Exam Professional Machine Learning Engineer topic 1 question 143 discussion

A. Deploy the models to a Vertex AI endpoint using the traffic-split=0=80, PREVIOUS_MODEL_ID=20 configuration. The recommended approach to achieve the desired outcome would be to deploy the ML models to a Vertex AI endpoint and configure the traffic splitting using the traffic-split parameter. The traffic-split parameter enables you to split traffic between multiple versions of a model based on a percentage split. In this case, the newest model should receive the majority of the traffic, which can be achieved by setting the traffic-split parameter to 0=80. The previous version of the model should receive the remaining 20% of the traffic, which can be achieved by setting the PREVIOUS_MODEL_ID parameter to 20.

Vertex AI Traffic Splitting: Vertex AI natively supports traffic splitting between deployed models through the traffic-split parameter. This allows you to specify the desired traffic distribution (80% to the newest model, 20% to the previous one) during deployment.

Went with A

I think is A because traffic can be split across different versions when using Endpoints https://cloud.google.com/vertex-ai/docs/general/deployment#models-endpoint. The --trafic-split flag does exist, but in the question the syntax is incorrect, it should be "--traffic-split = [MODEL_ID_1=value, MODEL_ID_2=value]" as explained in https://cloud.google.com/sdk/gcloud/reference/ai/endpoints/deploy-model