Machine Learning Operations (MLOps) has become a critical discipline in effectively managing and deploying machine learning models. As the field of MLOps evolves, numerous technology architectures have emerged to address the challenges associated with scaling, automation, reproducibility, and collaboration. In this blog, we will delve into some of the recent technology architectures used in MLOps, highlighting their benefits and how they contribute to enhancing efficiency and scalability.