From a Monolithic Big Data System to a Microservices Event-Driven Architecture

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[Context] Data-intensive systems, a.k.a. big data systems (BDS), are software systems that handle a large volume of data in the presence of performance quality attributes, such as scalability and availability. Before the advent of big data management systems (e.g. Cassandra) and frameworks (e.g. Spark), organizations had to cope with large data volumes with custom-tailored solutions. In particular, a decade ago, Tecgraf/PUC-Rio developed a system to monitor truck fleet in real-time and proactively detect events from the positioning data received. Over the years, the system evolved into a complex and large obsolescent code base involving a costly maintenance process. [Goal] We report our experience on replacing a legacy BDS with a microservice-based event-driven system. [Method] We applied action research, investigating the reasons that motivate the adoption of a microservice-based event-driven architecture, intervening to define the new architecture, and documenting the challenges and lessons learned. [Results] We perceived that the resulting architecture enabled easier maintenance and faultisolation. However, the myriad of technologies and the complex data flow were perceived as drawbacks. Based on the challenges faced, we highlight opportunities to improve the design of big data reactive systems. [Conclusions] We believe that our experience provides helpful takeaways for practitioners modernizing systems with data-intensive requirements. © 2020 IEEE.
Original languageEnglish
Title of host publicationProceedings of 46th Euromicro Conference on Software Engineering and Advanced Applications
Publication date2020
Article number9226286
Publication statusPublished - 2020
Event46th Euromicro Conference on Software Engineering and Advanced Applications - SEAA 2020; - Virtuel, Slovakia
Duration: 26 Aug 202028 Aug 2020


Conference46th Euromicro Conference on Software Engineering and Advanced Applications - SEAA 2020;

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