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Intelligent Log Analysis Using Machine and Deep Learning
Abstract
Computers generate a large volume of logs recording various events of interest. These logs are a rich source of information and can be analyzed to extract various insights about the system. However, due to its overwhelmingly large volume, logs are often mismanaged and not utilized effectively. The goal of this chapter is to help researchers and industrial professionals make more informed decisions about their logging solutions. It first lays the foundation by describing log sources and format. Then it describes all the components involved in logging. The remainder of the chapter provides a survey of different log analysis techniques and their applications, consisting of conventional techniques using rules and event correlators that can detect known issues, plus more advanced techniques such as statistical, machine learning, and deep learning techniques that can also detect unknown issues. The chapter concludes describing the underlying concepts of the techniques, their application to log analysis, and their comparative effectiveness.
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