The correct choice is to add a check in the deployment component that verifies whether the endpoint already exists and, if so, calls the update endpoint method instead of create. This directly resolves the pipeline failure by aligning the deployment logic with Vertex AI’s resource management: the Vertex AI Endpoint service treats create and update as distinct operations, and attempting to create an existing endpoint throws a conflict error. On the Google Professional Machine Learning Engineer exam, this scenario tests your understanding of pipeline idempotency and the Kubeflow Pipelines SDK’s interaction with Vertex AI resources—a common trap is assuming retries or external triggers will fix a logic error, when the real fix is a conditional branch in the component itself. Remember the memory tip: “Check before you create, update if it’s late”—meaning always verify resource existence in a recurring pipeline to avoid redundant creation failures.
PMLE Automating and orchestrating ML pipelines Practice Question
This PMLE practice question tests your understanding of automating and orchestrating ml pipelines. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 are responsible for maintaining an ML pipeline that runs daily on Vertex AI Pipelines. The pipeline preprocesses data, trains a model, and deploys it to an endpoint. Recently, the pipeline has been failing at the deployment step because the endpoint already exists and the deploy step tries to create a new endpoint instead of updating the existing one. The pipeline code is written using the Kubeflow Pipelines SDK. You need to modify the pipeline to resolve this issue with minimal changes. What should you do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
In the deployment component, add a check to verify if the endpoint exists, and if so, call the update endpoint method instead of create.
Option A is correct because it addresses the root cause: the deployment component should check if the endpoint exists and update it instead of creating a new one. Option B is wrong because using a Cloud Function bypasses the pipeline orchestration and adds unnecessary complexity. Option C is wrong because retrying will not fix the fundamental issue of trying to create an existing endpoint. Option D is wrong because manual deletion defeats automation and is not a robust solution.
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.
✗
Change the pipeline to use a Cloud Function that triggers the deployment independently, bypassing Vertex AI Pipelines.
Why it's wrong here
This adds external dependency and loses pipeline orchestration benefits.
✓
In the deployment component, add a check to verify if the endpoint exists, and if so, call the update endpoint method instead of create.
Why this is correct
This directly fixes the deployment logic to handle existing endpoints.
Related concept
Read the scenario before looking for a memorised answer.
✗
Set the deploy component's retry policy to infinite so it eventually succeeds.
Why it's wrong here
Retrying will not resolve the create-vs-update issue; the error is deterministic.
✗
Manually delete the existing endpoint before each pipeline run.
Why it's wrong here
Manual intervention is error-prone and not a scalable solution.
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.
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 PMLE 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.
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: In the deployment component, add a check to verify if the endpoint exists, and if so, call the update endpoint method instead of create. — Option A is correct because it addresses the root cause: the deployment component should check if the endpoint exists and update it instead of creating a new one. Option B is wrong because using a Cloud Function bypasses the pipeline orchestration and adds unnecessary complexity. Option C is wrong because retrying will not fix the fundamental issue of trying to create an existing endpoint. Option D is wrong because manual deletion defeats automation and is not a robust solution.
What should I do if I get this PMLE question wrong?
Identify which PMLE 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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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