The correct answer is to switch to a Memorystore Standard tier instance with a higher capacity and enable scaling. This works because scaling up a Standard tier instance increases not only memory but also the underlying CPU and network bandwidth, directly addressing the throughput bottleneck during a flash sale without requiring any application code changes or architectural redesign. On the Google Professional Cloud Developer exam, this scenario tests your understanding of Memorystore scaling limits versus clustering—a common trap is assuming clustering is needed for throughput, but clustering requires application-level sharding logic and is meant for data partitioning, not simple vertical scaling. The key distinction is that Standard tier supports online vertical scaling, while Basic tier does not, and clustering adds complexity you don’t need here. Memory tip: “Scale up before you shard out”—vertical scaling on Standard tier is the simplest path to higher throughput when your architecture is already monolithic.
PCD Building and testing applications Practice Question
This PCD practice question tests your understanding of building and testing applications. 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.
You are a developer for an e-commerce platform running on Google Kubernetes Engine (GKE) with a Cloud SQL backend. The application uses Cloud Memorystore for Redis for session caching. During a flash sale, you notice that the application latency spikes and some users are unable to complete checkout. You suspect the Redis instance is overwhelmed. The Redis instance is currently a Standard tier instance with 5 GB of memory. You need to increase throughput without significant architectural changes. You have the following options: A) Migrate to a Memorystore Basic tier instance with a larger memory size. B) Enable for Redis clustering on the existing instance to distribute load across shards. C) Switch to a Memorystore Standard tier instance with a higher capacity and enable scaling. D) Use client-side caching to reduce load on the Redis instance. Which option should you choose?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Switch to a Memorystore Standard tier instance with a higher capacity and enable scaling.
Option B is correct because enabling scaling on a Memorystore Standard tier instance allows you to increase the instance's capacity and throughput without architectural changes. Scaling up the memory size increases the available CPU and network bandwidth, directly addressing the latency spike during the flash sale. This approach maintains the existing Redis configuration and requires no application code changes, unlike clustering or client-side caching.
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 client-side caching to reduce load on the Redis instance.
Why it's wrong here
Client-side caching can help but is not a quick fix for an overwhelmed instance and adds complexity.
✓
Switch to a Memorystore Standard tier instance with a higher capacity and enable scaling.
Why this is correct
Standard tier supports vertical scaling and provides higher throughput and high availability.
Related concept
Read the scenario before looking for a memorised answer.
✗
Migrate to a Memorystore Basic tier instance with a larger memory size.
Why it's wrong here
Basic tier has lower throughput and no replication, which could worsen performance during peak load.
✗
Enable for Redis clustering on the existing instance to distribute load across shards.
Why it's wrong here
Memorystore for Redis does not support clustering; you would need a different product.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that Redis clustering is the only way to scale throughput, but in Memorystore, clustering requires a new instance and is not a simple enablement on an existing instance, making vertical scaling the correct answer for immediate relief without architectural changes.
Detailed technical explanation
How to think about this question
Memorystore Standard tier instances support vertical scaling by increasing memory size, which also increases the instance's CPU and network capacity because GKE allocates proportional resources. Under the hood, Redis is single-threaded for command processing, so scaling memory effectively increases the available CPU cycles for handling more operations per second. In a flash sale scenario, the bottleneck is often the Redis instance's ability to process SET/GET commands for session data, and scaling up provides immediate relief without re-architecting the application.
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.
Building and testing applications — This question tests Building and testing applications — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Switch to a Memorystore Standard tier instance with a higher capacity and enable scaling. — Option B is correct because enabling scaling on a Memorystore Standard tier instance allows you to increase the instance's capacity and throughput without architectural changes. Scaling up the memory size increases the available CPU and network bandwidth, directly addressing the latency spike during the flash sale. This approach maintains the existing Redis configuration and requires no application code changes, unlike clustering or client-side caching.
What should I do if I get this PCD 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.
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Question Discussion
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