Publikation - Einzelansicht
details for the publication
| author(s) | Leonhard Faubel and Klaus Schmid |
| title | A Systematic Analysis of MLOps Features and Platforms |
| publication type | Beitrag zu Zeitung oder Zeitschrift |
| journal | WiPiEC Journal - WiPiEC Journal - Works in Progress in Embedded Computing Journal |
| number / issue | 2 |
| volume | 10 |
| year | 2024 |
| URL | https://wipiec.digitalheritage.me/index.php/wipiecjournal/article/view/73 |
| abstract |
While many companies aim to use Machine Learning (ML) models, transitioning to deployment and practical application of such models can be very time-consuming and technically challenging. To address this, MLOps (ML Operations) offers processes, tools, practices, and patterns to bring ML models into operation. A large number of tools and platforms have been created to support developers in creating practical solutions. However, specific needs vary strongly in a situation-dependent manner, and a good overview of their characteristics is missing, making the architect’s task very challenging. We conducted a systematic literature review (SLR) of MLOps platforms, describing their qualities, features, tactics, and patterns. In this paper, we want to map the design space of MLOps platforms. We are guided by the Attribute-Driven Design (ADD) methodology. In this way, we want to |
