ABSTRACT
This chapter presents a case study and motivation. It proposes approach and results of approach. The chapter provides the review of related works. Jiang et al. proposed an automated approach which examines the logs, recognize the internal structure of log lines and then convert them into related execution events. It also provides the objective of predictive analysis to estimate the unknown future events and time of the event. The chapter explores the predictive models such as statistical models and machine learning algorithms. It starts approach with data gathering and lead to forecasting techniques. The framework of approach is divided into three main phases; the first two phases are the repetition from the previous research paper in which we discuss data pre-processing and feature extraction. The second phase is converting the error logs into a sequence of log lines or events, and the third phase forecasting the events and time of the events from the sequence of events.
