- A
Cloud Pub/Sub
Why wrong: Pub/Sub is a managed messaging service but not Kafka; you would need to adapt your Kafka producers/consumers.
- B
Confluent Cloud on GCP
Why wrong: Confluent Cloud is a third-party managed Kafka offering, not a Google Cloud service.
- C
Cloud Dataflow
Why wrong: Dataflow is a stream processing service, not a message broker.
- D
Dataproc
Dataproc supports running Kafka as an optional component on managed clusters, giving you control and scalability.
Question 344 of 1,000
PDE Ingesting and Processing the Data Practice Question
This PDE practice question tests your understanding of ingesting and processing the data. 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.
Your company uses Kafka for event streaming. You want to run Kafka on Google Cloud with the ability to auto-scale clusters and use managed infrastructure. Which service should you choose?
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
✓
Dataproc
Dataproc is the correct choice because it is a managed Spark and Hadoop service on Google Cloud that supports running Kafka clusters. It allows auto-scaling of worker nodes and integrates with GCP storage and networking, providing the managed infrastructure required for Kafka event streaming.
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 Pub/Sub
Why it's wrong here
Pub/Sub is a managed messaging service but not Kafka; you would need to adapt your Kafka producers/consumers.
- ✗
Confluent Cloud on GCP
Why it's wrong here
Confluent Cloud is a third-party managed Kafka offering, not a Google Cloud service.
- ✗
Cloud Dataflow
Why it's wrong here
Dataflow is a stream processing service, not a message broker.
- ✓
Dataproc
Why this is correct
Dataproc supports running Kafka as an optional component on managed clusters, giving you control and scalability.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse managed Kafka services (like Confluent Cloud) with GCP-native managed infrastructure, or assume Cloud Pub/Sub is equivalent to Kafka for event streaming, when Dataproc is the correct choice for running Kafka itself on GCP with auto-scaling.
Detailed technical explanation
How to think about this question
Dataproc uses the Cloud Dataproc Agent to manage cluster lifecycle, and auto-scaling is based on YARN memory or CPU utilization metrics via the Dataproc autoscaler. Kafka on Dataproc can leverage Persistent Disks for broker storage and Cloud Monitoring for metrics, enabling cost-efficient scaling for variable workloads like real-time event streaming pipelines.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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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Ingesting and Processing the Data — study guide chapter
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FAQ
Questions learners often ask
What does this PDE question test?
Ingesting and Processing the Data — This question tests Ingesting and Processing the Data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Dataproc — Dataproc is the correct choice because it is a managed Spark and Hadoop service on Google Cloud that supports running Kafka clusters. It allows auto-scaling of worker nodes and integrates with GCP storage and networking, providing the managed infrastructure required for Kafka event streaming.
What should I do if I get this PDE 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
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