Methods and systems that identify computational-entity transactions and corresponding log/event-message traces from streams and/or collections of log/event messages

Abstract

The current document is directed to methods and systems that automatically identify log/event-message traces and computational-entity transactions within collections and/or streams of log/event messages. Automated identification of log/event-message traces provides the basis for automated interpretation, by automated computer-system administration-and-the management subsystems, of the information represented by collections and/or streams of log/event messages. Disclosed approaches to automatically identifying log/event-message traces and computational-entity involve identifying log/event-message types, generating time-series-like log/event-message-type occurrence signals from log/event-message collections and/or streams, and computing cross correlations between pairs of log/event-message-type occurrence signals. In one implementation, a strongly-correlated-type graph is generated from the computed cross correlations, from which connected-components subgraphs, corresponding to computational-entity transactions, are extracted. Log/event-message traces are then extracted from acyclic graphs generated from the connected-component subgraphs.