mediumMultiple Select
PDE Practice Question: Planning to migrate a legacy batch ETL pipeline…
A company is planning to migrate a legacy batch ETL pipeline to Google Cloud. The pipeline involves reading from a relational database, transforming data, and writing to a data warehouse. Which three Google Cloud services can be used as the orchestration layer? (Choose three.)
⚠ Common exam trap
Google Cloud often tests the distinction between data processing services (Dataproc, Dataflow) and orchestration services (Workflows, Composer, Scheduler), so candidates mistakenly select Dataproc or Dataflow thinking they can orchestrate, when they are actually execution engines.
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 Scheduler
Cloud Scheduler is a fully managed cron job service that can trigger orchestration workflows on a schedule. It is correct because it can initiate batch ETL pipelines by sending HTTP requests to Cloud Run, Cloud Functions, or Pub/Sub, making it a lightweight orchestration trigger for scheduled batch jobs.
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 Dataproc
Why it's wrong here
Dataproc is a managed Spark/Hadoop service, not an orchestrator.
- ✓
Cloud Scheduler
Why this is correct
Cloud Scheduler can trigger jobs on a schedule, acting as a simple orchestrator.
- ✗
Cloud Dataflow
Why it's wrong here
Dataflow is a data processing engine, not an orchestration service.
- ✓
Cloud Workflows
Why this is correct
Cloud Workflows is a serverless orchestration service that can coordinate multi-step pipelines.
- ✓
Cloud Composer
Why this is correct
Cloud Composer is a managed Apache Airflow environment for orchestrating workflows.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
About these practice questions
This PDE question is part of Courseiva's 747-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE 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 PDE exam.