This is a dedicated watch page for a single video.
You are an ML engineer working for a logistics company that uses machine learning models to optimize delivery routes, predict maintenance needs, and forecast demand. The company wants to deploy several models into production, each serving different business functions but running on the same infrastructure to minimize costs. These models differ in the frequency of updates. The company is considering whether to use a multi-model deployment approach or a multi-container deployment approach on Amazon SageMaker to manage these models efficiently. Given these requirements, which deployment strategy is MOST SUITABLE for managing these diverse models?