AI-Driven Predictive Scaling for Multi-Cloud Resource Management: Using Adaptive Forecasting, Cost-Optimization, and Auto-Tuning Algorithms

Serverless computing has revolutionized cloud infrastructure by enabling application development without managing underlying servers. However, integrating serverless with multi-cloud environments introduces unique security and scaling challenges. This paper presents an AI-driven predictive scaling approach using three key algorithms: Adaptive Forecasting Algorithm (AFA), Cost-Optimized Resource Allocation Algorithm (CORA), and AI-Based Auto-Tuning Algorithm (AITA). These algorithms address the challenges of workload prediction, resource optimization, and performance tuning. Experimental results demonstrate significant cost reductions and performance improvements compared to conventional methods.