Structural Decoupling and The Evolutionary Transition of Enterprise Systems: A Taxonomy of Microservice Extraction, Machine Learning-Assisted Boundary Detection, And Architectural Longevity DOI

• Dr. Marcus Thorne

  Institute for Software Systems Engineering, University of Zurich, Switzerland

  Author

The shift from monolithic architectures to microservices represents a fundamental change in the management of software complexity, scalability, and organizational alignment. This research provides an exhaustive analysis of the mechanisms governing this transition, focusing on the theoretical underpinnings of service extraction and the maintenance of long-lived software architectures. We investigate the persistence of the monolithic model, arguing that its continued relevance is predicated on specific economic and operational advantages that are often overlooked in the rush toward decentralization. Central to this study is the revisit of Conway’s Law, where we advocate for a task-based perspective on team-service alignment. The article further explores the extraction of microservices from legacy systems through a variety of techniques, including traditional refactoring and contemporary machine learning-assisted boundary detection. By establishing a comprehensive taxonomy of microservice anti-patterns, this work provides architects with a framework to avoid the common pitfalls of granularization. The methodology examines the optimization of microservice economics through granularity planning and the technical debt implications of architectural decay. Our findings suggest that successful modularization requires a symbiotic relationship between code-level refactoring and organizational task coordination, facilitated by automated identification tools that bridge the gap between abstract enterprise requirements and concrete service implementation.

Conway, M.: Conway’s Law, last accessed 01/10/2018.

???? K. S. Hebbar, “MACHINE LEARNING-ASSISTED SERVICE BOUNDARY DETECTION FOR MODULARIZING LEGACY SYSTEMS,” International Journal of Applied Engineering & Technology, vol. 04,no.02, pp. 401-414, Sep. 2022, https://romanpub.com/resources/ijaet-v4-2-2022-48.pdf

???? Kanjilal, Joydip. Advantages of monolithic architecture that prove it isn’t dead. 2020.

???? Kwan, I. et al.: Conway ’ s Law Revisited : The Evidence For a Task-based Perspective. IEEE Softw. 29, 1, (2011).

???? Levcovitz, A. et al.: Towards a Technique for Extracting Microservices from Monolithic Enterprise Systems. In: 3rd Brazilian Workshop on Software Visualization, Evolution and Maintenance (VEM). pp. 97–104 (2015).

???? Lewis, J., Fowler, M.: Microservices - a definition of this new architectural term, last accessed 01/10/2018.

???? Lilienthal, C.: Langlebige Software-Architekturen: Technische Schulden analysieren, begrenzen und abbauen. dpunkt.verlag (2017).

???? Mazlami, G. et al.: Extraction of Microservices from Monolithic Software Architectures. In: 2017 IEEE International Conference on Web Services (ICWS). pp. 524–531 (2017).

???? Mustafa, O., Gómez, J.M.: Optimizing economics of microservices by planning for granularity level Experience Report. (2017).

???? Newman, S.: Building Microservices. O’Reilly (2015).

???? Opdyke, W.F., Johnson, R.E.: Creating Abstract Superclasses by Refactoring of stract Classes Finding. Matrix. February, 66–73 (1993).

???? Rotem-Gal-Oz, Arnon. SOA Patterns. Simon and Schuster, 2012.

???? Schmitz, David. 10 Tips for failing badly at Microservices. 2017.

???? Taibi, Davide; Lenarduzzi, Valentina; Pahl, Claus. Microservices Anti Patterns: A Taxonomy. 2019.

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