Machine learning-based anomaly detection for Golden Baseline and Network Intent

Configuring and maintaining Golden Baseline and Network Intent checks today requires customers to manually define specific thresholds and rules for what constitutes a deviation from normal behavior. This setup and ongoing maintenance can be complex, particularly for customers who want to detect meaningful changes without specifying exact numeric or logical criteria in advance. This enhancement would introduce a machine learning-based option for Golden Baseline and Network Intent that automatically learns normal network behavior and flags deviations without requiring manually defined thresholds. Customers would benefit from reduced setup and maintenance effort while gaining more adaptive and accurate detection of meaningful changes in their network environment.