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Systematic Mapping of Monolithic Applications to Microservices Architecture

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arxiv 2309.03796 v1 pith:TMXOCPWJ submitted 2023-09-07 cs.SE

classification cs.SE
keywords microservicesmonolithicarchitecturesoftwaresystemsarchitecturalconsideringdevelopment
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The aim of this paper to provide the solution microservices architecture as a popular alternative to monolithic architecture. It discusses the advantages of microservices and the challenges that organizations face when transitioning from a monolithic system. It presents a case study of a financial application and proposed techniques for identifying microservices on monolithic systems using domain-driven development concepts. In recent years, microservices architecture has emerged as a new architectural style in the software development industry. As legacy monolithic software becomes too large to manage, many large corporations are considering converting their traditional monolithic systems into small-scale, self-contained microservices. However, migrating from monolithic to microservices architecture is a difficult and challenging task. It presents a comparison of the two architectural styles and discusses the difficulties that led companies to switch to microservices. The study's findings suggest that the proposed technique can improve work performance and establish clear models, but it may not be useful for systems with lower levels of complexity. This research paper has practical implications for software architects and developers who are considering migrating from monolithic to microservices architecture.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Extracting Overlapping Microservices from Monolithic Code via Deep Semantic Embeddings and Graph Neural Network-Based Soft Clustering

    cs.SE 2025-08 reject novelty 6.0 of 10

    Mo2oM assigns classes to overlapping microservices using UniXcoder embeddings and NOCD soft clustering, claiming large gains in modularity metrics over hard-clustering baselines on four monoliths.

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