Performance Analysis of Machine Learning Based Fault Detection for Cloud Infrastructure

Abstract

As the cloud infrastructure becomes more complex, the importance of fault detection technology is increasing. A machine learning-based fault detection technology is being used to overcome the limitations of the existing fault detection method through log analysis and threshold-based fault detection method. Machine learning-based fault detection methods are greatly influenced by features. In this paper, we introduce feature engineering techniques that can affect accuracy, and propose a method to improve the performance of fault detection models in cloud infrastructure through comparative analysis and verification of various feature analysis models.