Discovering Anomalies and Root Causes in Applications via Relevant Fields Analysis

Abstract

In this paper, we present a powerful end-to-end data mining system that collects application related data and provides insightful relevant fields analysis in addition to search and filtering. We present details on field extraction, indexing, relevant field processing and dynamic baseline derivation. We also propose to demonstrate the effectiveness of various scoring algorithms. Two real-world use cases show relevant fields analysis is effective to detect application anomalies and discover root causes of application incidents.