The paper examines the explores the use of artificial intelligence (AI) methods and tools for the efficient construction, management, and optimization of cloud IT infrastructures. The main challenges related to the automation of deployment, scaling, monitoring, and resource optimization in the cloud environment are analyzed, along with the role of AI in addressing these issues. Approaches to integrating AI to improve productivity, reduce operational costs, and enhance the security of cloud platforms are discussed. Special attention is given to the use of machine learning algorithms for load forecasting, enabling dynamic resource adjustment in the cloud in response to changing demand. The application of AI for database optimization, automation of continuous integration and delivery (CI/CD) processes, and effective management of network resources in real-time is also examined. Based on the AWS cloud architecture, specific examples of AI integration for automatic infrastructure scaling and ensuring resilience under varying loads are proposed. The advantages of using intelligent systems for mitigating cybersecurity risks and managing large data volumes, as well as improving resource management efficiency, are highlighted. The study’s findings confirm that the use of AI significantly enhances the flexibility, resilience, and overall effectiveness of cloud IT systems, optimizing costs and ensuring high user service levels. The main directions for further research in this rapidly developing and promising field are outlined, which will improve existing models and create new methods for building intelligent cloud infrastructures.
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