Research And Implementation Of Web-based Service Fault Diagnosis System Based On Event Correlation

In an increasingly competitive market conditions, internet companies need services of higher reliability. Fast and accurate fault diagnosis can directly improve service reliability, and improve the company’s competitiveness and influence fundamentally, a complete fault diagnosis system can greatly improve the efficiency of fault diagnosis.This paper analyzes the research status of fault diagnosis on domestic and overseas software, networks, internet services, and their related products, and summarized existing research and product shortage. On this basis, this paper propose a suitable solution for web-based service fault diagnosis combined with the characteristics. Finally, this paper through simulation experiments verifies the effectiveness of the fault diagnosis system.This paper presents the design and development of a web-based service fault diagnosis system based event correlation, proposed the use of association rule mining method preliminary screening of possible causal relationship between an event and another, and on the basis of feedback of the results of the analysis, through machine learning methods to optimize causality of events collection, and ultimately achieve the purpose of accurate fault diagnosis. This paper describes the methods used in the design and development of web-based service fault diagnosis system process, encountered problems and design solutions, and developed a corresponding fault diagnosis system.