- A
Cloud Scheduler to trigger the pipeline on a schedule.
Why wrong: Not needed for CI/CD triggered by code push.
- B
Cloud Functions to deploy the model.
Why wrong: Deployment can be done directly from the pipeline using components.
- C
Vertex AI Pipelines to orchestrate training and evaluation.
Pipelines are used to run the ML workflow.
- D
Cloud Build trigger configured to respond to push events to the main branch.
Essential for triggering the pipeline on code push.
- E
Vertex AI Continuous Training service.
Why wrong: Not a distinct service; Vertex AI Training is part of pipelines.
Question 805 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 are building a CI/CD pipeline for an ML model using Cloud Build. When code is pushed to the main branch, you want to automatically build a training image, run a Vertex AI pipeline, and if the model evaluation passes, deploy it to a staging endpoint. Which two components are essential for this CI/CD pipeline?
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
✓
Vertex AI Pipelines to orchestrate training and evaluation.
Option C is correct because Vertex AI Pipelines is the service that orchestrates the entire ML workflow, including training, evaluation, and conditional deployment logic. In a CI/CD pipeline, you need a managed orchestrator to chain steps like model training, evaluation, and deployment, and Vertex AI Pipelines provides that with its Kubeflow Pipelines-based DAG execution.
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.
- ✗
Cloud Scheduler to trigger the pipeline on a schedule.
Why it's wrong here
Not needed for CI/CD triggered by code push.
- ✗
Cloud Functions to deploy the model.
Why it's wrong here
Deployment can be done directly from the pipeline using components.
- ✓
Vertex AI Pipelines to orchestrate training and evaluation.
Why this is correct
Pipelines are used to run the ML workflow.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Cloud Build trigger configured to respond to push events to the main branch.
Why this is correct
Essential for triggering the pipeline on code push.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Vertex AI Continuous Training service.
Why it's wrong here
Not a distinct service; Vertex AI Training is part of pipelines.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between event-driven triggers (Cloud Build trigger on push) and schedule-based triggers (Cloud Scheduler), so candidates mistakenly pick Cloud Scheduler when the requirement is for a code-push event.
Detailed technical explanation
How to think about this question
Cloud Build triggers can be configured to respond to Git push events (e.g., to the main branch) by using a Pub/Sub topic or webhook that Cloud Build listens to. Vertex AI Pipelines uses the Kubeflow Pipelines SDK to define a directed acyclic graph (DAG) of steps, and it supports conditional execution (e.g., only deploy if evaluation metrics pass a threshold) via the `if`/`else` constructs in the pipeline definition. A real-world scenario is a multi-step pipeline that trains a model, runs evaluation with a custom container, and then conditionally deploys to a staging endpoint using the `google_cloud_pipeline_components` library.
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.
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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: Vertex AI Pipelines to orchestrate training and evaluation. — Option C is correct because Vertex AI Pipelines is the service that orchestrates the entire ML workflow, including training, evaluation, and conditional deployment logic. In a CI/CD pipeline, you need a managed orchestrator to chain steps like model training, evaluation, and deployment, and Vertex AI Pipelines provides that with its Kubeflow Pipelines-based DAG execution.
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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Last reviewed: Jul 4, 2026
This PMLE 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 PMLE exam.
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