A Generative AI Framework for Autonomous Infrastructure Management in Cloud Operations

Because cloud environments are always changing, the need for smart and automated infrastructure management systems is rising. Maintaining current levels of fast, reliable and flexible digital activities is difficult with just traditional and manual approaches. The authors describe a generative AI framework that can help companies manage their cloud resources on its own. The framework uses the capabilities of AI to make decisions in real-time, detect issues early and fix them without human intervention. The use of event-driven workflows, serverless computing and reinforcement learning helps this system provide a robust and scalable way to automate infrastructure. The aim of the framework is to transform cloud operations through saving money, increasing system availability and better using resources. The main part of this framework is an AI-powered layer that engages with APIs and infrastructure-as- code (IaC) through automation to make configuration and resource adjustments depending on performance and operational events. The model regularly processes past and current information to better manage failures, problems with resources and security risks. It helps propose best practices, handle patch management automatically and maintain compliance with government policies. Keywords: Generative AI, Cloud Operations, Infrastructure Automation, AIOps, Self-healing Systems, DevOps, Cloud-native Frameworks, Reinforcement Learning, Event-driven Architecture, Fault Tolerance, Autonomous