- A
Use autoscaling with a minimum of 1000 processing units, a maximum of 2000 processing units, and a target CPU utilization of 65%
Why wrong: Spanner uses high-priority CPU utilization, not total CPU utilization, for autoscaling decisions.
- B
Use autoscaling with a minimum of 1000 processing units, a maximum of 2000 processing units, and a target high-priority CPU utilization of 65%
This configuration allows the instance to scale up from 1000 to 2000 processing units when high-priority CPU exceeds the target.
- C
Use autoscaling with a minimum of 1 node, a maximum of 2 nodes, and a target CPU utilization of 65%
Why wrong: Processing units are used, not nodes. Node-based scaling is legacy and not integrated with processing units.
- D
Manually increase processing units to 2000
Why wrong: Manual scaling requires constant monitoring and adjustment; autoscaling is more efficient.
PCD Practice Question: Deploy Scalable and Highly Available Databases in Google Cloud
This PCD practice question tests your understanding of deploy scalable and highly available databases in google cloud. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses Cloud Spanner with an instance configured with 1000 processing units. They notice that high-priority CPU utilization consistently exceeds 65% during peak hours, causing increased latency. They want to auto-scale based on this metric. Which scaling configuration should they use?
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 autoscaling with a minimum of 1000 processing units, a maximum of 2000 processing units, and a target high-priority CPU utilization of 65%
Cloud Spanner autoscaling uses processing units (not nodes) and allows setting a target for high-priority CPU utilization. Setting a minimum of 1000 processing units ensures a baseline, and a maximum of 2000 allows scaling up. The target high-priority CPU utilization (e.g., 65%) triggers scaling. Node-based options are not used with processing units.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 autoscaling with a minimum of 1000 processing units, a maximum of 2000 processing units, and a target CPU utilization of 65%
Why it's wrong here
Spanner uses high-priority CPU utilization, not total CPU utilization, for autoscaling decisions.
- ✓
Use autoscaling with a minimum of 1000 processing units, a maximum of 2000 processing units, and a target high-priority CPU utilization of 65%
Why this is correct
This configuration allows the instance to scale up from 1000 to 2000 processing units when high-priority CPU exceeds the target.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use autoscaling with a minimum of 1 node, a maximum of 2 nodes, and a target CPU utilization of 65%
Why it's wrong here
Processing units are used, not nodes. Node-based scaling is legacy and not integrated with processing units.
- ✗
Manually increase processing units to 2000
Why it's wrong here
Manual scaling requires constant monitoring and adjustment; autoscaling is more efficient.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
Identify which PCD exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Deploy Scalable and Highly Available Databases in Google Cloud — study guide chapter
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FAQ
Questions learners often ask
What does this PCD question test?
Deploy Scalable and Highly Available Databases in Google Cloud — This question tests Deploy Scalable and Highly Available Databases in Google Cloud — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use autoscaling with a minimum of 1000 processing units, a maximum of 2000 processing units, and a target high-priority CPU utilization of 65% — Cloud Spanner autoscaling uses processing units (not nodes) and allows setting a target for high-priority CPU utilization. Setting a minimum of 1000 processing units ensures a baseline, and a maximum of 2000 allows scaling up. The target high-priority CPU utilization (e.g., 65%) triggers scaling. Node-based options are not used with processing units.
What should I do if I get this PCD question wrong?
Identify which PCD exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
This PCD 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 PCD exam.
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