- A
VertexEndpointDeployOp
Why wrong: This deploys a model to an endpoint, not register it.
- B
CreateModelVersionsOp
Why wrong: Not a standard component name.
- C
ModelRegisterOp
Why wrong: Not a standard component name.
- D
VertexModelUploadOp
This component uploads a model to the Vertex AI Model Registry.
Question 944 of 1,000
PMLE Automating and Orchestrating ML Pipelines Practice Question
This PMLE practice question tests your understanding of automating and orchestrating ml pipelines. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You have a Vertex AI pipeline that trains a model and outputs a Model artifact. You want to register this model in the Vertex AI Model Registry. Which pre-built Google Cloud Pipeline Components component 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
✓
VertexModelUploadOp
The correct component is VertexModelUploadOp because it is specifically designed to upload a trained model artifact to the Vertex AI Model Registry, creating a new model version or a new model if one does not exist. This component takes the model artifact from a pipeline step and registers it, making it available for deployment or version management.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
VertexEndpointDeployOp
Why it's wrong here
This deploys a model to an endpoint, not register it.
- ✗
CreateModelVersionsOp
Why it's wrong here
Not a standard component name.
- ✗
ModelRegisterOp
Why it's wrong here
Not a standard component name.
- ✓
VertexModelUploadOp
Why this is correct
This component uploads a model to the Vertex AI Model Registry.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between model registration and deployment, so candidates mistakenly choose VertexEndpointDeployOp thinking it registers the model, when in fact it only deploys an already-registered model to an endpoint.
Detailed technical explanation
How to think about this question
Under the hood, VertexModelUploadOp calls the Vertex AI Model Service's upload API, which accepts a model artifact URI (typically from a Cloud Storage bucket) and metadata such as the model's display name, description, and labels. This component supports versioning by automatically incrementing the version ID when uploading a model with the same display name, enabling lineage tracking across pipeline runs. In a real-world scenario, you might use VertexModelUploadOp in a CI/CD pipeline to register a retrained model after each successful training run, ensuring that only validated models are promoted to the registry.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PMLE question test?
Automating and Orchestrating ML Pipelines — This question tests Automating and Orchestrating ML Pipelines — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: VertexModelUploadOp — The correct component is VertexModelUploadOp because it is specifically designed to upload a trained model artifact to the Vertex AI Model Registry, creating a new model version or a new model if one does not exist. This component takes the model artifact from a pipeline step and registers it, making it available for deployment or version management.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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