Data-Driven Reduction of Log Message Data

Techniques are provided for data-driven reduction of log message data. An exemplary method comprises: obtaining log files and user-specified configuration parameters, wherein the log files each comprise one or more log messages; generating an event count matrix indicating a number of times each of a plurality of unique messages appeared in a given log file of the log files; generating a correlation graph by inserting similar messages with a mutual undirected edge, wherein similar messages are identified based on a predefined similarity measure; extracting redundant messages from the correlation graph by selecting log messages for inclusion in an uninformative log message filter from sub-graphs of the correlation graph in which any two nodes are connected together, except those log messages satisfying a predefined message frequency criteria; and identifying one or more redundant messages using the uninformative log message filter. The uninformative log message filter is optionally applied to real-time log messages and/or existing file systems.