Detecting behavior patterns utilizing machine learning model trained with multi-modal time series analysis of diagnostic data

Abstract

An apparatus includes a processing device configured to obtain time series diagnostic data associated with assets in an information technology (IT). The processing device is also configured to generate first modality information comprising behavior labels assigned to each of a plurality of time periods, a given behavior label for a given time period being based at least in part on measured feature values for the features collectively in the given time period. The processing device is further configured to generate second modality information comprising feature deltas characterizing differences between measured feature values for interdependent feature pairs. The processing device is further configured to perform multi-modal analysis of the time series diagnostic data to detect behavior patterns in the utilizing a machine learning model trained using the first modality information and the second modality information, and to initiate remedial action in the IT infrastructure responsive to detecting an anomalous behavior pattern.