Load Balancing Strategies for Multi-Cloud Applications: Round-Robin vs. Predictive Algorithms

This paper explores the effectiveness of different load-balancing strategies within multi-cloud environments, focusing on comparing the Round-Robin and Predictive Algorithms. As multi-cloud applications become more common due to their advantages in resilience, flexibility, and cost efficiency, managing workload distribution efficiently has emerged as a significant challenge. This paper examines both load-balancing approaches, evaluating them based on key factors such as performance metrics, cost implications, and scalability. Additionally, the paper presents case studies and practical examples to provide a deeper understanding of how these strategies perform in real-world scenarios. Our analysis also takes into account the operational complexities associated with each approach, offering insights into their practical effectiveness. Keywords Load balancing, multi-cloud, round-robin algorithm, predictive algorithms, cloud computing, workload management, resource optimization, adaptive algorithms, traffic distribution