Continuous Architecting with Microservices and DevOps: A Systematic Mapping Study

TL;DR

This systematic mapping study characterizes microservice architectural principles and patterns within DevOps, highlighting existing tools, techniques, and research gaps for continuous delivery in cloud-based systems.

Contribution

It provides a comprehensive mapping of microservice principles, patterns, and techniques used in DevOps, along with insights from 23 case studies and identifies research gaps.

Findings

Identified common microservice principles and patterns from 23 case studies.

Mapped existing microservices-specific techniques in DevOps pipelines.

Highlighted research gaps, especially in release phase techniques.

Abstract

Context: Several companies are migrating their information systems into the Cloud. Microservices and DevOps are two of the most common adopted technologies. However, there is still a lack of understanding how to adopt a microservice-based architectural style and which tools and technique to use in a continuous architecting pipeline. Objective: We aim at characterizing the different microservice architectural style principles and patterns in order to map existing tools and techniques adopted in the context of DevOps. Methodology: We conducted a Systematic Mapping Study identifying the goal and the research questions, the bibliographic sources, the search strings, and the selection criteria to retrieve the most relevant papers. Results: We identified several agreed microservice architectural principles and patterns widely adopted and reported in 23 case studies, together with a summary of the advantages, disadvantages, and lessons learned for each pattern from the case studies. Finally, we mapped the existing microservices-specific techniques in order to understand how to continuously deliver value in a DevOps pipeline. We depicted the current research, reporting gaps and trends. Conclusion: Different patterns emerge for different migration, orchestration, storage and deployment settings. The results also show the lack of empirical work on microservices-specific techniques, especially for the release phase in DevOps.