DBS-C01 Management and Operations Practice Question
A company is using Amazon ElastiCache for Redis as a caching layer for a high-traffic web application. The cache hit ratio has dropped from 95% to 70% after a recent deployment that changed the cache key structure. The application team wants to improve the hit ratio without increasing the cache memory. Which action should they take?
⚠ Common exam trap
It's easy for candidates to confuse TTL management (options C and D) with key distribution issues, mistakenly believing that extending or randomizing expiration times will fix a hit ratio drop caused by poor key placement across cluster nodes.
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
✓
Implement a consistent hashing algorithm for key distribution.
A drop in cache hit ratio after changing the key structure indicates that the new keys are not being distributed evenly across the cluster nodes, causing some nodes to be overloaded with misses. Implementing a consistent hashing algorithm (e.g., using the Redis Cluster hash slot mechanism or a client-side library like libketama) ensures that keys are distributed uniformly across shards, minimizing cache misses and improving the hit ratio without adding memory.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Disable Cluster Mode and use a single node.
Why it's wrong here
Using a single node reduces capacity and can lead to more evictions, worsening the hit ratio.
- ✓
Implement a consistent hashing algorithm for key distribution.
Why this is correct
Consistent hashing minimizes key redistribution when nodes change and ensures even distribution, reducing evictions and improving hit ratio.
- ✗
Increase the TTL (time-to-live) for all cache keys.
Why it's wrong here
Increasing TTL keeps data longer but does not address the underlying distribution issue; it may lead to stale data.
- ✗
Use random TTLs to spread out expiration times.
Why it's wrong here
Random TTLs do not address the distribution problem and can cause cache misses at unpredictable times.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DBS-C01 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 DBS-C01 exam.