Good or Bad: Design Principles for Resolving Maintainability Issues for Microservices

Abstract

Microservices Architecture (MSA) style has gained popularity in the software industry as it provides a powerful method for developing applications that consist of several small, maintainable, independently deployable, and manageable services. The loosely coupled architecture style and dynamic nature of MSA cause many issues such as maintainability, security, latency, and performance. Anti-patterns are "poor" solutions to persistent issues. These solutions frequently make software systems more difficult to maintain. Microservice-based systems experience difficulties with maintainability and evolution, much like any other architectural style, because of these anti-patterns. As a result, adding and modifying functionalities becomes more and more difficult. The maintenance process also includes identifying anti-patterns within microservice-based systems, which improves the software's quality assessment. In this research, we analyze and understand the maintainability issues, anti-patterns, and suggested solutions related to microservices being discussed in the literature, and the Industry Forum. With the help of these blogs and academic literature, we propose a methodology to address the maintainability, design, and architecture issues for the improvement of microservices. We want to provide an extensive list of microservices anti-patterns and tool support to provide suggestions and categorize the best practices proposed by the professionals to support the research community and industry. In conclusion, we seek to improve the maintenance and quality of microservice-based systems with our semi-automatic tool-based approach. Our strategy is based on software re-engineering methods to extract useful data and has been created as an automated approach integrated with an add-in for Sparx System Enterprise Architecture (EA) for anti-patterns recognition from MS-based software applications. We have evaluated our approach on 20 open source microservices-based systems using precision and recall metric