ml-engineer-pro video for you've been assigned the task of deploying prototype code into a production environment. The feature engineering component is written
You've been assigned the task of deploying prototype code into a production environment. The feature engineering component is written in PySpark and operates on Dataproc Serverless, while model training is conducted using a Vertex AI custom training job. These two steps are currently disjointed, requiring manual execution of model training after the feature engineering phase concludes. Your objective is to establish a scalable and maintainable production workflow that seamlessly connects and tracks these steps. What should you do?