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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:

1. 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?

A) UCS X-series
B) Unified Edge
C) UCS M-series
D) UCS C-series Standalone

2. 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) traditional three-tier
B) flat Layer 2
C) rail optimized
D) leaf-spine

3. An engineer configures quality of service in the Cisco ACI fabric to connect VAST storage servers. Which combination of attributes must be selected?

A) Congestion Algorithm: Tail Drop
Congestion Notification: Enabled
B) Congestion Algorithm: Weighted Random Early Detection (WRED)
Congestion Notification: Disabled
C) Congestion Algorithm: Weighted Random Early Detection (WRED)
Congestion Notification: Enabled
D) Congestion Algorithm: Tail Drop
Congestion Notification: Disabled

4. A network architect designs connectivity for a new Cisco AI POD operating in Intersight Managed Mode. To ensure high availability and aggregate bandwidth for external network traffic, a port channel must be established using multiple 100 GbE uplink ports on the fabric interconnects to connect to the upstream core switch infrastructure. Which specific policy, applied through the domain profile, must be modified to define and configure this port channel on the fabric interconnects for the desired uplink connectivity?

A) LAN connectivity policy
B) Ethernet network group
C) port policy
D) network connectivity policy

5. Which aspect of rapid provisioning supports a scalable workload execution in an AI infrastructure?

A) delayed rollout of new network resources
B) efficient launch of computational platforms
C) limited connectivity within isolated locations
D) distinct management for isolated components

Solutions: