Option A is incorrect because it does not separate the training dataset into two tables based on the

features, which is necessary to train the two models separately and accurately.

Option B is incorrect because it does not separate the training dataset into two tables based on the

features, and because it uses the same monitoring-config-from parameter for both models, which

would not account for the different feature selections.

Option C is incorrect because it deploys the models to two separate endpoints, which would increase

the management effort and complexity of the pipeline.

Option D is correct because it separates the training dataset into two tables based on the features,

which would enable the two models to be trained separately and accurately. It also deploys both

models to the same endpoint, which would simplify the pipeline and reduce the management effort.

It also submits a Vertex Al Model Monitoring job with a monitoring-config-from parameter that

accounts for the model IDs and training datasets, which would enable the skew detection to work

properly for each model.