Cross-Cloud Data Engineering: Unified Big Data Workflows with AWS and GCP
Author(s): Praveen Kodakandla
Publication #: 2506028
Date of Publication: 03.11.2023
Country: India
Pages: 1-12
Published In: Volume 7 Issue 6 November-2023
Abstract
Using cloud computing has made it accessible for organizations to benefit from several providers and boost their flexibility, safety, and inventive ideas when handling data. This approach is gaining popularity in big data architecture because it enables businesses to formulate and handle data operations that work on AWS and GCP. With this approach, it’s easier to change vendors, balance costs with performance, and improve compliance with the rules for handling data. Also, it leads to difficulties in things like joining various types of data, coordinating different services, ensuring safety, and checking the system’s health. This article goes over the principles, tools, and patterns needed to develop effective cross-cloud big data workflows. The analysis covers important AWS and GCP services, explains common ways to tie them together, and discusses performance as well as governance matters. By studying a real case, we explain how companies can create data pipelines that easily expand, are fault-tolerant, and secure using all their cloud ecosystems. The author ends the article by introducing new trends that will play a key role in cross-cloud data engineering, such as cloud-agnostic platforms, AI-based orchestration, and responsible cost management.
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