SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company uses Amazon DynamoDB as its primary database. The operations team is seeing increased read latency during peak hours. The table has a provisioned read capacity of 1000 RCU, but CloudWatch metrics show that consumed read capacity frequently reaches 1000 RCU. The application uses eventually consistent reads. What is the MOST cost-effective way to reduce read latency?
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
✓
Enable DynamoDB Accelerator (DAX) to cache frequently read items.
DynamoDB Accelerator (DAX) provides an in-memory cache that reduces read latency by serving frequently accessed items from cache, without increasing provisioned RCU. This is cost-effective as it adds minimal cost compared to increasing capacity. Option A is wrong because switching to strongly consistent reads consumes double the RCU (since they require a read of the primary replica), increasing cost and potentially worsening latency. Option C is wrong because a Global Secondary Index (GSI) offloads reads from the base table but does not reduce latency for reads on the base table itself; it also incurs additional write costs. Option D is wrong because increasing RCU to 2000 would double the cost, though it might reduce throttling, it's not the most cost-effective. Option E is wrong because using ElastiCache adds operational complexity and cost, and DAX is a more seamless, DynamoDB-native caching solution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to strongly consistent reads to improve consistency.
Why it's wrong here
Strongly consistent reads consume double the RCU, worsening throttling.
- ✓
Enable DynamoDB Accelerator (DAX) to cache frequently read items.
Why this is correct
DAX provides microsecond read latency and reduces load on the table.
- ✗
Create a global secondary index (GSI) on the table to offload reads.
Why it's wrong here
GSI is for different access patterns, not for reducing base table read latency.
- ✗
Increase the provisioned read capacity to 2000 RCU.
Why it's wrong here
Increases cost without addressing latency directly.
- ✗
Use Amazon ElastiCache for Memcached as a read cache.
Why it's wrong here
While ElastiCache for Memcached can reduce read load by caching frequently accessed data, it fails here because the bottleneck is provisioned RCU saturation, not a lack of caching. The correct solution must increase read capacity or use DAX, which integrates directly with DynamoDB’s API and handles cache invalidation automatically. Memcached is tempting because it offloads database reads in general, but it would require custom application logic to manage cache misses and staleness, making it less direct for DynamoDB’s eventual consistency model.
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