A Study on Deep Learning Frameworks to Understand the Real Time Fault Detection and Diagnosis in IT Operations with AIOPs
Latha Narayanan Valli, N. Sujatha, E. Joice Rathinam · 2023
Business operations in the recent Era are highly complex and demand high throughput technology to address the needs. Artificial Intelligence for IT Operations (AIOPs) plays a vital role in the detection of problems in real-time IT operations and provides solutions for businesses. This study outlines the understanding of deep learning models in fault detection and diagnosis in IT operations using AIOPs. Data was acquired from IT experts who are playing significant roles in the companies through a survey questionnaire which helps to analyze deep learning models used for business. Subsequently, hypothesis testing was done to assess the proposed framework for enhancing accuracy with reduced downtime. The results show that the framework achieves good accuracy, precision, and recall rates in comparison to classic machine-learning techniques. The proposed framework has the potential to realize problem detection and diagnosis in IT operations with a hybrid deep learning model and AIOPs to increase efficiency.