- A
Implement autoscaling based on CPU utilization
Autoscaling adjusts capacity to match demand, preventing overload during peak hours.
- B
Enable Cloud CDN with the origin as the backend bucket
Why wrong: CDN helps for static content, but the application may be dynamic; this alone may not solve latency for all requests.
- C
Use Cloud Memorystore to cache frequently accessed data
Caching reduces database calls and backend processing, lowering response times.
- D
Increase the size of the instances serving the application
Why wrong: Larger instances add cost and may not address root cause; autoscaling and caching are more efficient.
- E
Reduce the number of backend services to simplify routing
Why wrong: Reducing services may limit functionality and does not directly improve latency.
PCDOE Optimizing service performance Practice Question
This PCDOE practice question tests your understanding of optimizing service performance. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 web application experiences high latency during peak hours. Which TWO actions should the team take to optimize performance?
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
Implement autoscaling based on CPU utilization
Option A is correct because implementing autoscaling based on CPU utilization allows the application to dynamically add compute instances during peak hours when CPU load increases, thereby distributing the request load and reducing latency. This aligns with Google Cloud's managed instance groups and autoscaling policies that scale out based on metrics like CPU utilization, ensuring sufficient resources are available to handle traffic spikes without manual intervention.
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.
- ✓
Implement autoscaling based on CPU utilization
Why this is correct
Autoscaling adjusts capacity to match demand, preventing overload during peak hours.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Enable Cloud CDN with the origin as the backend bucket
Why it's wrong here
CDN helps for static content, but the application may be dynamic; this alone may not solve latency for all requests.
- ✓
Use Cloud Memorystore to cache frequently accessed data
Why this is correct
Caching reduces database calls and backend processing, lowering response times.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the size of the instances serving the application
Why it's wrong here
Larger instances add cost and may not address root cause; autoscaling and caching are more efficient.
- ✗
Reduce the number of backend services to simplify routing
Why it's wrong here
Reducing services may limit functionality and does not directly improve latency.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that vertical scaling (increasing instance size) is equivalent to horizontal scaling (autoscaling) for handling peak loads, but the exam expects candidates to recognize that horizontal scaling is more cost-effective, resilient, and aligned with cloud-native best practices for optimizing performance under variable traffic.
Detailed technical explanation
How to think about this question
Autoscaling in Google Cloud Compute Engine uses the 'autoscaler' component that monitors a chosen metric (e.g., CPU utilization at 60-80% target) and adjusts the number of instances in a managed instance group. Under the hood, the autoscaler uses a predictive algorithm that can also incorporate load balancing signals to preemptively scale before CPU spikes occur. A real-world scenario where this matters is an e-commerce site during a flash sale: without autoscaling, a sudden traffic surge overwhelms fixed instances, causing latency spikes; with CPU-based autoscaling, new instances are provisioned within minutes, distributing the load and maintaining response times.
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.
TExam Day Tips
- 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
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Optimizing service performance — study guide chapter
Learn the concepts, then practise the questions
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FAQ
Questions learners often ask
What does this PCDOE question test?
Optimizing service performance — This question tests Optimizing service performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement autoscaling based on CPU utilization — Option A is correct because implementing autoscaling based on CPU utilization allows the application to dynamically add compute instances during peak hours when CPU load increases, thereby distributing the request load and reducing latency. This aligns with Google Cloud's managed instance groups and autoscaling policies that scale out based on metrics like CPU utilization, ensuring sufficient resources are available to handle traffic spikes without manual intervention.
What should I do if I get this PCDOE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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 →
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Last reviewed: Jun 30, 2026
This PCDOE 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 PCDOE exam.
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