Generative AI Leader Google Cloud's Generative AI Offerings Practice Question
A company is using Vertex AI Model Registry to manage multiple versions of its custom generative model. They want to automatically route a percentage of traffic to a new model version for testing. What should they do?
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
✓
Deploy both versions to the same endpoint and adjust traffic split settings
Vertex AI Endpoints support traffic splitting between model versions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set up a Cloud Tasks queue to distribute requests
Why it's wrong here
Cloud Tasks queues asynchronous work items for later execution; it does not inspect or split live inference requests between model versions. It suits decoupling background jobs from request handling, while Vertex AI endpoint traffic splitting performs the percentage-based version routing required here.
- ✗
Create a new endpoint for each version
Why it's wrong here
Separate endpoints isolate versions but provide no mechanism to send a defined percentage of requests to each; clients must choose one endpoint. Multiple endpoints suit independent deployment and scaling of distinct models, whereas a single endpoint with traffic splits delivers the required percentage routing.
- ✓
Deploy both versions to the same endpoint and adjust traffic split settings
Why this is correct
Deploying both model versions to one endpoint and adjusting its traffic split routes a defined percentage of requests to the new version. This satisfies the stem's requirement for automatic percentage-based traffic routing for testing, which the Model Registry alone cannot perform.
- ✗
Use a load balancer in front of the endpoints
Why it's wrong here
A load balancer distributes connections but cannot read Vertex AI Model Registry version metadata or apply percentage splits across deployed model versions. It suits generic HTTP traffic distribution; Vertex AI's own traffic-split configuration on an endpoint performs the version routing described.
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