GCP-ADP Data Preparation And Ingestion Practice Question
You are using Dataflow with autoscaling. What metric determines whether the worker pool scales up or down?
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
✓
Work backlog and throughput
Dataflow autoscaling is based on the backlog of work and CPU usage of current workers.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Work backlog and throughput
Why this is correct
Autoscaling reacts to the volume of pending work.
- ✗
Network latency
Why it's wrong here
Network latency is not a primary scaling factor.
- ✗
Memory usage
Why it's wrong here
Scaling is primarily driven by work backlog, not memory.
- ✗
User-defined triggers
Why it's wrong here
Autoscaling is automatic based on internal metrics.
About these practice questions
One of 205 original GCP-ADP practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Google Cloud exam blueprint
This GCP-ADP 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 GCP-ADP exam.