DVA-C02 Troubleshooting and Optimization Practice Question
A developer is troubleshooting an application that uses Amazon ElastiCache for Redis to improve performance. The application periodically experiences high latency during peak hours. The developer checks the ElastiCache metrics and sees that the 'Evictions' metric is consistently high and the 'CacheHitRate' metric is low. The cluster has a single node with a cache.t3.small instance type. Which action will most likely improve the cache hit rate and reduce latency?
⚠ Common exam trap
The trap here is that candidates may focus on optimizing eviction policies or adding replicas, but the core issue is insufficient memory capacity, which only scaling up can resolve.
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
✓
Scale up to a larger node type (e.g., cache.t3.medium) to increase available memory.
The high 'Evictions' and low 'CacheHitRate' metrics indicate that the Redis node is running out of memory, forcing it to evict keys to make room for new data. Scaling up to a larger node type (cache.t3.medium) increases the available memory, allowing more data to be cached and reducing evictions, which directly improves the cache hit rate and reduces latency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Scale up to a larger node type (e.g., cache.t3.medium) to increase available memory.
Why this is correct
Scaling up to a larger node type directly increases the available RAM for the Redis instance. This additional memory allows the cache to store more data, significantly reducing the frequency of key evictions caused by memory pressure. Consequently, the cache hit rate improves, as more requested data is found in cache, leading to lower latency and better application performance by minimizing database lookups.
- ✗
Enable cluster mode and distribute data across multiple shards to reduce memory pressure.
Why it's wrong here
Enabling cluster mode increases total available memory by partitioning data across shards, yet it does not address the immediate need to increase the capacity of a single node's RAM. This approach fails because the primary issue is an undersized instance type causing evictions due to insufficient memory per shard. Sharding is intended for scaling throughput and expanding aggregate storage capacity when a single node reaches its maximum limit or CPU ceiling.
- ✗
Change the eviction policy to 'allkeys-lfu' to better manage which keys are evicted.
Why it's wrong here
Changing the eviction policy can improve the quality of evictions (e.g., keep frequently used keys), but if the memory is full, evictions will still occur. This may help the hit rate but not as effectively as adding memory.
- ✗
Add a read replica for the Redis cluster to offload read traffic.
Why it's wrong here
Adding a read replica primarily serves to distribute read traffic and enhance high availability, not to increase the memory capacity of the primary node. Evictions occur when the primary's allocated memory is exhausted, irrespective of replica presence. Replicas maintain a copy of the primary's data but do not contribute to the primary's operational memory pool, thus failing to resolve the underlying memory shortage causing evictions.
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1 more way this is tested on DVA-C02
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Variation 1. A developer is troubleshooting performance issues in an application that uses Amazon ElastiCache for Redis. The application experiences periodic latency spikes during peak hours. The developer checks CloudWatch metrics and sees that the 'Evictions' metric is consistently high and the 'CacheHitRate' metric is low. The cluster uses a single cache.t3.small node. Which action will most likely improve the cache hit rate and reduce latency?
hard- A.Increase the number of replicas
- B.Enable cluster mode and add more shards
- C.Increase the TTL of cached items
- ✓ D.Use a larger instance type
Why D: The symptoms—high evictions and low cache hit rate—indicate that the single cache.t3.small node is running out of memory. Using a larger instance type increases the available memory, allowing more data to be cached, reducing evictions, and improving the cache hit rate. This directly addresses the root cause of memory pressure without changing the cluster architecture or data expiration behavior.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.