Microservices architecture has gained significant traction, in part owing to its potential to deliver scalable, robust, agile, and failure-resilient software products. Consequently, many companies that use large and complex software systems are actively looking for automated solutions to decompose their monolith applications into microservices. This paper rigorously examines 35 research papers selected from well-known databases using a Systematic Literature Review (SLR) protocol and snowballing method, extracting data to answer the research questions, and presents the following four contributions. First, the Monolith to Microservices Decomposition Framework (M2MDF) which identifies the major phases and key elements of decomposition. Second, a detailed analysis of existing decomposition approaches, tools and methods. Third, we identify the metrics and datasets used to evaluate and validate monolith to microservice decomposition processes. Fourth, we propose areas for future research. Overall, the findings suggest that monolith decomposition into microservices remains at an early stage and there is an absence of methods for combining static, dynamic, and evolutionary data. Insufficient tool support is also in evidence. Furthermore, standardised metrics, datasets, and baselines have yet to be established. These findings can assist practitioners seeking to understand the various dimensions of monolith decomposition and the community's current capabilities in that endeavour. The findings are also of value to researchers looking to identify areas to further extend research in the monolith decomposition space. 

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Decomposition of Monolith Applications Into Microservices Architectures: A Systematic Review

ExplorViz supports research on software visualization, software comprehension tasks and software collaboration. To achieve this, ExplorViz provides multi-level visualization from the software landscape layer toward the level of individual software applications. Via immersive 3D visualizations in virtual reality, ExplorViz also supports collaboration in software development teams. The research tool development commenced in 2012, and grew toward a powerful, extensible open-source software that has been employed in a variety of software engineering research projects. In this paper, we review its history, development and research impact.

ExplorViz: Research on software visualization, comprehension and collaboration

Background Microservices are an architectural approach of growing use, and the optimal granularity of a microservice directly affects the application's quality attributes and usage of computational resources. Determining microservice granularity is an open research topic. Methodology We conducted a systematic literature review to analyze literature that addresses the definition of microservice granularity. We searched in IEEE Xplore, ACM Digital Library and Scopus. The research questions were: Which approaches have been proposed to define microservice granularity and determine the microservices' size? Which metrics are used to evaluate microservice granularity? Which quality attributes are addressed when researching microservice granularity? Results We found 326 papers and selected 29 after applying inclusion and exclusion criteria. The quality attributes most often addressed are runtime properties (e.g., scalability and performance), not development properties (e.g., maintainability). Most proposed metrics were about the product, both static (coupling, cohesion, complexity, source code) and runtime (performance, and usage of computational resources), and a few were about the development team and process. The most used techniques for defining microservices granularity were machine learning (clustering), semantic similarity, genetic programming, and domain engineering. Most papers were concerned with migration from monoliths to microservices; and a few addressed green-field development, but none address improvement of granularity in existing microservice-based systems. Conclusions Methodologically speaking, microservice granularity research is at a Wild West stage: no standard definition, no clear development-operation trade-offs, and scarce conceptual reuse (e.g., few methods seem applicable or replicable in projects other than their initial proposal). These gaps in granularity research offer clear options to investigate on continuous improvement of the development and operation of microservice-based systems.

Defining and measuring microservice granularity-a literature overview.

In many enterprises the number of deployed applications is constantly increasing. Those applications - often several hundreds - form large software landscapes. The comprehension of such landscapes is frequently impeded due to, for instance, architectural erosion, personnel turnover, or changing requirements. Therefore, an efficient and effective way to comprehend such software landscapes is required. The current state of the art often visualizes software landscapes via flat graph-based representations of nodes, applications, and their communication.

Hierarchical software landscape visualization for system comprehension: A controlled experiment.

Today’s system migration focuses on modernizing legacy and monolithic systems towards microservices’ architectures. This study aims at understanding if and how quality attributes improvement are explicitly driving the migration process. We designed and conducted a systematic literature review on the topic. We started from over 2.000 potentially relevant research papers. We applied a selection procedure resulting in 58 selected research papers over the last six years. Our study revealed the following main findings: i) while still limited, quality attributes-driven migration is getting some attention, especially during the microservices identification phase; ii) we related the migration phases to the subset of quality attributes found in the papers accepted for this systematic review. 

A Systematic Literature Review on Migration to Microservices: a Quality Attributes perspective

Migrating monolithic software systems into microservices requires the application of decomposition techniques to find and select appropriate service boundaries. These techniques are often based on domain knowledge, static code analysis, and non-functional requirements such as maintainability.In this paper, we present our experience with an approach that extends static analysis with dynamic analysis of a legacy software system’s runtime behavior, including the live trace visualization to support the decomposition into microservices. Overall, our approach combines established analysis techniques for microservice decomposition, such as the bounded context pattern of domain-driven design, and enriches the collected information via dynamic software visualization to identify appropriate microservice boundaries.In collaboration with the German IT service provider adesso SE, we applied our approach to their real-word, legacy lottery application $in\vert {FOCUS}$ to identify good microservice decompositions for this layered monolithic Enterprise Java system.

Microservice Decomposition via Static and Dynamic Analysis of the Monolith

Migrating monolithic software systems into microservices requires the application of decomposition techniquesto find and select appropriate service boundaries. These techniques are often based on domain knowledge, static code analysis, and non-functional requirements such as maintainability. In this paper, we present our experience with an approach that extends static analysis with dynamic analysis of a legacy software system's runtime behavior, including the live trace visualization to support the decomposition into microservices. Overall, our approach combines established analysis techniques for microservice decomposition, such as the bounded context pattern of domain-driven design, and enriches the collected information via dynamic software visualization to identify appropriate microservice boundaries. In collaboration with the German IT service provider adesso SE, we applied our approach to their real-word, legacy lottery application in|FOCUS to identify good microservice decompositions for this layered monolithic Enterprise Java system.

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Microservice Decomposition via Static and Dynamic Analysis of the Monolith

Microservice Decomposition via Static and Dynamic Analysis of the Monolith