- 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 Dataproc 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. A key principle to apply: dataproc. 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 via initialization actions. It allows auto-scaling of worker nodes and integrates with GCP storage and networking, providing the managed infrastructure required for Kafka event streaming. Note that Confluent Cloud is a third-party managed Kafka service, not a GCP-native service, and Cloud Pub/Sub is a messaging service, not a Kafka replacement. Cloud Dataflow is for data processing pipelines, not for running Kafka itself.
Key principle: Dataproc
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
Dataproc
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap is that candidates may confuse third-party 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 GCP-native service for running Kafka itself with auto-scaling and managed resources.
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
- Dataproc
- Kafka on Google Cloud
- Cloud Pub/Sub
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
Dataproc
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.
Review dataproc, then practise related PDE questions on the same topic to reinforce the concept.
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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 — Dataproc.
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 via initialization actions. It allows auto-scaling of worker nodes and integrates with GCP storage and networking, providing the managed infrastructure required for Kafka event streaming. Note that Confluent Cloud is a third-party managed Kafka service, not a GCP-native service, and Cloud Pub/Sub is a messaging service, not a Kafka replacement. Cloud Dataflow is for data processing pipelines, not for running Kafka itself.
What should I do if I get this PDE question wrong?
Review dataproc, then practise related PDE questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Dataproc
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Last reviewed: Jul 4, 2026
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