The answer is that no version of the model has been deployed to the endpoint. Even if the model resource and the endpoint resource both exist, Vertex AI requires you to explicitly deploy a specific model version to the endpoint before it can serve online predictions. This step creates the underlying serving infrastructure and associates the model’s artifact with the endpoint’s prediction URL. On the Google Professional Data Engineer exam, this scenario tests your understanding of the deployment lifecycle: creating a model and creating an endpoint are separate prerequisites, but the critical action that enables online prediction is the deployment of a model version to that endpoint. A common trap is assuming that simply having a model and an endpoint is sufficient, or confusing model creation with deployment. Remember the mnemonic: “Create, then deploy—or your predictions will be empty.”
PDE Operationalizing machine learning models Practice Question
This PDE practice question tests your understanding of operationalizing machine learning models. 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.
Exhibit
Refer to the exhibit.
Error log from Cloud Logging:
{
"textPayload": "Prediction failed: Model 'projects/my-project/locations/us-central1/models/12345' is not deployed to endpoint 'projects/my-project/locations/us-central1/endpoints/67890'. Ensure the model is deployed to the endpoint before making predictions.",
"timestamp": "2024-03-15T10:30:00Z",
"resource": {
"type": "aiplatform.googleapis.com/Endpoint"
}
}
A user gets the above error when trying to get online predictions. The model was created and the endpoint exists. What is the most likely reason?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Refer to the exhibit.
Error log from Cloud Logging:
{
"textPayload": "Prediction failed: Model 'projects/my-project/locations/us-central1/models/12345' is not deployed to endpoint 'projects/my-project/locations/us-central1/endpoints/67890'. Ensure the model is deployed to the endpoint before making predictions.",
"timestamp": "2024-03-15T10:30:00Z",
"resource": {
"type": "aiplatform.googleapis.com/Endpoint"
}
}
A
The endpoint does not exist.
Why wrong: Endpoint exists as shown in error path.
B
The endpoint is in a different region than the model.
Why wrong: If regions mismatched, error would indicate region conflict; here both are us-central1.
C
No version of the model is deployed to the endpoint.
A model must be deployed (a model version) to the endpoint to serve predictions.
D
The model does not exist.
Why wrong: Error says model not deployed, not that it doesn't exist.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
No version of the model is deployed to the endpoint.
Correct: C. The model must be deployed (a version deployed) to the endpoint. Option A wrong because model exists. Option B wrong because endpoint exists. Option D wrong because region mismatch would give different error.
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.
✗
The endpoint does not exist.
Why it's wrong here
Endpoint exists as shown in error path.
✗
The endpoint is in a different region than the model.
Why it's wrong here
If regions mismatched, error would indicate region conflict; here both are us-central1.
✓
No version of the model is deployed to the endpoint.
Why this is correct
A model must be deployed (a model version) to the endpoint to serve predictions.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The model does not exist.
Why it's wrong here
Error says model not deployed, not that it doesn't exist.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Command / output trap
Endpoint exists as shown in error path.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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.
Identify which PDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Operationalizing machine learning models — This question tests Operationalizing machine learning models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: No version of the model is deployed to the endpoint. — Correct: C. The model must be deployed (a version deployed) to the endpoint. Option A wrong because model exists. Option B wrong because endpoint exists. Option D wrong because region mismatch would give different error.
What should I do if I get this PDE question wrong?
Identify which PDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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