Improvement suggestions for software based on microservice architecture with code analysis techniques

Microservice is an architectural style that has recently started gaining popularity to become a new architectural phenomenon. Microservice architecture provides new opportunities to deploy scalable, language free and dynamically adjustable applications. Microservice based architecture is defined as a software architecture pattern for development of distributed applications, where the application is comprised of a number of smaller independent components; these components are small application in-themselves. This architecture style has gained popularity over the last few years to describe a particular way of designing software applications as suites of independently deployable services. There are certain common characteristics around organization around business capability, automated deployment, built released with automated processes, intelligence in the endpoints, and decentralized control of languages and data. On the other hand, there is no precise definition of this architectural style and mentioned benefits come with challenges, such as discovering services over network, security management, communication optimization, data sharing and performance. Furthermore, team size, culture, skills, productivity etc. have an impact on software development. Unfortunately, there is no strict rule about these challenges; there are some practices that have been proven in real-world systems. According to this characteristic features and tradeoffs, defining new metrics and practices to measure software quality and suitability for microservice practices were studied. New metrics were defined to measure service size and inter-service communication. In order to check compliance with these metrics, static analysis tool which name is MISKAA to analyze software based on microservice architecture were developed. A sample ticket selling application to evaluate these metrics and practices were implemented. Analysis results would be helpful for project team to improve software quality and to detect bugs or bad practices.