Toward End-to-End MLOps Tools Map: A Preliminary Study based on a Multivocal Literature Review

April 06, 2023 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Sergio Moreschi, Gilberto Recupito, Valentina Lenarduzzi, Fabio Palomba, David Hastbacka, Davide Taibi arXiv ID 2304.03254 Category cs.SE: Software Engineering Citations 7 Venue arXiv.org Last Checked 4 months ago
Abstract
MLOps tools enable continuous development of machine learning, following the DevOps process. Different MLOps tools have been presented on the market, however, such a number of tools often create confusion on the most appropriate tool to be used in each DevOps phase. To overcome this issue, we conducted a multivocal literature review mapping 84 MLOps tools identified from 254 Primary Studies, on the DevOps phases, highlighting their purpose, and possible incompatibilities. The result of this work will be helpful to both practitioners and researchers, as a starting point for future investigations on MLOps tools, pipelines, and processes.
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