To better manage network health, AI-Powered ADEM now uses adaptive machine learning baselining (dynamic baselining) to baseline performance metrics for all mobile users across the LAN, WiFi, Internet, and Prisma® Access gateway segments. Dynamic baselining addresses the challenges of using fixed industry benchmarks for measuring performance metrics. ADEM uses intelligent baselining to learn typical time-varying performance patterns of each unique network segment. With dynamic baselining, you can accurately identify true performance anomalies as against normal network fluctuations.

Dynamic baselining creates customized baseline thresholds for each network segment (LAN, Internet, Prisma Access) based on geographic locations, Internet Service Provider, and Prisma Access gateway locations. ADEM groups users with similar network attributes such as Internet Service Provider (ISP), Prisma Access gateway locations and creates baselines for LAN, Internet, and Prisma Access network segments based on the 30 days historical data.

ADEM intuitively displays network performance metrics and trends with baseline ranges against actual performance values that allows you to immediately spot deviations without manual analysis. This approach helps in faster root cause analysis of the issue and enhances your network monitoring efficiency.