Event-Driven Microservices with Kafka and SQS for Market Development Tools

Abstract

Event-driven microservices constitute a paradigm of architectural construction of scalable, resilient, and data-driven digital platforms. With the market development tools, including, but not limited to, customer analytics systems, dynamic pricing engines, recommendation systems, and campaigns automation configuration frameworks, the requirement of real-time responsiveness and high-throughput data processing has gone up substantially. Apache Kafka and Amazon Simple Queue Service (SQS) are among the technologies that are of high value to support asynchronous communication, distributed event streaming, and task execution reliability. The architectural backgrounds of event driven micro services, a comparison of streaming and queue based messaging infrastructures, a hybrid theoretical framework (HEOMDM), as well as experimentation of performance metrics such as throughput, latency, scalability, and fault tolerance, were reviewed. The results show that distributed log systems like Kafka have better throughput and replayability whereas managed queue services like SQS are better in simplifying operations and reliability of tasks.In a hybrid integration strategy, a balanced solution is provided to the market development systems that need real-time analytics and reliable background processing. In this paper, the insight will be synthesized on how event-driven microservices can be applied to support next-generation market intelligence platforms via synthesizing analysis of architecture and theory, empirical analysis, and modeling systems. The other research concerns, which arise during the review, are observability, governance, cost optimization, and intelligent automation.