Exploration of Enterprise Big Data Microservice Architecture Based on Domain-Driven Design (DDD)
Yiru Zhang

TL;DR
This paper presents a microservice architecture for enterprise big data platforms using Domain-Driven Design, enhancing scalability, flexibility, and data collection efficiency through modularization and dynamic scheduling.
Contribution
It introduces a DDD-based microservice approach for enterprise big data platforms, including an automated data collection process and an improved scheduling algorithm.
Findings
Significantly improved platform scalability and data quality
Enhanced data collection efficiency and real-time monitoring
Successful implementation and testing validate the approach
Abstract
With the rapid advancement of digitization and intelligence, enterprise big data processing platforms have become increasingly important in data management. However, traditional monolithic architectures, due to their high coupling, are unable to cope with increasingly complex demands in the face of business expansion and increased data volume, resulting in limited platform scalability and decreased data collection efficiency. This article proposes a solution for enterprise big data processing platform based on microservice architecture, based on the concept of Domain Driven Design (DDD). Through in-depth analysis of business requirements, the functional and non functional requirements of the platform in various scenarios were determined, and the DDD method was used to decompose the core business logic into independent microservice modules, enabling data collection, parsing, cleaning,…
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Taxonomy
TopicsSoftware System Performance and Reliability · Big Data and Digital Economy · Cloud Computing and Resource Management
