Predictive Infrastructure Management: Leveraging AI for Proactive Issue Detection in Hybrid Cloud Environments

Abstract

As hybrid cloud environments become the backbone of modern IT infrastructure, ensuring system uptime and operational efficiency has become more challenging. Predictive infrastructure management, powered by AI and machine learning, offers a proactive approach to detecting potential issues before they impact service delivery. This paper explores the key technologies and strategies behind predictive infrastructure management, including anomaly detection algorithms, predictive maintenance models, and intelligent automation. It highlights how AI-powered tools can monitor resource utilization, detect faults, and optimize infrastructure performance across multi-cloud environments. Through case studies, the paper demonstrates how enterprises can achieve enhanced reliability, reduced downtime, and improved operational efficiency. Finally, it provides recommendations for organizations adopting predictive infrastructure management frameworks, focusing on governance models, skill development, and best practices.