The answer is Cloud Run, the correct compute component for a serverless data pipeline that processes JSON messages from Pub/Sub and writes results to BigQuery. Cloud Run is ideal because it is a fully managed platform that automatically scales from zero based on incoming HTTP requests, making it perfect for event-driven processing via Pub/Sub push subscriptions, and it integrates natively with BigQuery for high-throughput writes. On the Google Professional Cloud Developer exam, this scenario tests your understanding of choosing the right serverless compute service for event-driven, stateful pipelines—a common trap is selecting Cloud Functions for its simplicity, but Cloud Run offers longer request timeouts, larger instance memory, and concurrent request handling, which are critical for batch processing or heavy transformations. Remember the memory tip: “Run handles the heavy lifting” — when your pipeline needs more than a quick function call, Cloud Run scales without provisioning overhead.
PCD Practice Question: Designing highly scalable, available, and reliable cloud-native applications
This PCD practice question tests your understanding of designing highly scalable, available, and reliable cloud-native applications. 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.
An organization wants to design a serverless data processing pipeline that is highly available and can automatically scale based on the number of incoming requests. The pipeline processes JSON messages from a Cloud Pub/Sub topic and writes results to BigQuery. Which service should be used as the compute component?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cloud Run
Cloud Run is the correct compute component because it is a fully managed serverless platform that automatically scales from zero based on incoming HTTP requests, supports event-driven processing via Pub/Sub push subscriptions, and integrates natively with BigQuery. It provides high availability by default across zones and can handle burst traffic without provisioning overhead, making it ideal for a serverless pipeline that processes JSON messages and writes results to BigQuery.
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 Dataflow
Why it's wrong here
Overkill for simple message processing; better for complex stream processing.
✓
Cloud Run
Why this is correct
Cloud Run provides automatic scaling, can be triggered via Pub/Sub push, and supports longer processing times.
Related concept
Read the scenario before looking for a memorised answer.
✗
Cloud Functions
Why it's wrong here
Cloud Functions can work but Cloud Run offers better concurrency and longer timeouts for this use case.
✗
Compute Engine with managed instance groups
Why it's wrong here
Not serverless; requires manual scaling configuration.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between serverless compute services (Cloud Run vs Cloud Functions) by focusing on execution time limits and concurrency; the trap here is that candidates choose Cloud Functions for its simplicity, overlooking the 9-minute timeout and lack of support for long-running or high-concurrency workloads that Cloud Run handles natively.
Detailed technical explanation
How to think about this question
Cloud Run runs stateless containers on a fully managed Knative-based platform, automatically scaling each container instance based on the number of concurrent requests using the 'concurrency' setting (default 80). When integrated with Pub/Sub via push subscriptions, Cloud Run receives messages as HTTP POST requests, processes them, and can write to BigQuery using the streaming inserts API (tabledata.insertAll) for near-real-time ingestion, with automatic retries and dead-letter queues for reliability.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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.
Designing highly scalable, available, and reliable cloud-native applications — This question tests Designing highly scalable, available, and reliable cloud-native applications — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Cloud Run — Cloud Run is the correct compute component because it is a fully managed serverless platform that automatically scales from zero based on incoming HTTP requests, supports event-driven processing via Pub/Sub push subscriptions, and integrates natively with BigQuery. It provides high availability by default across zones and can handle burst traffic without provisioning overhead, making it ideal for a serverless pipeline that processes JSON messages and writes results to BigQuery.
What should I do if I get this PCD 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.
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Question Discussion
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