JOURNAL ARTICLE

Optimizing Data Flow in Multi-Cloud Environments: A Technical Deep Dive

Srujan Reddy Anugu

Year: 2025 Journal:   International Journal of Scientific Research in Computer Science Engineering and Information Technology Vol: 11 (1)Pages: 1466-1473

Abstract

The widespread adoption of multi-cloud strategies has fundamentally transformed enterprise computing architectures, introducing opportunities and challenges in modern IT environments. This article examines data flow optimization between multiple cloud providers, focusing on performance constraints, integration complexities, and security requirements. The article investigates advanced optimization techniques, including direct cloud interconnection, data fabric implementation, intelligent replication strategies, and edge computing integration. Through this article, enterprise deployments across various sectors, the article demonstrates that properly implemented multi-cloud optimization strategies significantly enhance operational resilience, reduce costs, and improve system performance. The article highlights the importance of standardized APIs, comprehensive monitoring frameworks, and emerging AI-driven optimization approaches in achieving efficient multi-cloud operations. This article provides valuable insights for organizations seeking to optimize their multi-cloud environments while maintaining security and compliance requirements.

Keywords:
Cloud computing Computer science Flow (mathematics) Operating system Mathematics

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7
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0.03
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Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Cloud Data Security Solutions
Physical Sciences →  Computer Science →  Information Systems

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