DEA-C01 Data Store Management Practice Question
An e-commerce application uses Amazon ElastiCache for Redis to cache product catalog data. The cache currently uses lazy loading. The team wants to ensure that frequently accessed product data is always fresh. Which caching strategy should they implement?
⚠ Common exam trap
Candidates often assume lazy loading with a short TTL is sufficient for freshness, but the exam tests the understanding that only write-through (or write-behind) strategies guarantee synchronous cache updates without relying on expiration windows.
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
✓
Write-through caching
Write-through caching ensures that data is written to the cache simultaneously with the database, guaranteeing that frequently accessed product data is always fresh. This strategy eliminates stale reads by synchronously updating the cache on every write, which directly addresses the requirement for freshness without relying on expiration or lazy population.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Write-through caching
Why this is correct
Write-through caching updates the Redis cache synchronously on every database write, so cached product data never goes stale. This directly satisfies the freshness constraint that lazy loading cannot guarantee, since lazy loading only populates entries on a miss and leaves existing values stale until eviction or expiry.
- ✗
Set a TTL of 5 minutes for all cached items
Why it's wrong here
A fixed TTL expires entries regardless of access frequency, so popular products still go stale between refreshes and cold reads hit the database. TTLs are tempting as a freshness lever, and a short TTL would suit data where bounded staleness is acceptable rather than requiring frequently accessed items to stay fresh.
- ✗
Use database read replicas to serve data
Why it's wrong here
Read replicas serve database queries directly, bypassing the cache entirely, so they add no freshness mechanism for cached product data and increase database load. Replicas are tempting for scaling reads, and they would be the answer if the goal were offloading read traffic rather than keeping cached entries current.
- ✗
Lazy loading with TTL
Why it's wrong here
Lazy loading with TTL is the existing strategy plus expiry, so data is only refreshed on a miss after expiry, leaving frequently accessed items stale until then. It is tempting because it is the simplest change, and it would be correct if some staleness were tolerable rather than requiring fresh popular data.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-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 DEA-C01 exam.