A Prescriptive Model for Migration to Microservices Based on SDLC Artifacts

Deepali Bajaj; Urmil Bharti; Anita Goel; S. C. Gupta

doi:10.13052/jwe1540-9589.20312

Authors

Deepali Bajaj Department of Computer Science, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, Delhi, India https://orcid.org/0000-0003-2655-3001
Urmil Bharti Department of Computer Science, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, Delhi, India
Anita Goel Department of Computer Science, Dyal Singh College, University of Delhi, Delhi, India
S. C. Gupta Department of Computer Science, Indian Institute of Technology, Delhi, India

DOI:

https://doi.org/10.13052/jwe1540-9589.20312

Keywords:

Microservices, decomposition, migration, extraction, slicing, identifying, brownfield development, greenfield development, microservices architecture (MSA)

Abstract

Microservices architectural style is gaining popularity in industry and is being widely adopted by large corporations like Amazon, Netflix, Spotify, eBay, and many more. Several other organizations are also preferring to migrate their existing enterprise scale applications to microservices architecture. Researchers have proposed various approaches for microservices decomposition to be used in migrating or rebuilding a monolithic application to microservices. Applying any available approach to an existing monolithic application is not a straightforward decision; thus, there is a need for guidelines that assist in the migration process. There are various challenges in a migration process because different migration approaches use different sets of input data to identify microservices. Since the available migration techniques are not structured, logically, selection of an appropriate migration strategy is a difficult decision for any system architect. So, it is a recurrent open research question – which migration technique should be adopted to get microservices for a legacy monolithic application? This paper addresses this research challenge by examining existing approaches for microservices migration and groups them based on software development life cycle (SDLC) artifacts. Our research also proposes a microservices prescriptive model (MPM) from the existing prominent microservice migration techniques. This model provides recommendation (1) for refactoring an existing legacy system to microservices, and (2) for new microservices development projects. Our study also helps in gaining more insight about greenfield and brownfield development approaches in microservices applications. Moreover, researchers and practitioners of the field can benefit from this model to further validate their migration approaches based on the available system artifacts.

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Author Biographies

Deepali Bajaj, Department of Computer Science, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, Delhi, India

Deepali Bajaj has over 14 years of teaching experience as Assistant Professor in Department of Computer Science, Shaheed Rajguru College of Applied Sciences for Women (University of Delhi). She is currently doing her research in the area of Cloud and Distributed Computing. Her key research areas are Microservices and Function as a service (FaaS) of serverless technology. She has authored several national and international research publications.

Urmil Bharti, Department of Computer Science, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, Delhi, India

Urmil Bharti has over 14 years of teaching experience as Assistant Professor in Department of Computer Science, Shaheed Rajguru College of Applied Sciences for women (University of Delhi). Earlier she has more than 10 years of industry experience. Her last designation was Senior Quality Analyst. She is currently doing her research in the area of Cloud and Distributed Computing. Her key research area is open source serverless frameworks. She has authored several national and international research publications.

Anita Goel, Department of Computer Science, Dyal Singh College, University of Delhi, Delhi, India

Anita Goel is an Associate Professor in Department of Computer Science, Dyal Singh College, University of Delhi, India. She has received her Ph.D. in Computer Science and Masters in Computer Applications from Jamia Millia Islamia and Department of Computer Science (University of Delhi), respectively. She has a work experience of more than 30 years. She is a visiting faculty to Delhi Technological University and NIIT University. From 2009–10, she was Fellow in Computer Science, at Institute of Life Long Learning (ILLL) in University of Delhi. She has served as member of program committee of International conferences like IEEE BigData Congress 2015 and ICWI 2015. She has guided several students for their doctoral studies and has travelled internationally to present research papers. She has authored books in Computer Science and has several national and international research publications.

S. C. Gupta, Department of Computer Science, Indian Institute of Technology, Delhi, India

S. C. Gupta is B.Tech (EE) from IIT Delhi and has worked at Computer Group at Tata Institute of Fundamental Research and NCSDCT (now C-DAC Mumbai), Till recently, he worked as Deputy Director General, Scientist-G and Head of Training at National Informatics Centre, New Delhi and was responsible for keeping its 3000 scientists/ engineers up to date in various technologies. He has extensive experience in design and development of large Complex Software Systems. Currently he is a Visiting Faculty at Dept of Computer Science and Engineering, IIT Delhi. His research interests includes Software Engineering, Data Bases and Cloud Computing. He has been teaching Cloud Computing at IIT Delhi, which includes emerging disruptive technologies like SDN and SDS. He has guided many M.Tech & Ph.D. Research students in these technologies and has many publications in Software Engineering and Cloud Technology in National and International Conferences and Journals.

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