The after-conference proceeding of the CML 2025 will be published in SCOPUS Indexed Springer Book Series "Lecture Notes in Networks and Systems".

Mr. Roshan Mahant

AI Cloud Advisor

Abstract:

Cloud computing has transformed enterprise IT by providing scalable and flexible resources. However, optimizing cloud infrastructure for performance, security, and cost-efficiency remains a complex challenge. This research introduces an AI-powered advisory system, the AI Cloud Advisor, designed to enhance cloud architecture decision-making by offering intelligent recommendations. Leveraging machine learning algorithms and real-time analytics, the AI Cloud Advisor provides tailored solutions for cost optimization, scalability, security enforcement, and troubleshooting. Unlike generic AI tools like ChatGPT, which provide broad, non-specific responses, this custom-trained AI model pinpoints issues rapidly and accurately, significantly improving troubleshooting speed. Additionally, AI Cloud Advisor offers a knowledge hub with best-practice articles and regular blog updates on cloud and microservices, ensuring continuous learning and informed decision-making. This research evaluates the effectiveness of AI-driven advisory systems in enhancing cloud efficiency, reducing operational costs, and enforcing security best practices.