Microservices and Real-Time Processing in Retail IT: A Review of Open-Source Toolchains and Deployment Strategies

📅 2025-06-11
📈 Citations: 0
Influential: 0
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🤖 AI Summary
Retail digital transformation demands real-time processing, scalability, and elasticity—challenges inadequately addressed by monolithic or loosely integrated architectures. Method: This paper designs and implements an open-source, event-driven microservices framework, systematically integrating Apache Kafka, Spring Boot, MongoDB, and Kubernetes—the first such holistic integration in retail contexts. The framework enables high-throughput financial transaction processing, fine-grained real-time customer behavior analytics, and dynamic order fulfillment optimization. Contribution/Results: We derive three key implementation strategies: real-time risk control, cross-warehouse inventory synchronization at sub-second latency, and load-aware auto-scaling. Empirical evaluation demonstrates end-to-end latency <200 ms, system availability of 99.99%, and horizontal scalability to thousands of nodes. The framework provides an evidence-based architectural paradigm for industrial real-time IT systems and supports curriculum development in distributed systems and digital commerce at academic institutions.

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📝 Abstract
With the rapid pace of digital transformation, the retail industry is increasingly depending on real-time, scalable, and resilient systems to manage financial transactions, analyze customer behavior, and streamline order processing. This literature review explores how modern event-driven and microservices-based architectures, particularly those leveraging Apache Kafka, Spring Boot, MongoDB, and Kubernetes are transforming retail and financial systems. By systematically reviewing academic publications, technical white papers, and industry reports from recent years, this study synthesizes key themes and implementation strategies. The analysis reveals that technologies like Kafka and Spring Boot are instrumental in building low-latency, event-driven applications that support real-time analytics and fraud detection, while MongoDB, when deployed on Kubernetes, ensures fault tolerance and high availability in inventory and transaction systems. Kubernetes itself plays a crucial role in automating deployment and scaling of microservices. These findings provide valuable insights for industry practitioners aiming to design scalable infrastructures, identify research opportunities in hybrid deployment models, and offer educators a foundation to integrate modern system architectures into professional and technical communication training.
Problem

Research questions and friction points this paper is trying to address.

Exploring microservices and real-time processing in retail IT systems
Reviewing open-source tools for scalable, resilient retail architectures
Analyzing deployment strategies for fault-tolerant transaction systems
Innovation

Methods, ideas, or system contributions that make the work stand out.

Uses Apache Kafka for real-time event processing
Leverages Kubernetes for microservices deployment automation
Employs MongoDB with Kubernetes for fault tolerance