Google Professional Machine Learning Engineer
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You have developed a regression model using tabular data and have set up a system using Vertex AI Pipelines, Vertex AI Training, Vertex AI Experiments, and Vertex AI Endpoints to train and deploy updated versions of the model. The model is currently deployed in a Vertex AI endpoint, and your users are making predictions by calling this endpoint. To ensure the model remains accurate, you need to monitor the feature data distribution and receive an email alert if it changes significantly, prompting you to retrigger the training pipeline and deploy an updated model. What should you do?
A
Use Vertex AI Model Monitoring. Enable prediction drift monitoring on the endpoint, and specify a notification email.
B
In Cloud Logging, create a logs-based alert using the logs in the Vertex AI endpoint. Configure Cloud Logging to send an email when the alert is triggered.
C
In Cloud Monitoring, create a logs-based metric and a threshold alert for the metric. Configure Cloud Monitoring to send an email when the alert is triggered.
D
Export the container logs of the endpoint to BigQuery. Create a Cloud Function to run a SQL query over the exported logs and send an email. Use Cloud Scheduler to trigger the Cloud Function.