- A
Cloud Functions subscribed to the Pub/Sub topic with idempotent logic.
Why wrong: Cloud Functions with Pub/Sub get at-least-once delivery. Idempotency helps but doesn't provide exactly-once guarantees at the infrastructure level.
- B
Dataflow with Pub/Sub as the source using the Beam SDK.
Dataflow's Beam runner provides exactly-once processing semantics over Pub/Sub by checkpointing and deduplicating based on message IDs.
- C
BigQuery Subscriptions connected directly to the Pub/Sub topic.
Why wrong: BigQuery subscriptions write Pub/Sub messages to BigQuery tables with at-least-once semantics; they don't guarantee exactly-once processing.
- D
Cloud Run with a Pub/Sub push subscription and database deduplication table.
Why wrong: Deduplication in Cloud Run requires custom application logic; it's not a built-in infrastructure guarantee and adds application complexity.
Quick Answer
The answer is Dataflow with Pub/Sub as the source using the Beam SDK. This combination provides built-in exactly-once processing semantics because Dataflow leverages the Beam engine’s checkpointing mechanism alongside Pub/Sub’s snapshot-based deduplication, tracking each message’s unique ID to prevent reprocessing even if a worker fails and restarts. On the Google Associate Cloud Engineer exam, this concept tests your understanding of how managed services handle fault-tolerant stream processing, often appearing as a distractor where candidates might incorrectly choose Pub/Sub alone or a simple Cloud Function. A common trap is assuming Pub/Sub’s at-least-once delivery is sufficient, but Dataflow’s checkpointing is what guarantees the “exactly once” contract within the pipeline. Memory tip: think of Dataflow as the “accountant” that checks each message’s receipt (unique ID) against its checkpoint ledger, ensuring no double-counting.
Google ACE Planning and configuring a cloud solution Practice Question
This ACE practice question tests your understanding of planning and configuring a cloud solution. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
You are designing an application that needs to process exactly once each message published to a topic, even if the consumer fails partway through and restarts. Which GCP service provides built-in exactly-once processing semantics with Pub/Sub?
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
Dataflow with Pub/Sub as the source using the Beam SDK.
Dataflow with Pub/Sub as the source using the Beam SDK provides built-in exactly-once processing semantics because it leverages the Beam engine's checkpointing and the Pub/Sub source's snapshot-based deduplication. Dataflow tracks each message's unique ID and ensures that even if a worker fails and restarts, the message is not reprocessed, guaranteeing exactly-once delivery within the pipeline.
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 Functions subscribed to the Pub/Sub topic with idempotent logic.
Why it's wrong here
Cloud Functions with Pub/Sub get at-least-once delivery. Idempotency helps but doesn't provide exactly-once guarantees at the infrastructure level.
- ✓
Dataflow with Pub/Sub as the source using the Beam SDK.
Why this is correct
Dataflow's Beam runner provides exactly-once processing semantics over Pub/Sub by checkpointing and deduplicating based on message IDs.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
BigQuery Subscriptions connected directly to the Pub/Sub topic.
Why it's wrong here
BigQuery subscriptions write Pub/Sub messages to BigQuery tables with at-least-once semantics; they don't guarantee exactly-once processing.
- ✗
Cloud Run with a Pub/Sub push subscription and database deduplication table.
Why it's wrong here
Deduplication in Cloud Run requires custom application logic; it's not a built-in infrastructure guarantee and adds application complexity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that Pub/Sub itself provides exactly-once delivery, but Pub/Sub only guarantees at-least-once; the exactly-once semantics must be implemented by the consumer, and Dataflow is the only GCP service that offers this built-in for Pub/Sub sources.
Detailed technical explanation
How to think about this question
Under the hood, Dataflow uses a combination of checkpointing and the Pub/Sub source's snapshot API to track which messages have been committed. When a worker fails, the pipeline restarts from the last consistent checkpoint, and the Pub/Sub source re-reads messages from a snapshot, filtering out those already processed via unique message IDs. This is critical in streaming pipelines where late-arriving data or worker preemptions could otherwise cause duplicates, such as in financial transaction processing or real-time analytics.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this ACE question test?
Planning and configuring a cloud solution — This question tests Planning and configuring a cloud solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Dataflow with Pub/Sub as the source using the Beam SDK. — Dataflow with Pub/Sub as the source using the Beam SDK provides built-in exactly-once processing semantics because it leverages the Beam engine's checkpointing and the Pub/Sub source's snapshot-based deduplication. Dataflow tracks each message's unique ID and ensures that even if a worker fails and restarts, the message is not reprocessed, guaranteeing exactly-once delivery within the pipeline.
What should I do if I get this ACE 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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Last reviewed: Jun 30, 2026
This ACE 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 ACE exam.
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