Optimizing Cloud Infrastructure Performance Using AI: Intelligent Resource Allocation and Predictive Maintenance

Abstract

The growing trend of cloud computing calls for efficient utilization of resources and robustness of the system. Typically, such inefficiencies due to traditional resource allocation and maintenance strategies include underutilization, latency issues, and unexpected system failures. Dynamic resource allocation and Predictive maintenance, as well as its AI-driven optimization, are enhanced in cloud infrastructure with intelligent solutions that are based on AI-driven optimization techniques. Historical data for the workload trends, virtual resource distribution, and detecting anomalies to the system are analyzed by machine learning algorithms. We review AI-based strategies for the optimization of cloud infrastructure and discuss their comparison with traditional methods concerning the main performance metrics. Finally, it discusses what future research directions in AI-driven cloud optimization are possible.