200-301 Question 483
Select 3A network administrator is tasked with optimizing network performance and detecting anomalies in real-time. They decide to implement AI-driven solutions in the network operations center. Which of the following use cases best illustrates the application of generative and predictive AI in this scenario?
- A
Using machine learning to analyze historical network traffic and predict future bandwidth requirements.
- B
Automatically generating configuration templates for new devices based on network policies.
- C
Deploying AI to simulate potential network outages and suggest preventive measures.
- D
Using AI to monitor network traffic patterns and dynamically adjust quality of service (QoS) policies in real-time.
- E
Manually configuring and troubleshooting network devices based on predefined baseline parameters.
Show answer and explanation
Correct answers: A, C, D
Explanation
Generative AI can simulate potential scenarios (e.g., network outages) to proactively suggest solutions, while predictive AI leverages historical data to forecast future trends or adjust operations dynamically. In this scenario, using predictive AI for bandwidth prediction, generative AI for outage simulation, and AI for real-time traffic-based QoS adjustments are all valid applications of AI in network operations.
- A. Correct.
Machine learning algorithms can predict future bandwidth needs by analyzing historical traffic data, which is an example of predictive AI in network operations.
- B. Incorrect.
Generating configuration templates based on network policies is a useful automation task, but it does not explicitly involve generative or predictive AI.
- C. Correct.
Simulating potential network outages and suggesting preventive measures is a valid use case of generative AI, as it creates hypothetical scenarios to improve network reliability.
- D. Correct.
AI can monitor traffic patterns and dynamically adjust QoS policies, which is an example of predictive AI being used in real-time network operations.
- E. Incorrect.
Manually configuring devices does not involve the use of AI or machine learning, and thus is not relevant to this use case.