- A
Use optimized data structures like hashes instead of strings for complex data.
Correct. Using hashes or other optimized data structures reduces memory and CPU overhead for complex data, improving read/write performance.
- B
Configure the cache to use LRU eviction policy.
Why wrong: Incorrect. LRU eviction policy manages memory when the cache is full but does not directly improve read/write performance.
- C
Disable persistence by setting appendonly to no.
Why wrong: Incorrect. Disabling persistence improves write performance but is not the primary issue for a slow application and may compromise data durability.
- D
Increase the number of shards to distribute data.
Why wrong: Incorrect. Increasing shards distributes data but does not necessarily improve performance if the bottleneck is CPU or memory; auto scaling addresses capacity more effectively.
- E
Enable ElastiCache auto scaling to adjust the number of nodes.
Correct. Enabling auto scaling adjusts the number of nodes based on demand, ensuring adequate resources during traffic spikes and improving performance.
DVA-C02 ElastiCache Auto Scaling Practice Question
This DVA-C02 practice question tests your understanding of troubleshooting and optimization. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. A key principle to apply: elastiCache Auto Scaling. 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 developer is troubleshooting a slow-running application that uses ElastiCache for Redis as a caching layer. The application frequently reads and writes data to the cache. Which TWO actions should the developer take to improve cache 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
Use optimized data structures like hashes instead of strings for complex data.
Option A is correct because using optimized data structures like hashes instead of strings reduces memory and CPU overhead for complex data, improving cache performance. Option E is correct because enabling ElastiCache auto scaling allows the cluster to adjust the number of nodes based on demand, preventing performance degradation during traffic spikes. Option B is incorrect: LRU eviction policy helps manage memory when full but is not a performance optimization for read/write operations. Option C is incorrect: disabling persistence (appendonly no) improves write performance but is not the primary issue for a slow application and may affect data durability. Option D is incorrect: increasing shards distributes data but does not directly improve performance if the bottleneck is CPU or memory; auto scaling is a more targeted solution.
Key principle: ElastiCache Auto Scaling
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 optimized data structures like hashes instead of strings for complex data.
Why this is correct
Correct. Using hashes or other optimized data structures reduces memory and CPU overhead for complex data, improving read/write performance.
Related concept
ElastiCache Auto Scaling
- ✗
Configure the cache to use LRU eviction policy.
Why it's wrong here
Incorrect. LRU eviction policy manages memory when the cache is full but does not directly improve read/write performance.
- ✗
Disable persistence by setting appendonly to no.
Why it's wrong here
Incorrect. Disabling persistence improves write performance but is not the primary issue for a slow application and may compromise data durability.
- ✗
Increase the number of shards to distribute data.
Why it's wrong here
Incorrect. Increasing shards distributes data but does not necessarily improve performance if the bottleneck is CPU or memory; auto scaling addresses capacity more effectively.
- ✓
Enable ElastiCache auto scaling to adjust the number of nodes.
Why this is correct
Correct. Enabling auto scaling adjusts the number of nodes based on demand, ensuring adequate resources during traffic spikes and improving performance.
Related concept
ElastiCache Auto Scaling
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common trap is to think that disabling persistence (appendonly) is the best way to improve write performance in Redis, but in a caching scenario, persistence may not be the main bottleneck.
Detailed technical explanation
How to think about this question
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- ElastiCache Auto Scaling
- Optimized Data Structures
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
ElastiCache Auto Scaling
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. ElastiCache Auto Scaling Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review elastiCache Auto Scaling, then practise related DVA-C02 questions on the same topic to reinforce the concept.
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Troubleshooting and Optimization — study guide chapter
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FAQ
Questions learners often ask
What does this DVA-C02 question test?
Troubleshooting and Optimization — This question tests Troubleshooting and Optimization — ElastiCache Auto Scaling.
What is the correct answer to this question?
The correct answer is: Use optimized data structures like hashes instead of strings for complex data. — Option A is correct because using optimized data structures like hashes instead of strings reduces memory and CPU overhead for complex data, improving cache performance. Option E is correct because enabling ElastiCache auto scaling allows the cluster to adjust the number of nodes based on demand, preventing performance degradation during traffic spikes. Option B is incorrect: LRU eviction policy helps manage memory when full but is not a performance optimization for read/write operations. Option C is incorrect: disabling persistence (appendonly no) improves write performance but is not the primary issue for a slow application and may affect data durability. Option D is incorrect: increasing shards distributes data but does not directly improve performance if the bottleneck is CPU or memory; auto scaling is a more targeted solution.
What should I do if I get this DVA-C02 question wrong?
Review elastiCache Auto Scaling, then practise related DVA-C02 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
ElastiCache Auto Scaling
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Last reviewed: Jun 20, 2026
This DVA-C02 practice question is part of Courseiva's free Amazon Web Services 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 DVA-C02 exam.
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