Exam Professional Machine Learning Engineer topic 1 question 182 discussion

Minimal Downtime: By deploying the new model to the existing endpoint, you avoid any service interruptions caused by creating and switching to a completely new endpoint. Versioning: Setting the parentModel parameter allows you to track the lineage of your models and easily revert to the previous version if needed. Traffic Control: Vertex AI lets you control traffic allocation between different versions of a model deployed on the same endpoint. Setting the new model to 100% traffic directs all user requests to the new version.

My Answer: C In the context of deploying machine learning models, setting the **`parentModel`** parameter to the model ID of the currently deployed model means that the new model being deployed is created as a child model or an iteration of the existing model. This allows the new model to inherit certain properties or characteristics from the existing model, such as the architecture, hyperparameters, or feature transformations. Create a new Endpoint is Unnecessary.

Optionally set this model as the default version. The default version is preselected whenever the model is used for prediction (although you can still select other versions). https://cloud.google.com/vertex-ai/docs/model-registry/versioning

a,c -creating new endpoint is an unnecessary disruption to the application d - doesn't work, two models are on the same endpoint and traffic is still going through the old model

Leverages existing endpoint: Using the same endpoint maintains the same endpoint URL, avoiding DNS updates and potential service interruptions. Gradual traffic transition: Vertex AI allows you to gradually shift traffic between model versions, ensuring a smooth transition without impacting users. Clear versioning: Setting parentModel establishes a relationship between the new model and the existing one, aiding in organization and tracking model lineage.