI infrastructure focused on inferencing workloads with optional training capabilities
C) to deliver modular AI hardware components that can be integrated with third-party software platforms
D) to enable AI lifecycle management through cloud-native software with hardware support limited to compute servers

2. An engineer must configure dynamic load balancing (DLB) on a Cisco Nexus 9000 Series Switch AI fabric using a CLI. Which configuration must be implemented for only the odd-numbered interfaces?

A) Create a DLB hardware profile and include the list of desired interfaces.
B) Exclude the desired interfaces from DLB with the interface level configuration of no dlb-interface.
C) Create a QoS policy that enables DLB and apply that policy to the relevant interfaces.
D) Under the relevant interface-level configuration, add the keyword dlb-interface.

3. An end customer plans to deploy an AI fabric in a new data center. Their engineers are more familiar with CLI-based networks and require the capability to automate standardized configuration templates and monitor flows for the fabric. Which data center automation tool meets the requirements?

A) HyperFabric
B) Digital Network Architecture Center
C) Intersight
D) Nexus Dashboard

4. 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.

5. A network operations team deploys HyperFabric AI and wants to monitor fabric health to proactively identify performance issues. The team must track metrics specifically relevant to AI training workloads. Which metric is most critical for identifying congestion issues that could impact AI training performance in a HyperFabric AI deployment?

A) spanning tree topology change notifications
B) BGP EVPN route count per leaf switch
C) PFC pause frame transmission rate per interface
D) VXLAN tunnel packet encapsulation rate

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