Google PCA Practice Question: Managing and Provisioning a Solution Infrastructure
A data engineering team wants to ingest streaming data from Pub/Sub, transform it using Apache Beam, and load it into BigQuery for real-time analytics. They need a fully managed solution that handles autoscaling and does not require managing servers. Which TWO Google Cloud services should they use?
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 Dataflow
Dataflow is the fully managed service for executing Apache Beam pipelines, with autoscaling and serverless execution. Pub/Sub is the ingestion service. Cloud Composer is Airflow, not streaming; Dataproc is for Spark/Hadoop; Dataprep is for data preparation.
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 for running Hadoop/Spark clusters, not fully managed streaming.
- ✓
Cloud Dataflow
Why this is correct
Dataflow runs Beam pipelines with autoscaling and serverless processing.
- ✗
Cloud Dataprep
Why it's wrong here
Dataprep is for data preparation, not real-time streaming pipelines.
- ✗
Cloud Composer
Why it's wrong here
Composer is for workflow orchestration, not real-time stream processing.
- ✓
Cloud Pub/Sub
Why this is correct
Pub/Sub ingests streaming data and feeds into Dataflow.
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
Learn chapter
Introduction to Google Cloud Platform
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Dataflow
Dataflow is a Google Cloud managed service that processes and transforms data in real-time or batch mode using Apache Beam pipelines.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCA 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 PCA exam.