Sustainable and ESG-Driven Multi-Cloud Optimization in Large Enterprises: Balancing Cost, Performance, and Flexibility

Abstract

As cloud continues to reign across businesses of all sizes, large companies are choosing a multi-cloud strategy to harness the strengths of various providers to provide greater flexibility, lower costs, and more performance. In this article, we examine the imperative for proactive multi-cloud optimization and the importance of ongoing resource evaluation and administration. The article outlines the advantages of creating a framework to leverage best-of-breed service and dynamic scaling and encourage innovation while enabling enterprises to steer clear of vendor lock-in and keep the business as resilient as possible in the case of service disruptions. In addition, it describes the best practices regarding resource management, performance tracking, and security on different platforms. As a transformative approach, this thesis presents the integration of artificial intelligence and machine learning into predictive multi-cloud management to optimize resource allocation and improve the overall efficiency of the cloud. Finally, this proactive framework also helps organizations overcome the challenges of an enterprise operating in a multi-cloud world to work with scalability and agility and maintain a competitive edge. Furthermore, this framework considers Environmental, Social, and Governance (ESG) and aligns with the multi-cloud strategy with sustainability goals. By Integrating ESG principles, organizations can reduce carbon footprint and reduce environmental impact and support corporate social responsibilities, driving responsible technology adoption practices balancing cost and performance.