Google Sample Question 6 of 15

You need to develop an online model prediction service that accesses pre-computed near-real-time features and returns a customer churn probability value. The features are saved in BigQuery and updated hourly using a scheduled query. You want this service to be low latency and scalable and require minimal maintenance. What should you do?

Source: Google Cloud OFFICIAL

Official sample question published by Google Cloud. WiseOwlLearns is not affiliated with Google LLC.

All explanations and Option Analyzer™ content are generated by WiseOwlLearns and are not endorsed by Google Cloud.

A 1. Configure Vertex AI Feature Store to automatically import features from BigQuery, and serve them to the model. 2. Deploy the prediction model as a custom Vertex AI endpoint, and enable automatic scaling. ✓ Correct
B 1. Configure a Cloud Run function that exports features from BigQuery to Memorystore. 2. Use a custom container on Google Kubernetes Engine to deploy a service that performs feature lookup from Memorystore and performs inference with an in-memory model.
C 1. Configure a Cloud Run function that exports features from BigQuery to Vertex AI Feature Store. 2. Use the online service API from Vertex AI Feature Store to perform feature lookup. Deploy the model as a custom prediction endpoint in Vertex AI, and enable automatic scaling.
D 1. Configure a Cloud Run function that exports features from BigQuery to Vertex AI Feature Store. 2. Use a custom container on Google Kubernetes Engine to deploy a service that performs feature lookup from Vertex AI Feature Store’s online serving API and performs inference with an in-memory model.
🦉 Explanation by WiseOwl Tutor™ — not endorsed by Google

Using Vertex AI Feature Store with BigQuery prioritizes low latency, scalability, requires minimal maintenance, and facilitates integration with other Vertex AI services as a fully managed solution. Cloud Run functions combined with GKE increase maintenance overhead significantly. Exporting features manually via Cloud Run functions to Vertex AI Feature Store is redundant because Feature Store can import them automatically from BigQuery.

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