Professional Insights into Benefits and Limitations of Implementing MLOps Principles

Gabriel Araujo, Marcos Kalinowski, Markus Endler, Fabio Calefato

2024

Abstract

Context: Machine Learning Operations (MLOps) has emerged as a set of practices that combines development, testing, and operations to deploy and maintain machine learning applications. Objective: In this paper, we assess the benefits and limitations of using the MLOps principles in online supervised learning. Method: We conducted two focus group sessions on the benefits and limitations of applying MLOps principles for online machine learning applications with six experienced machine learning developers. Results: The focus group revealed that machine learning developers see many benefits of using MLOps principles but also that these do not apply to all the projects they worked on. According to experts, this investment tends to pay off for larger applications with continuous deployment that require well-prepared automated processes. However, for initial versions of machine learning applications, the effort taken to implement the principles could enlarge the project’s scope and increase the time needed to deploy a first version to production. The discussion brought up that most of the benefits are related to avoiding error-prone manual steps, enabling to restore the application to a previous state, and having a robust continuous automated deployment pipeline. Conclusions: It is important to balance the trade-offs of investing time and effort in implementing the MLOps principles considering the scope and needs of the project, favoring such investments for larger applications with continuous model deployment requirements.

Paper Citation

in Harvard Style

Araujo G., Kalinowski M., Endler M. and Calefato F. (2024). Professional Insights into Benefits and Limitations of Implementing MLOps Principles. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 305-312. DOI: 10.5220/0012741100003690

in Bibtex Style

@conference{iceis24,
author={Gabriel Araujo and Marcos Kalinowski and Markus Endler and Fabio Calefato},
title={Professional Insights into Benefits and Limitations of Implementing MLOps Principles},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2024},
pages={305-312},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012741100003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Professional Insights into Benefits and Limitations of Implementing MLOps Principles
SN - 978-989-758-692-7
AU - Araujo G.
AU - Kalinowski M.
AU - Endler M.
AU - Calefato F.
PY - 2024
SP - 305
EP - 312
DO - 10.5220/0012741100003690
PB - SciTePress