Advanced Log Analysis Tools for Efficient Root Cause Identification

Arnab Dey

Abstract: Log files serve as invaluable resources for troubleshooting and diagnosing software issues, yet the sheer volume and complexity of modern log data present significant challenges for developers and IT professionals. This paper presents an overview of advanced log analysis tools designed to facilitate efficient debugging and root cause identification in large - scale software systems. By harnessing the power of machine learning algorithms, distributed processing frameworks, and real - time monitoring techniques, these tools enable practitioners to navigate through massive log files, pinpoint anomalies, and expedite the resolution of critical issues. The paper explores key features, functionalities, and case studies of prominent log analysis tools, highlighting their effectiveness in accelerating problem resolution and enhancing system reliability.

Keywords: Log analysis, Debugging, Root cause identification, Machine learning, Distributed processing, Real - time monitoring