Google PCA Design and plan a cloud solution architecture Practice Question
This PCA practice question tests your understanding of design and plan a cloud solution architecture. 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.
A company is building a real-time data pipeline that ingests events from IoT devices, processes them with Apache Beam, and stores results in BigQuery for analytics. The pipeline must handle spikes in traffic and guarantee exactly-once processing. Which combination of services should they use?
Why wrong: Dataproc is primarily for batch processing with Spark/Hadoop, not for streaming Beam pipelines.
B
Cloud IoT Core, Data Fusion, and Cloud Bigtable.
Why wrong: Cloud IoT Core is deprecated; Data Fusion is for batch data integration, not streaming.
C
Cloud Storage, Cloud Functions, and BigQuery.
Why wrong: Cloud Functions are not designed for high-throughput streaming with exactly-once guarantees.
D
Cloud Pub/Sub, Dataflow, and BigQuery.
Cloud Pub/Sub handles event ingestion with scalability, Dataflow provides exactly-once processing for streaming, and BigQuery serves as the analytics data warehouse.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cloud Pub/Sub, Dataflow, and BigQuery.
Option D is correct because Cloud Pub/Sub provides scalable, asynchronous ingestion for IoT event spikes, Dataflow (which runs Apache Beam) offers exactly-once processing semantics via checkpointing and idempotent sinks, and BigQuery serves as the analytics destination. This combination meets all requirements: Pub/Sub decouples producers from consumers, Dataflow handles stateful processing with exactly-once guarantees, and BigQuery supports real-time streaming inserts.
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, Dataproc, and BigQuery.
Why it's wrong here
Dataproc is primarily for batch processing with Spark/Hadoop, not for streaming Beam pipelines.
✗
Cloud IoT Core, Data Fusion, and Cloud Bigtable.
Why it's wrong here
Cloud IoT Core is deprecated; Data Fusion is for batch data integration, not streaming.
✗
Cloud Storage, Cloud Functions, and BigQuery.
Why it's wrong here
Cloud Functions are not designed for high-throughput streaming with exactly-once guarantees.
✓
Cloud Pub/Sub, Dataflow, and BigQuery.
Why this is correct
Cloud Pub/Sub handles event ingestion with scalability, Dataflow provides exactly-once processing for streaming, and BigQuery serves as the analytics data warehouse.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that any combination of Google Cloud services can achieve exactly-once processing, but the trap here is that only Dataflow (with its Beam runner) provides native exactly-once semantics for streaming pipelines, while Dataproc, Data Fusion, and Cloud Functions lack this guarantee.
Detailed technical explanation
How to think about this question
Dataflow's exactly-once processing relies on a combination of checkpointing (via consistent snapshots using the MillWheel engine) and idempotent writes to BigQuery's streaming buffer, which deduplicates records using insertId. Under the hood, Pub/Sub uses a pull-based model with acknowledgments and dead-letter queues to handle backpressure, while Dataflow's autoscaling adjusts worker count based on lag metrics from Pub/Sub's subscription. In a real-world scenario, a sudden spike from thousands of IoT sensors can be absorbed by Pub/Sub's unbounded buffer, and Dataflow's exactly-once guarantees prevent duplicate analytics even if workers fail and restart.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Design and plan a cloud solution architecture — This question tests Design and plan a cloud solution architecture — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Cloud Pub/Sub, Dataflow, and BigQuery. — Option D is correct because Cloud Pub/Sub provides scalable, asynchronous ingestion for IoT event spikes, Dataflow (which runs Apache Beam) offers exactly-once processing semantics via checkpointing and idempotent sinks, and BigQuery serves as the analytics destination. This combination meets all requirements: Pub/Sub decouples producers from consumers, Dataflow handles stateful processing with exactly-once guarantees, and BigQuery supports real-time streaming inserts.
What should I do if I get this PCA 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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