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Defining and measuring microservice granularity-a literature overview.

Fredy H Vera-Rivera1,2,3, Carlos Gaona2, Hernán Astudillo4

  • 1GIA Research Group, Universidad Francisco de Paula Santander, Cúcuta, Norte de Santander, Colombia.

Peerj. Computer Science
|October 4, 2021
PubMed
Summary
This summary is machine-generated.

Determining microservice granularity is crucial for application quality. Current research lacks standardized definitions and reusable methods, indicating a need for further investigation into development-operation trade-offs for microservice architectures.

Keywords:
MetricsMicro service architectureMicro-service granularityMicroservices decompositionMonolith to microservicesQuality attributtesService computingSistematic literature review

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Area of Science:

  • Computer Science
  • Software Engineering
  • Distributed Systems

Background:

  • Microservices architecture is increasingly adopted.
  • Optimal microservice granularity impacts application quality attributes and resource utilization.
  • Defining microservice granularity remains an open research challenge.

Purpose of the Study:

  • To systematically review literature on defining microservice granularity.
  • To identify proposed approaches, metrics, and quality attributes related to microservice granularity.
  • To analyze the current state of research in microservice granularity.

Main Methods:

  • Systematic literature review.
  • Searches conducted in IEEE Xplore, ACM Digital Library, and Scopus.
  • Analysis of 29 selected papers based on research questions regarding granularity definition, metrics, and quality attributes.

Main Results:

  • Runtime quality attributes (scalability, performance) are prioritized over development attributes (maintainability).
  • Metrics primarily focus on product aspects (static and runtime) rather than team/process.
  • Common techniques include machine learning, semantic similarity, genetic programming, and domain engineering.
  • Research predominantly addresses monolith-to-microservice migration, with limited focus on green-field or existing system improvements.

Conclusions:

  • Microservice granularity research is methodologically immature with no standard definitions or clear development-operation trade-offs.
  • Limited conceptual reuse hinders replicability across projects.
  • Significant opportunities exist for research on continuous improvement of microservice-based systems' development and operation.