Cloud Digital Leader Google Cloud Products and Services Practice Question
A data engineer needs to process a continuous stream of events from a global user base, perform real-time transformations, and write the results to both Cloud Storage and BigQuery. The solution must handle sudden traffic spikes and be fully managed (no server management). Which combination of services should the engineer use?
⚠ Common exam trap
The trap is picking Cloud Functions as the transformation engine because it is serverless and easy, but the exam expects you to know Dataflow is the managed service for continuous stream processing with multiple sinks.
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
✓
Pub/Sub, Dataflow, Cloud Storage, BigQuery
Pub/Sub ingests the continuous global event stream, Dataflow performs the real-time transformations in a fully managed, autoscaling way, and the pipeline can write results to both Cloud Storage and BigQuery as sinks. This combination meets every requirement: global ingestion, real-time processing, dual output, spike handling via autoscaling, and no server management. Dataflow is the only option that natively supports streaming transformations with exactly-once semantics and writes to multiple sinks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Pub/Sub, Cloud Functions, Cloud Storage
Why it's wrong here
Cloud Functions is an event-driven compute service with invocation timeouts and concurrency limits, making it unsuitable for sustained high-throughput stream processing; it also lacks the windowing, state management, and auto-scaling that Dataflow provides. Without BigQuery, the pipeline cannot serve low-latency analytical queries, so it delivers neither scalability nor downstream analytics.
- ✗
Pub/Sub, Dataflow, Cloud Functions
Why it's wrong here
Although Dataflow correctly handles stream processing from Pub/Sub, adding Cloud Functions as a downstream component is architecturally wrong: Cloud Functions is not a sink, and it reintroduces per-message invocation overhead and scaling bottlenecks. Dataflow should write processed results directly to Cloud Storage and BigQuery, which act as the data lake and analytics warehouse, making the Cloud Functions hop redundant and harmful.
- ✗
Cloud Scheduler, Cloud Functions, BigQuery
Why it's wrong here
Cloud Scheduler triggers jobs on a fixed cron schedule, producing discrete batches rather than consuming an unbounded stream, so it cannot provide real-time processing of continuously arriving even numbers. Cloud Functions invoked by the scheduler is equally unsuitable for high-throughput stream processing, as it lacks the streaming engine capabilities of Dataflow, and BigQuery alone cannot ingest and process raw events without a streaming pipeline.
- ✓
Pub/Sub, Dataflow, Cloud Storage, BigQuery
Why this is correct
This pipeline uses Pub/Sub for asynchronous ingestion, then Dataflow (the fully managed Apache Beam runner) to read the unbounded stream, apply transforms, and write to two complementary sinks: Cloud Storage for durable raw data or archives, and BigQuery for interactive analytics. Dataflow handles the challenges of streaming—windowing, triggering, exactly-once processing, and auto-scaling—so all services are purpose-built for their roles and form a complete, production-ready architecture.
Go deeper
Related to this question
Learn chapter
DevOps: Continuous Integration and Delivery
Key term
Dataflow
Dataflow is a Google Cloud managed service that processes and transforms data in real-time or batch mode using Apache Beam pipelines.
Key term
BigQuery
BigQuery is a fully managed, serverless data warehouse on Google Cloud that lets you run fast SQL queries on massive datasets without managing any infrastructure.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This GCDL 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 GCDL exam.