Mona's key feature is the insights generator, which once configured, automatically and almost exhaustively searches for segments in the data in which some anomalous behavior takes place. It then creates context-rich insights regarding these anomalies and alerts the user accordingly. You define the metrics that you’d like to monitor, the anomaly types to search for, and the dimensions on which to segment the data.
Mona's insight generator can be configured to search for drifts, outlier segments, sudden changes, and other anomaly types in both a metric's average or the size of segments, as well as drifts in the sum of a metric and newly appearing segments in the data. More anomaly detection types are being continuously added.
More info on the concepts, configuration possibilities, and semantics can be found in the next pages.
Updated about 2 months ago