PDE Preparing and Using Data for Analysis Practice Question
You are using Vertex AI Feature Store to serve features for online predictions. Your model requires features from multiple sources with low latency (<10ms). Which type of serving should you use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Online serving with Bigtable
Online serving (with Bigtable as backing store) provides low-latency feature retrieval. Offline serving is for batch predictions. Feature Store supports both; online is for real-time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Online serving with Cloud SQL
Why it's wrong here
Feature Store does not support Cloud SQL as online store.
- ✗
Offline serving with BigQuery
Why it's wrong here
Offline serving is for batch, not low-latency.
- ✓
Online serving with Bigtable
Why this is correct
Online serving uses Bigtable for low-latency feature retrieval.
- ✗
Offline serving with Cloud Storage
Why it's wrong here
Cloud Storage is for batch, not low-latency.
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