Workaround Prediction of Cloud Alarms using Machine Learning

Abstract

Cloud-based systems imply applications, resources, or services provided to users as per their requirement through the Internet using a cloud computing provider’s server. These clouds trigger alarm events to indicate the health of the system. Monitoring these alarms is essential for maintaining the health and continuous functioning of the cloud. Because of the humungous number of alarms triggered on a daily basis, notifying critical alarms in time and taking required action is quite a challenging task. In this paper, a machine learning model is implemented using a decision tree classifier to analyze each alarm and predict if any action is required for that alarm or not. Additionally, it notifies the concerned team via creating JIRA tickets.