mediumMultiple Choice
PDE Practice Question: A data pipeline uses Cloud Pub/Sub to ingest…
A data pipeline uses Cloud Pub/Sub to ingest events and Cloud Functions to transform and write to BigQuery. The system is experiencing data loss during Pub/Sub subscription outages. Which design change improves reliability?
⚠ Common exam trap
Google Cloud often tests the misconception that increasing timeouts or ack deadlines alone can prevent data loss, when in reality they only delay the inevitable loss without a replay mechanism like checkpointing or a persistent buffer.
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
✓
Use Dataflow with at-least-once delivery and checkpointing
Dataflow with at-least-once delivery and checkpointing ensures that messages are not lost during Pub/Sub subscription outages because Dataflow tracks processing progress via checkpoints and can replay unacknowledged messages from the last checkpoint. This decouples the processing from the subscription's transient failures, providing fault-tolerant, exactly-once or at-least-once semantics depending on the sink.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Dataflow with at-least-once delivery and checkpointing
Why this is correct
Dataflow provides exactly-once semantics with checkpointing to prevent data loss.
- ✗
Use a pull subscription with a custom app that polls frequently
Why it's wrong here
Custom polling adds complexity and still can lose messages if the puller fails.
- ✗
Use long ack deadlines to keep messages in the subscription
Why it's wrong here
Ack deadlines only affect redelivery; during outage, messages can still be lost if not acknowledged.
- ✗
Increase the timeout in Cloud Functions
Why it's wrong here
Timeout extension does not handle subscription outages.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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