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GTMicro—microservice identification approach based on deep NLP transformer model for greenfield developments

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Abstract

Microservice architecture (MSA) has become a new style to modernize monolithic systems. MSA comprises small, independent, and autonomous services that communicate using lightweight network protocols. Recently few studies have proposed microservice identification techniques to embrace the designing of microservices. However, majority of the existing approaches are applicable to brownfield applications where monolithic application already exists. In this paper, we introduce a novel Greenfield Transformer-based Microservice identification approach—GTMicro to identify the bounded context as microservices for greenfield applications. GTMicro makes use of Bidirectional Encoder Representations from Transformers (BERT) which is a deep Learning model. BERT is used to compute the semantic textual similarity between use cases of the application and group them semantically. We validated GTMicro on two sample benchmark monolithic Java applications and migrated them toward microservices-based architecture. We mapped GTMicro to the state-of-the-art software quality assessment metrics and have presented the gains achieved through our results.

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Notes

  1. https://github.com/blueperf/acmeair-monolithic-java.

  2. https://github.com/blueperf/acmeair-mainservice-java.

  3. https://huggingface.co/sentence-transformers.

  4. https://github.com/DeepaliBajajDU/GTMicro.

  5. https://github.com/mybatis/jpetstore-6.

  6. https://github.com/DeepaliBajajDU/TeacherFeedbackSystem.

  7. https://spring.io/projects/spring-boot.

  8. https://github.com/DeepaliBajajDU/JPetStoreMicroservices.

  9. https://github.com/DeepaliBajajDU/TFA-microservice.

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Authors and Affiliations

  1. Department of Computer Science, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, Delhi, India

    Deepali Bajaj & Urmil Bharti

  2. Department of Computer Science, Vivekanand College, University of Delhi, Delhi, India

    Isha Gupta

  3. Department of Management, Atal Bihari Vajpayee School of Management and Entrepreneurship, Jawaharlal Nehru University, New Delhi, India

    Priya Gupta

  4. Department of Computer Science, School of Open Learning, University of Delhi, Delhi, India

    Asha Yadav

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  1. Deepali Bajaj
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  4. Priya Gupta
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Correspondence to Urmil Bharti.

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Bajaj, D., Bharti, U., Gupta, I. et al. GTMicro—microservice identification approach based on deep NLP transformer model for greenfield developments. Int. j. inf. tecnol. 16, 2751–2761 (2024). https://doi.org/10.1007/s41870-024-01766-5

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