Machine Learning Models Monitoring in MLOps Context: Metrics and Tools
DOI:
https://doi.org/10.3991/ijim.v17i23.43479Keywords:
Machine Learning, MLOps, Metrics, Monitroring tools, Continuous MonitoringAbstract
In many machine learning projects, the lack of an effective monitoring system is a worrying issue. This leads to a series of challenges and risks that compromise the quality, reliability and sustainability of models deployed in production. As Machine Learning gains importance in various fields, poorly implemented monitoring represents a major obstacle to realizing its full potential. This article presents a comprehensive guide of machine learning models monitoring metrics and tool used in the MLOps context. The monitoring of metrics is important to evaluate and validate the performance of a machine-learning model, not only throughout the development phase but also during its deployment in the production environment. It enables real-time data to be collected on various metrics. The purpose of monitoring in MLOps context is to identify potential issues and adjustments made accordingly, guaranteeing consistent model quality and reliability. This article provides a comprehensive guide that introduces and explains a wide range of metrics used for continuous monitoring of ML systems at various stages of the MLOps lifecycle. Additionally, it presents a comparative analysis of available monitoring tools, enabling organizations to optimize their performance and ensure the seamless deployment of their machine learning applications. In essence, it underscores the critical importance of continuous monitoring and tailored metrics for ensuring the success and reliability of machine learning systems.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Anas BODOR, Meriem Hnida, Najima Daoudi
This work is licensed under a Creative Commons Attribution 4.0 International License.
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.
This journal has been awarded the SPARC Europe Seal for Open Access Journals (What's this?)