PDE Ingesting and Processing the Data Practice Question
You have a Dataflow pipeline that processes streaming data with high throughput. You notice that the pipeline is experiencing high latency and the workers are underutilized. Which Dataflow feature can automatically optimize resource allocation?
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
✓
Dataflow Prime
Dataflow Prime (also known as right-fitting) provides vertical autoscaling and resource optimization based on actual usage. Horizontal autoscaling is standard but may not address underutilization. Streaming engine is for scaling the streaming writes but not worker tuning. Flex templates are for deployment, not runtime optimization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Flex Templates
Why it's wrong here
Flex Templates are for packaging pipeline code, not runtime optimization.
- ✗
Horizontal autoscaling
Why it's wrong here
Horizontal autoscaling adds/removes workers but does not adjust individual worker size.
- ✗
Streaming Engine
Why it's wrong here
Streaming Engine offloads state to backend services but does not optimize worker resource allocation.
- ✓
Dataflow Prime
Why this is correct
Dataflow Prime offers vertical autoscaling and right-fitting to optimize worker resources.
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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.