Cloud Infrastructure Fault Monitoring and Prediction System using LSTM based predictive maintenance

By analysing the system logs, which provide us with useful information, we may identify the key information about the system or application that helps in better utilisation of system resources. It is difficult to simply look through every raw log message on a regular basis for large-scale systems, though. The two most difficult aspects of reading logs are the quantity of these unstructured log messages and linking the log messages to system activities. These restrictions limit the capacity to diagnose previously unknown system events that negatively impacted system performance as well as the ability to provide alerts or warnings on known system events. In this study, we provide a framework for a real-time system event analysis UI for log monitoring. Our UI framework offers a real-time, structured view of log events. The logs are examined on our UI interface after being processed and evaluated. Also, we have used several machine learning algorithm like LSTM for predictive maintenance in cloud fault monitoring system.