Enhancing Cloud Performance with AI-Based Predictive Analytics

The article addresses the issue of cloud performance optimization through AI-powered predictive analytics, aiming to simplify resource allocation and minimize performance bottlenecks in cloud computing. The motivation is to realize efficient cloud computing, where predictive models can make a dramatic difference in allocating resources and realize cost-effectiveness. Leveraging publicly available data from Google Cloud BigQuery, the study applies machine learning algorithms, including time-series prediction and regression models, to predict cloud resource utilization and performance degradation. The primary findings are that AI-powered models can efficiently predict resource surges and optimize cloud scaling policies. The findings form the foundation for developing more efficient cloud infrastructure administration with considerable performance and cost optimization benefits. The study demonstrates the feasibility of AI-based cloud performance optimization for practical applications.