Your team is working on a project that involves training a large number of machine learning (ML) models using various algorithms, parameters, and datasets. The models are being trained using two services: Vertex AI Pipelines and Vertex AI Workbench notebook instances. The goal is to compare the performance of all the models across these two services efficiently. How should you store the parameters and metrics with minimal effort to facilitate this comparison?