How is out-of-band management utilized by network operators in an AI environment?
A.
It is used to remotely manage and troubleshoot network devices independently of the production network.
B.
It is used to directly manage the AI model’s learning rate during training sessions.
C.
It is used to increase the computational power of AI models by adapting additional processing resources.
D.
It is used to manage the data throughput of AI applications by prioritizing network traffic.
The Answer Is:
A
This question includes an explanation.
Explanation:
Out-of-band management provides a dedicated channel, separate from the production network, for remotely managing and troubleshooting devices (e.g., switches, servers) in an AI environment. This ensures control and recovery even if the primary network fails, unlike options tied to model training, compute power, or traffic prioritization.
(Reference: NVIDIA AI Infrastructure and Operations Study Guide, Section on Out-of-Band Management)
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