A network engineer wants to enhance network efficiency using advanced technologies. Which of the following actions utilizes machine learning to predict network issues before they occur?
Real-time monitoring of network traffic to detect anomalies
Forecasting potential network bottlenecks based on usage trends
Managing access control lists with policy-driven tools
Forecasting potential network bottlenecks based on usage trends is an application of machine learning for predictive analysis in network operations. Machine learning algorithms analyze historical traffic data to identify patterns and anticipate future congestion, allowing network engineers to address issues proactively. The other options involve automation, real-time monitoring, or policy management, which are important but do not specifically leverage machine learning for predictive purposes.
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Cisco CCNA 200-301
Automation and Programmability
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