JOURNAL ARTICLE

Actor-Driven Decomposition of Microservices through Multi-level Scalability Assessment

Matteo CamilliCarmine ColarussoBarbara RussoEugenio Zimeo

Year: 2023 Journal:   ACM Transactions on Software Engineering and Methodology Vol: 32 (5)Pages: 1-46   Publisher: Association for Computing Machinery

Abstract

The microservices architectural style has gained widespread acceptance. However, designing applications according to this style is still challenging. Common difficulties concern finding clear boundaries that guide decomposition while ensuring performance and scalability. With the aim of providing software architects and engineers with a systematic methodology, we introduce a novel actor-driven decomposition strategy to complement the domain-driven design and overcome some of its limitations by reaching a finer modularization yet enforcing performance and scalability improvements. The methodology uses a multi-level scalability assessment framework that supports decision-making over iterative steps. At each iteration, architecture alternatives are quantitatively evaluated at multiple granularity levels. The assessment helps architects to understand the extent to which architecture alternatives increase or decrease performance and scalability. We applied the methodology to drive further decomposition of the core microservices of a real data-intensive smart mobility application and an existing open-source benchmark in the e-commerce domain. The results of an in-depth evaluation show that the approach can effectively support engineers in ( i ) decomposing monoliths or coarse-grained microservices into more scalable microservices and ( ii ) comparing among alternative architectures to guide decision-making for their deployment in modern infrastructures that orchestrate lightweight virtualized execution units.

Keywords:
Microservices Computer science Scalability Software deployment Distributed computing Software engineering Benchmark (surveying) Decomposition Architectural style Architecture Computer architecture Cloud computing Database Operating system

Metrics

21
Cited By
9.23
FWCI (Field Weighted Citation Impact)
59
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Software System Performance and Reliability
Physical Sciences →  Computer Science →  Computer Networks and Communications
Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
Advanced Software Engineering Methodologies
Physical Sciences →  Computer Science →  Artificial Intelligence
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