Modeling and Orchestration of Complex ETL Pipelines in Distributed and Cloud-Native Environments

Ramesh Tangudu *

Enterprise Architect and Application Development Lead, TX, USA.
 
Review
International Journal of Science and Research Archive, 2024, 13(01), 3637-3646.
Article DOI: 10.30574/ijsra.2024.13.1.2104
Publication history: 
Received on 19 September 2024; revised on 24 October 2024; accepted on 29 October 2024
 
Abstract: 
Aim: The aim of this study is to investigate effective modeling and orchestration strategies for complex ETL (Extract, Transform, Load) pipelines in distributed and cloud-native environments. Modern data-driven systems demand scalable, reliable, and maintainable ETL workflows capable of handling heterogeneous data sources and high data velocity.
Method: This work adopts a conceptual and architectural modeling approach, combining workflow abstraction, distributed processing paradigms, and cloud-native orchestration tools. ETL pipelines are modeled using directed acyclic graphs (DAGs), containerization, and microservices-based deployment strategies.
Results: The proposed modeling and orchestration framework improves pipeline modularity, fault isolation, and execution efficiency. Experimental observations demonstrate enhanced scalability, reduced failure recovery time, and better resource utilization compared to monolithic ETL designs.
Conclusion: The study concludes that cloud-native orchestration combined with structured ETL modeling significantly enhances operational robustness and flexibility. These techniques provide a strong foundation for building future-proof data integration platforms in large-scale distributed environments.
 
Keywords: 
ETL Pipelines; Distributed Systems; Cloud-Native Architecture; Workflow Orchestration; Data Engineering
 
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0