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Informative Article | Engineering Science | India | Volume 8 Issue 1, January 2019 | Rating: 4.1 / 10
Architecting a Cloud Data Platform: Bridging Storage and Compute for Enhanced Data Processing
Venkat Kalyan Uppala
Abstract: Cloud computing has revolutionized the way organizations manage and process data, offering scalability, cost-efficiency, and flexibility that traditional on-premises infrastructures cannot match. This paper explores the evolution of cloud computing, highlighting its transition from basic storage solutions to advanced data processing capabilities. Key aspects such as the scalability of resources, cost advantages, and the ability to handle big data are discussed. The paper also examines the transition from on-premises to cloud-based platforms, emphasizing the benefits and challenges of integrating storage and compute functions to optimize resource utilization and performance. Through a comprehensive literature review, the paper traces the development of cloud data platforms, from early storage solutions to modern architectures that support real-time processing, machine learning, and advanced analytics. Key architectural principles such as the separation of storage and compute, elasticity, and data locality are analyzed, demonstrating their significance in enhancing cloud efficiency and performance. The paper also addresses practical strategies for implementing cloud data platforms, including the use of hybrid cloud solutions, and discusses the challenges of managing data locality and latency. The findings suggest that cloud computing, with its continuous advancements, remains a critical component for organizations seeking to leverage data-driven decision-making and innovation.
Keywords: cloud computing, data processing, scalability, cloud platforms, hybrid cloud solutions
Edition: Volume 8 Issue 1, January 2019
Pages: 2281 - 2289