Cloud-Agnostic Solution for Large-Scale HighPerformance Compute and Data Partitioning

Abstract

The rapid evolution of cloud computing demands efficient and scalable solutions for compute and data partitioning across diverse platforms. This paper introduces a novel cloud-agnostic framework designed to address the challenges of large-scale partitioning strategies. By leveraging compute and data partitioning strategies, our approach ensures high performance, scalability, and seamless integration across major cloud providers like AWS, Azure, GCP, and Oracle Cloud. We present real-world case studies demonstrating the framework's effectiveness in significantly improving processing times, data integrity, and handling substantial workloads with minimal downtime.