AIOPs based Predictive Alerting for System Stability in IT Environment

Abstract

Many industries and organizations are moving away from legacy systems towards digital transformation to optimize their business processes. Artificial intelligence for IT operations (AIOps) plays a pivotal role in digital transformation. AIOps platforms utilize a large amount of data coupled with classical machine learning and cutting-edge analytic technologies. This will boost IT operations with proactive dynamic activities. The Micro Focus Operations Bridge (OpsBridge) monitors the health and performance of the systems in the infrastructure and applications across their IT environment and the hundreds of alerts are delivered to respective teams. These huge number of alerts create an alert noise. In this paper, we present an AIOps based automated predictive alerting system using logistic regression to monitor the system environment and reduce the alert noise. This predictive alerting will identify abnormalities in operational data and raise an alert on these abnormalities that could potentially impact an application or service.