A Comprehensive Review of AIOps: Architectures, Techniques, Tools, Challenges, and Future Directions

The rapid expansion of cloud-native architectures, microservices, and distributed IT environments has increased the complexity of managing modern infrastructure. Artificial Intelligence for IT Operations (AIOps) has emerged as a key paradigm that integrates machine learning (ML), big data analytics, and automation to enhance operational efficiency. This review paper provides a comprehensive analysis of AIOps, including its foundational concepts, system architecture, core analytical techniques, leading enterprise tools, current challenges, and emerging research directions. The study highlights the evolving role of generative AI and large language models in autonomous operations, offering insights into the future trajectory of AIOps-driven intelligent IT ecosystems.