- A
Add more instances to the instance groups to increase total memory capacity.
Why wrong: Adding instances distributes memory but each instance still duplicates cache entries, wasting memory and not improving hit ratio.
- B
Migrate to a managed in-memory cache like Memorystore for Redis to serve as a centralized cache shared by all instances.
A centralized cache eliminates duplication, reduces per-instance memory pressure, and improves cache hit ratio, reducing latency.
- C
Increase the machine type of instances to have more memory per instance (e.g., n1-highmem-4).
Why wrong: More memory per instance still leads to duplication and does not address the low cache hit ratio.
- D
Enable autoscaling based on memory utilization.
Why wrong: Autoscaling on memory may add instances under memory pressure, but the fundamental cache design issue remains.
PCDOE Optimizing service performance Practice Question
This PCDOE practice question tests your understanding of optimizing service performance. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 runs a production web application on Google Compute Engine behind an HTTP(S) load balancer. The application is deployed across multiple managed instance groups in three regions (us-east1, europe-west1, asia-east1). Recently, users report slow page load times. Monitoring shows that CPU utilization on instances is consistently low (around 30%) but memory usage is high (over 80%). The application uses a self-managed in-memory cache per instance to store session data and frequently accessed objects. The team is considering adding more instances to the instance groups to distribute the load. However, they notice that the load balancer's latency is spiking and the cache hit ratio is low. What is the most likely issue and what should the engineer do?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
Migrate to a managed in-memory cache like Memorystore for Redis to serve as a centralized cache shared by all instances.
The low cache hit ratio and high memory usage indicate that each instance's self-managed in-memory cache is fragmented and inefficient, as session data and frequently accessed objects are not shared across instances. This forces the load balancer to repeatedly fetch data from the backend, causing latency spikes. Migrating to a centralized managed cache like Memorystore for Redis eliminates per-instance cache duplication, improves cache hit ratio, and reduces load balancer latency by serving data from a single, consistent cache.
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.
- ✗
Add more instances to the instance groups to increase total memory capacity.
Why it's wrong here
Adding instances distributes memory but each instance still duplicates cache entries, wasting memory and not improving hit ratio.
- ✓
Migrate to a managed in-memory cache like Memorystore for Redis to serve as a centralized cache shared by all instances.
Why this is correct
A centralized cache eliminates duplication, reduces per-instance memory pressure, and improves cache hit ratio, reducing latency.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the machine type of instances to have more memory per instance (e.g., n1-highmem-4).
Why it's wrong here
More memory per instance still leads to duplication and does not address the low cache hit ratio.
- ✗
Enable autoscaling based on memory utilization.
Why it's wrong here
Autoscaling on memory may add instances under memory pressure, but the fundamental cache design issue remains.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that scaling horizontally (adding more instances) or vertically (increasing instance size) can solve performance issues caused by architectural inefficiencies like cache fragmentation, rather than addressing the root cause with a shared caching layer.
Detailed technical explanation
How to think about this question
In a multi-region deployment with a self-managed per-instance cache, each instance stores its own copy of session data and objects, leading to cache misses when a user's request is routed to a different instance (e.g., due to load balancing or instance scaling). Memorystore for Redis provides a centralized, highly available cache that all instances can access, ensuring consistent cache hits regardless of which instance serves the request. This reduces backend load and latency, as the load balancer no longer needs to wait for cache-miss-driven database queries or object recomputation.
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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Optimizing service performance practice 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: Migrate to a managed in-memory cache like Memorystore for Redis to serve as a centralized cache shared by all instances. — The low cache hit ratio and high memory usage indicate that each instance's self-managed in-memory cache is fragmented and inefficient, as session data and frequently accessed objects are not shared across instances. This forces the load balancer to repeatedly fetch data from the backend, causing latency spikes. Migrating to a centralized managed cache like Memorystore for Redis eliminates per-instance cache duplication, improves cache hit ratio, and reduces load balancer latency by serving data from a single, consistent cache.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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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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