A Systematic Literature Review of MLOps Adoption in Software Development Companies: Attributes, Maturity, Benefits and Challenges

Abstract

Software development companies (SDCs) have started to include Machine Learning (ML) within their projects, which has allowed ML models to not be left behind to the experimentation stage, but to move to the production stage, here Machine Learning Operations (MLOps) arises to decrease the gap between operations, development and data science teams. Therefore, this article presents a systematic literature review on the adoption of MLOps in SDCs, based on the analysis of 28 primary studies. The findings of this article reflect the efforts of the scientific community to define the principles, roles, artifacts, benefits, challenges, and crucial factors for the implementation of MLOps in SDCs.

Ähnliche Arbeiten