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Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions

Exhibit

{
  "name": "projects/my-project/locations/us-central1/endpoints/123456",
  "displayName": "my-endpoint",
  "deployedModels": [
    {
      "id": "789",
      "model": "projects/my-project/locations/us-central1/models/456",
      "dedicatedResources": {
        "machineSpec": {
          "machineType": "n1-standard-2",
          "acceleratorType": "NVIDIA_TESLA_T4",
          "acceleratorCount": 1
        },
        "minReplicaCount": 1,
        "maxReplicaCount": 3
      },
      "automaticResources": null
    }
  ]
}

Refer to the exhibit. This JSON describes a Vertex AI endpoint with a deployed model. Which statement about scaling is true?

⚠ Common exam trap

Google Cloud often tests the misconception that any endpoint with a `minReplicaCount` and `maxReplicaCount` automatically enables scaling, but the trap here is that without `autoscalingMetricSpecs`, the endpoint uses dedicated resources and does not scale dynamically — the `maxReplicaCount` is ignored if autoscaling metrics are absent.

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

✓

The endpoint uses only dedicated resources, no automatic scaling

The JSON shows that the endpoint is configured with `dedicatedResources` and no `autoscalingMetricSpecs` or `minReplicaCount`/`maxReplicaCount` fields. In Vertex AI, when you specify only `machineSpec` and a fixed `minReplicaCount` (here implicitly 1) without a `maxReplicaCount` or autoscaling metrics, the endpoint uses dedicated resources with no automatic scaling — the model will always run on exactly the number of replicas you define, regardless of load.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
The endpoint uses only dedicated resources, no automatic scaling
Why this is correct
DedicatedResources with min/max replicas means manual scaling.
✗
The endpoint will automatically scale based on GPU utilization
Why it's wrong here
GPU utilization is not a scaling metric in dedicated resources.
✗
The endpoint will scale from 1 to 3 replicas based on load using automatic scaling
Why it's wrong here
It uses dedicated resources, not automatic scaling.
✗
The endpoint can scale to zero when not in use
Why it's wrong here
Dedicated resources do not support scaling to zero.

Go deeper

Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions

Exhibit

Why each option matters

Option-by-option breakdown

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