Scalable Microservices Architecture for Data-Intensive Applications
TL;DR
The analysis of performance has shown that the proposed solution is much better in terms of throughput, latency and fault isolation than the conventional architectures, proving that microservices architecture with proper design presents a solid base of scalable data-intensive systems.
Abstract
The modern software architectures have never had higher requirements than they do currently as the result of the rapid growth of data-intensive applications in the fields of cloud computing, Internet of Things (IoT), artificial intelligence, and large-scale web services. Amongst the problems that traditional monolithic systems cannot cope with are scalability, fault tolerance and on-going deployment demands using extensive data workloads. The consequence of this is that microservice architecture has become an architecture with potential to make systems that are scalable, resilient, and maintainable. The paper provides a detailed research of scalable microservices architecture specifically to the data intensive applications. The suggested architecture breaks the complex applications in loosely coupled, independently deployable services, which are specialized in the processing of specific data. Such fundamental architectural values as service granularity, data decentralization, containerization, orchestration, and asynchronous communication are discussed in detail. An overlay-based architectural design is presented to help scalability horizontally and provide high availability as well as efficient data management. Also, the analysis of current architectural methods is done in this study based on the comprehensive literature review that finds out the limitations in scalability, consistency, and operational complexity. An end-to-end process is suggested, where distributed data stores are combined with event-driven communication and automatic scaling processes. The analysis of performance has shown that the proposed solution is much better in terms of throughput, latency and fault isolation than the conventional architectures. These findings prove that microservices architecture with proper design presents a solid base of scalable data-intensive systems. The paper is useful to the researchers and practitioners who need to develop high-performance, cloud-native applications using micro services.