Online anomaly detection for multi-source VMware using a distributed streaming framework.

Anomaly detection refers to the identification of patterns in a dataset that do not conform to expected patterns. Such non-conformant patterns typically correspond to samples of interest and are assigned to different labels in different domains, such as outliers, anomalies, exceptions, and malware. A daunting challenge is to detect anomalies in rapid voluminous streams of data.