Understanding the Issues, Their Causes and Solutions in Microservices Systems: An Empirical Study

TL;DR

This empirical study analyzes issues, causes, and solutions in microservices systems through data from issue trackers, interviews, and surveys, providing comprehensive taxonomies and a future research framework for improving microservices engineering.

Contribution

It offers the first extensive taxonomy of issues, causes, and solutions in microservices, based on mixed-methods data from open-source projects and practitioners worldwide.

Findings

Technical Debt, CI/CD, Exception Handling, Security are dominant issues.

Main causes include programming errors, missing features, invalid configurations.

Identified 177 solution types for addressing microservices issues.

Abstract

Many small to large organizations have adopted the Microservices Architecture (MSA) style to develop and deliver their core businesses. Despite the popularity of MSA in the software industry, there is a limited evidence-based and thorough understanding of the types of issues (e.g., errors, faults, failures, and bugs) that microservices system developers experience, the causes of the issues, and the solutions as potential fixing strategies to address the issues. To ameliorate this gap, we conducted a mixed-methods empirical study that collected data from 2,641 issues from the issue tracking systems of 15 open-source microservices systems on GitHub, 15 interviews, and an online survey completed by 150 practitioners from 42 countries across 6 continents. Our analysis led to comprehensive taxonomies for the issues, causes, and solutions. The findings of this study informthat Technical Debt, Continuous Integration and Delivery, Exception Handling, Service Execution and Communication, and Security are the most dominant issues in microservices systems. Furthermore, General Programming Errors, Missing Features and Artifacts, and Invalid Configuration and Communication are the main causes behind the issues. Finally, we found 177 types of solutions that can be applied to fix the identified issues. Based on our study results, we propose a future research framework that outlines key problem dimensions and actionable study strategies to support the engineering of emergent and next-generation microservices systems.