Optimized Cloud Cost Management through AI-Driven Resource Allocation and Scheduling
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Optimized Cloud Cost Management through AI-Driven Resource Allocation and Scheduling
Praveen Kumar Thota
Cleveland State University, USA
Abstract
Deploying and managing IT systems has been changed for organizations due to the added scalability and flexibility cloud computing provides. On the other hand, increased cloud expenses are a big problem, mainly when organizations increase how much they use the cloud. It reviews effective ways to manage cloud costs by using artificial intelligence (AI) tools to arrange and schedule resources. Using machine learning real-world models such as reinforcement learning and predictive analytics, cloud resources are automatically allocated to avoid wasting them and use them effectively. According to this study, AI-assisted scheduling improves how jobs are completed and brings about substantial cost cuts without affecting how well the jobs are done. Using a full analysis, flowcharts, pseudocode and reviews of current methods, the research gives businesses a useful template for sustainable cloud cost reduction. It is clear from the study that AI has the power to change how costs are managed in the cloud and support better and less expensive ways of running cloud operations.
Keywords: Cloud cost optimization, AI-driven resource allocation, scheduling algorithms, machine learning, reinforcement learning