Automation of AD-OHC Dashbord and Monitoring of Cloud Resources using Genrative AI to Reduce Costing and Enhance Performance
Parikshit Chavan, Peeyusha Chavan · 2024
In this extensive review, the incorporation of Generative Artificial Intelligence (AI) into ad-hoc dashboards and cloud resource monitoring is investigated in depth. A purpose of this work is to investigate a current research and highlight the transformational potential of generative artificial intelligence for optimising costs, automating tasks, and improving overall cost efficiency. This article includes a comprehensive analysis of a development of ad-hoc cloud computing, a relevance of cloud resource monitoring, and the role that generative artificial intelligence plays in reducing costs. Notable advantages include better user satisfaction, resource optimisation, adaptive learning, and efficient automation. Additionally, precise decision-making and resource optimisation are highlighted. By presenting actual evidence, the study highlights the association between the quality of generative artificial intelligence and the influence it has on society. It finishes with an analysis of generative artificial intelligence applications in ad-hoc dashboards, with a focus on increased resource utilisation, scalability, and timely consistency of cloud resources. In addition, the article addresses constraints and makes suggestions for future paths. These include models that protect users’ privacy, efficient resource utilisation, explainable artificial intelligence, dynamic autonomy, and security-driven generative models. The paper’s goal is to provide the groundwork for further study and improvement.