Handling Communication via APIs for Microservices

TL;DR

This paper proposes an ID-passing API approach for microservice communication, reducing dependencies and refactoring efforts, and demonstrating improved performance over JSON-based methods in Java applications.

Contribution

It introduces an ID-passing API technique and an algorithm to minimize APIs, enhancing microservice communication and reducing manual refactoring.

Findings

Better time and memory performance with ID passing

Automated refactoring reduces manual effort by 40-60%

Effective in five Java applications

Abstract

Enterprises in their journey to the cloud, want to decompose their monolith applications into microservices to maximize cloud benefits. Current research focuses a lot on how to partition the monolith into smaller clusters that perform well across standard metrics like coupling, cohesion, etc. However, there is little research done on taking the partitions, identifying their dependencies between the microservices, exploring ways to further reduce the dependencies, and making appropriate code changes to enable robust communication without modifying the application behaviour. In this work, we discuss the challenges with the conventional techniques of communication using JSON and propose an alternative way of ID-passing via APIs. We also devise an algorithm to reduce the number of APIs. For this, we construct subgraphs of methods and their associated variables in each class and relocate them to their more functionally aligned microservices. Our quantitative and qualitative studies on five public Java applications clearly demonstrate that our refactored microservices using ID have decidedly better time and memory complexities than JSON. Our automation reduces 40-60\% of the manual refactoring efforts.