Empowering Machine Learning Development with Service-Oriented Computing Principles

Mostafa Hadadian Nejad Yousefi, Viktoriya Degeler, Alexander Lazovik*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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Despite software industries’ successful utilization of Service-Oriented Computing (SOC) to streamline software development, machine learning (ML) development has yet to fully integrate these practices. This disparity can be attributed to multiple factors, such as the unique challenges inherent to ML development and the absence of a unified framework for incorporating services into this process. In this paper, we shed light on the disparities between services-oriented computing and machine learning development. We propose “Everything as a Module” (XaaM), a framework designed to encapsulate every ML artifacts including models, code, data, and configurations as individual modules, to bridge this gap. We propose a set of additional steps that need to be taken to empower machine learning development using services-oriented computing via an architecture that facilitates efficient management and orchestration of complex ML systems. By leveraging the best practices of services-oriented computing, we believe that machine learning development can achieve a higher level of maturity, improve the efficiency of the development process, and ultimately, facilitate the more effective creation of machine learning applications.
Original languageEnglish
Title of host publicationService-Oriented Computing
Subtitle of host publication17th Symposium and Summer School, SummerSOC 2023 Heraklion, Crete, Greece, June 25 – July 1, 2023
EditorsMarco Aiello, Johanna Barzen, Schahram Dustdar, Frank Leymann
Place of PublicationCham
Number of pages20
ISBN (Print)9783031457272, 9783031457289
Publication statusPublished - 12-Oct-2023
Event17th Symposium and Summer School: SOC 2023 - Crete, Greece
Duration: 25-Jun-20231-Jul-2023

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference17th Symposium and Summer School


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