easyMultiple Choice
PDE Practice Question: Process streaming data from IoT devices with…
A company needs to process streaming data from IoT devices with sub-second latency and exactly-once processing guarantees. Which Google Cloud service should they use?
⚠ Common exam trap
Google Cloud often tests the distinction between data ingestion (Pub/Sub) and data processing (Dataflow), so the trap here is that candidates confuse Pub/Sub's streaming ingestion capability with the processing guarantees needed for exactly-once semantics.
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
✓
Cloud Dataflow
Cloud Dataflow is the correct choice because it provides a unified stream and batch processing model with exactly-once processing guarantees and sub-second latency via its Apache Beam SDK. It supports event-time processing, watermarks, and triggers to handle out-of-order data from IoT devices while ensuring each record is processed exactly once, even in the case of failures.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
BigQuery
Why it's wrong here
BigQuery is an analytics warehouse for batch and bounded queries, not a sub-second streaming engine with exactly-once semantics. It cannot meet the latency requirement for IoT telemetry. BigQuery would be the right choice for storing and analysing the streamed data after ingestion by a service such as Pub/Sub.
- ✗
Cloud Dataproc
Why it's wrong here
Dataproc runs batch and streaming Spark/Hadoop jobs on ephemeral clusters, adding cluster provisioning and micro-batch scheduling that cannot meet sub-second latency. It is tempting because it handles large-scale data processing, and would be correct for migrating existing Spark workloads or batch analytics rather than low-latency IoT streams.
- ✓
Cloud Dataflow
Why this is correct
Cloud Dataflow provides exactly-once processing through its Apache Beam runner, which tracks watermarks and uses checkpointing to deduplicate records during streaming execution. It satisfies the sub-second latency requirement via streaming mode rather than micro-batch windows, unlike Pub/Sub alone or Dataproc, which cannot guarantee exactly-once semantics natively.
- ✗
Cloud Pub/Sub
Why it's wrong here
Cloud Pub/Sub delivers at-least-once by default, so consumers must deduplicate to achieve exactly-once semantics; it does not natively guarantee exactly-once end-to-end processing. It is tempting because it handles high-throughput ingestion, but sub-second exactly-once stream processing belongs to Dataflow with Pub/Sub as source.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE 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 PDE exam.