easyMultiple Choice
PMLE Practice Question: A data scientist wants to automate the retraining…
A data scientist wants to automate the retraining of a model when new data arrives in Cloud Storage. Which Google Cloud service is most appropriate for orchestrating this workflow?
⚠ Common exam trap
Candidates often confuse event-triggered compute services (like Cloud Functions) with full workflow orchestration, failing to recognize that retraining pipelines require multi-step dependency management, retries, and monitoring that only a dedicated orchestrator like Cloud Composer provides.
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
✓
Cloud Composer
Cloud Composer (D) is the most appropriate service for orchestrating a retraining workflow because it is a fully managed workflow orchestration service built on Apache Airflow. It allows you to define a Directed Acyclic Graph (DAG) that triggers model retraining when new data arrives in Cloud Storage, handling dependencies, scheduling, and monitoring across multiple steps such as data validation, training, and deployment.
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 Run
Why it's wrong here
Cloud Run executes containerised HTTP services and event handlers; it lacks native scheduling, dependency graphs and retry orchestration for multi-step retraining pipelines. It would be correct for serving a trained model behind an endpoint, not for coordinating ingestion, training and deployment steps.
- ✗
Vertex AI Predictions
Why it's wrong here
Vertex AI Predictions serves trained models for online or batch inference; it does not watch Cloud Storage or trigger retraining. It is tempting because it is the Vertex AI component closest to the model, and would be correct if the requirement were to deploy the retrained model for serving rather than orchestrate the workflow.
- ✗
Cloud Scheduler
Why it's wrong here
Cloud Scheduler issues cron-based or HTTP triggers on a fixed timetable; it cannot react to a new object landing in Cloud Storage. It is tempting because it automates recurring jobs, and would be correct if retraining needed to run at set intervals rather than on data arrival.
- ✓
Cloud Composer
Why this is correct
Cloud Composer is a managed Apache Airflow service that orchestrates multi-step workflows, including Cloud Storage event triggers and Vertex AI training jobs. It satisfies the retraining-on-new-data constraint by scheduling and coordinating the pipeline end to end.
- ✗
Cloud Functions
Why it's wrong here
Cloud Functions runs short event-driven snippets, not multi-step retraining pipelines with dependencies and retries. It is tempting because it triggers on Cloud Storage object creation, but that role belongs to Cloud Composer or Vertex AI Pipelines, which orchestrate the full training workflow.
Go deeper
Related to this question
About these practice questions
One of 775 original PMLE practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.