The answer is to run a Vertex AI Pipeline for model evaluation and register the model only if metrics exceed thresholds. This is correct because it directly implements a model evaluation gate in the CI/CD pipeline, using Vertex AI’s managed orchestration to automatically validate performance on a validation set against predefined thresholds before promotion. In the Google Professional Machine Learning Engineer exam, this tests your understanding of MLOps gated promotions and the integration of Cloud Build, Cloud Deploy, and Vertex AI Pipelines. A common trap is selecting a simpler option like running a local script or using Cloud Build’s built-in test step, which lacks the reproducibility, artifact tracking, and threshold-based gating that Vertex AI Pipelines provides. Remember the memory tip: “Gate with a Pipeline, not a script”—if the answer involves manual checks or non-orchestrated steps, it’s likely wrong.
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.
An ML engineer is designing a CI/CD pipeline for ML models using Cloud Build and Cloud Deploy. They want to automatically test model performance on a validation set before promoting to production. Which step should be included in the CI/CD pipeline?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Run a Vertex AI Pipeline for model evaluation and register the model only if metrics exceed thresholds
Option E is correct because it directly integrates model evaluation into the CI/CD pipeline using Vertex AI Pipelines, which allows automated validation of model performance against predefined thresholds before promotion. This ensures that only models meeting quality criteria are deployed, aligning with MLOps best practices for gated promotions.
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.
✗
Run unit tests on the training code
Why it's wrong here
Unit tests verify code, not model performance.
✗
Use Cloud Composer to schedule evaluation
Why it's wrong here
Not part of CI/CD pipeline.
✗
Deploy to production immediately after training
Why it's wrong here
No validation, risky.
✗
Train the model in the CI/CD pipeline
Why it's wrong here
Training should be done separately, not in CI/CD.
✓
Run a Vertex AI Pipeline for model evaluation and register the model only if metrics exceed thresholds
Why this is correct
Implements a quality gate.
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 code testing (unit tests) and model validation (performance metrics), leading candidates to choose A because they conflate software testing with ML evaluation.
Detailed technical explanation
How to think about this question
Vertex AI Pipelines uses Kubeflow Pipelines SDK to define a directed acyclic graph (DAG) of steps, including model evaluation with metrics like AUC, precision, and recall. The pipeline can conditionally register the model in Vertex AI Model Registry only when metrics exceed thresholds, using a conditional node that checks evaluation output. In practice, this enables automated rollback or alerting if a model regresses, such as when a new training run produces a 2% drop in F1 score on the validation set.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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: Run a Vertex AI Pipeline for model evaluation and register the model only if metrics exceed thresholds — Option E is correct because it directly integrates model evaluation into the CI/CD pipeline using Vertex AI Pipelines, which allows automated validation of model performance against predefined thresholds before promotion. This ensures that only models meeting quality criteria are deployed, aligning with MLOps best practices for gated promotions.
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.
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Question Discussion
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