Jenny Sun contributed to the mlflow/mlflow repository by building support for Databricks Lakebase as a new resource type within the MLflow model serving framework. She designed and implemented a dedicated Databricks Lakebase class in Python, integrating it into the existing resource management flow to enable seamless specification and handling of Lakebase instances as model dependencies. This work required a strong understanding of API development, Databricks, and MLOps practices, ensuring that Lakebase-backed models could be deployed efficiently. Jenny’s contribution addressed the need for flexible resource management in MLflow, demonstrating depth in both integration and end-to-end deployment workflow design.