Generative AI Leader Vertex AI Model Registry Practice Question
Network Topology
A developer runs this command: `gcloud ai models upload --region=us-central1 --display-name=my-model --artifact-uri=gs://my-bucket/model.pkl`. What is the primary purpose?
⚠ Common exam trap
Google Cloud exams often test the distinction between model registration (uploading a trained artifact) and model training or deployment. Candidates may confuse `gcloud ai models upload` with starting a training job or deploying a model, but this command only stores the model artifact in the registry for versioning and reuse.
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
✓
Upload a model artifact to Model Registry
The command `gcloud ai models upload` uploads a local model artifact (model.pkl stored in Cloud Storage) to the Vertex AI Model Registry. This is used for versioning and managing trained models, not for initiating training, deployment, or pipeline creation. The Model Registry stores the model artifact for later use in deployments or predictions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a training pipeline
Why it's wrong here
The command registers an existing model artefact from Cloud Storage; training pipelines are created with `gcloud ai custom-jobs create` or pipeline templates. Training is tempting because models often originate from training runs, but this command consumes an already-trained artefact rather than producing one.
- ✗
Deploy a model to an endpoint
Why it's wrong here
The command uploads model artefacts to the Vertex AI Model Registry; deployment requires a separate `gcloud ai endpoints deploy-model` call. Deployment is tempting because uploaded models are typically deployed next, but upload only registers the model, it does not create an endpoint or serve predictions.
- ✗
Train a model
Why it's wrong here
The command imports a pre-built model artefact into the Vertex AI Model Registry; it does not execute training code or consume training data. Training is tempting because the uploaded artefact is usually the output of a prior training job, but this command performs no computation on the model itself.
- ✓
Upload a model artifact to Model Registry
Why this is correct
The command registers a trained model artefact stored in Cloud Storage with Vertex AI Model Registry in us-central1, assigning the display name my-model. It does not deploy an endpoint or run training; it creates the registry entry for versioning and deployment.
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Senior Network & Security Engineer · founder of Courseiva
This Generative AI Leader practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Generative AI Leader exam.