The correct combination is Cloud Pub/Sub, Cloud Dataflow, and Cloud Bigtable because this trio directly addresses the core requirements of real-time analytics IoT workloads on Google Cloud: high-throughput ingestion, sub-second stream processing, and low-latency time-series storage. Cloud Pub/Sub reliably ingests the massive data stream from thousands of devices, Cloud Dataflow performs stateful stream processing with exactly-once semantics to meet sub-second latency, and Cloud Bigtable provides sub-10ms read/write latency for time-series data at petabyte scale, making it the ideal operational database for this pattern. On the Google Professional Cloud Developer exam, this scenario tests your understanding of how to architect for high-throughput, low-latency pipelines while avoiding common traps like choosing Cloud SQL (which lacks horizontal scaling for IoT) or Cloud Storage (which is not designed for sub-second queries). A strong memory tip is to think of the “Pub/Flow/Table” triad: Pub for ingestion, Flow for processing, Table for storage—each service is purpose-built for its role in the real-time analytics pipeline.
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.
A company is building a real-time analytics application on Google Cloud that ingests data from thousands of IoT devices. The data must be processed with sub-second latency and stored in a time-series database for querying. Which combination of services provides the best scalability and availability?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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, Cloud Dataflow, Cloud Bigtable
Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, offering sub-10ms latency for time-series data. Combined with Cloud Pub/Sub for ingesting high-throughput IoT data and Cloud Dataflow for stream processing, this combination provides the best scalability and availability for real-time analytics with sub-second latency requirements.
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, Cloud Dataflow, Cloud Datastore
Why it's wrong here
Datastore is not optimized for time-series with high write throughput.
✗
Cloud Pub/Sub, Cloud Functions, Cloud SQL
Why it's wrong here
Cloud SQL is relational and not ideal for time-series scalability.
✗
Cloud Pub/Sub, Cloud Dataflow, Cloud Storage
Why it's wrong here
Cloud Storage is for object storage, not real-time queries.
✓
Cloud Pub/Sub, Cloud Dataflow, Cloud Bigtable
Why this is correct
Bigtable is ideal for high-throughput time-series data with low-latency access.
Clue confirmation
The clue word "best" in the question point toward this answer.
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 often confuse Cloud Bigtable with Cloud Datastore or Cloud SQL, not realizing that Bigtable is the only Google Cloud database purpose-built for high-throughput, low-latency time-series and analytical workloads at scale.
Detailed technical explanation
How to think about this question
Cloud Bigtable uses a distributed, sorted key-value store based on Google's Bigtable paper, with automatic sharding and replication across zones for high availability. Its native integration with Cloud Dataflow allows exactly-once processing semantics via checkpointing and dynamic rebalancing, while Cloud Pub/Sub provides at-least-once delivery with configurable retention and pull/push subscriptions. In real-world IoT scenarios, Bigtable's column families and time-based row keys enable efficient range scans for time-series queries, achieving consistent single-digit millisecond latencies even under millions of writes per second.
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.
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 Pub/Sub, Cloud Dataflow, Cloud Bigtable — Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, offering sub-10ms latency for time-series data. Combined with Cloud Pub/Sub for ingesting high-throughput IoT data and Cloud Dataflow for stream processing, this combination provides the best scalability and availability for real-time analytics with sub-second latency requirements.
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.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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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