- A
Write to DynamoDB only, and never update or invalidate the Redis cache.
Why wrong: Never invalidating means stale data may persist in cache until it naturally expires. That conflicts with the requirement for quick visibility of updates. This design sacrifices correctness for simplicity.
- B
Use a cache-aside approach with TTL plus explicit invalidation after writes.
A cache-aside (lazy loading) pattern reads from cache first; if missing/expired, it fetches from the source of truth. After an update, explicitly invalidating or updating the cached entry ensures subsequent reads quickly reflect changes. TTL provides protection against missed invalidations while invalidation accelerates correctness after writes.
- C
Cache only for reads, and do not fetch from DynamoDB when a key is missing.
Why wrong: If you do not fetch from DynamoDB on cache misses, you can return empty or incorrect responses. Cache-aside requires falling back to the source of truth. This option would break the functionality under cache misses.
- D
Rely on eventual consistency of Redis replication to propagate updates to all nodes.
Why wrong: Redis replication behavior is not a substitute for explicit cache invalidation for application-level correctness. Even if replication converges, stale cached entries may still be returned. Correctness needs a strategy tied to write events.
Quick Answer
The answer is a cache-aside strategy with TTL and explicit invalidation. This approach works because after a write to DynamoDB updates a user profile, the application explicitly removes the stale entry from ElastiCache Redis, forcing the next read to fetch the fresh data from DynamoDB and repopulate the cache. The TTL acts as a safety net, ensuring that even if invalidation is missed, the cached profile eventually expires and is refreshed. On the SAA-C03 exam, this scenario tests your understanding of balancing read performance with data consistency for user profile caches, where stale reads are unacceptable. A common trap is choosing write-through caching, which adds latency to every write and is overkill for profiles that are read far more often than updated. Remember the memory tip: “Invalidate on write, lazy load on read”—the cache is a helper, not the source of truth.
SAA-C03 Design High-Performing Architectures Practice Question
This SAA-C03 practice question tests your understanding of design high-performing architectures. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. A key principle to apply: cache-aside reads from cache first, then source of truth on miss.. 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.
Your application uses ElastiCache Redis as a cache for user profiles stored in DynamoDB. You must ensure that when a profile is updated, subsequent reads see the latest value quickly. Which cache strategy is generally the best fit for this requirement?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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 a cache-aside approach with TTL plus explicit invalidation after writes.
Option B is correct because a cache-aside (lazy loading) strategy with TTL and explicit invalidation ensures that after a write to DynamoDB, the stale Redis entry is removed, forcing the next read to fetch the fresh profile from DynamoDB and repopulate the cache. This combination minimizes the window of stale reads while maintaining high read performance, which is critical for user profile caches where consistency matters.
Key principle: Cache-aside reads from cache first, then source of truth on miss.
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 to DynamoDB only, and never update or invalidate the Redis cache.
Why it's wrong here
Never invalidating means stale data may persist in cache until it naturally expires. That conflicts with the requirement for quick visibility of updates. This design sacrifices correctness for simplicity.
- ✓
Use a cache-aside approach with TTL plus explicit invalidation after writes.
Why this is correct
A cache-aside (lazy loading) pattern reads from cache first; if missing/expired, it fetches from the source of truth. After an update, explicitly invalidating or updating the cached entry ensures subsequent reads quickly reflect changes. TTL provides protection against missed invalidations while invalidation accelerates correctness after writes.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Cache-aside reads from cache first, then source of truth on miss.
- ✗
Cache only for reads, and do not fetch from DynamoDB when a key is missing.
Why it's wrong here
If you do not fetch from DynamoDB on cache misses, you can return empty or incorrect responses. Cache-aside requires falling back to the source of truth. This option would break the functionality under cache misses.
- ✗
Rely on eventual consistency of Redis replication to propagate updates to all nodes.
Why it's wrong here
Redis replication behavior is not a substitute for explicit cache invalidation for application-level correctness. Even if replication converges, stale cached entries may still be returned. Correctness needs a strategy tied to write events.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse eventual consistency within Redis replication (which only applies to Redis-to-Redis sync) with the need to synchronize the cache with the authoritative data store (DynamoDB), leading them to pick option D, which does not address the core requirement of reflecting DynamoDB updates in the cache.
Detailed technical explanation
How to think about this question
In a cache-aside pattern, the application code checks the cache first; on a miss, it reads from DynamoDB and writes the result to Redis with a TTL. Explicit invalidation after a write deletes the specific key from Redis, ensuring the next read triggers a cache miss and fetches the updated profile. Under the hood, Redis uses a single-threaded event loop, so the DEL command is atomic and immediately removes the key, preventing race conditions where stale data could be served during the invalidation window.
KKey Concepts to Remember
- Cache-aside reads from cache first, then source of truth on miss.
- Explicit invalidation after writes ensures data freshness.
- TTL on cached items prevents indefinite staleness.
- ElastiCache Redis supports TTL and explicit key invalidation.
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
Cache-aside reads from cache first, then source of truth on miss.
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. Cache-aside reads from cache first, then source of truth on miss. 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 cache-aside reads from cache first, then source of truth on miss., then practise related SAA-C03 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this SAA-C03 question test?
Design High-Performing Architectures — This question tests Design High-Performing Architectures — Cache-aside reads from cache first, then source of truth on miss..
What is the correct answer to this question?
The correct answer is: Use a cache-aside approach with TTL plus explicit invalidation after writes. — Option B is correct because a cache-aside (lazy loading) strategy with TTL and explicit invalidation ensures that after a write to DynamoDB, the stale Redis entry is removed, forcing the next read to fetch the fresh profile from DynamoDB and repopulate the cache. This combination minimizes the window of stale reads while maintaining high read performance, which is critical for user profile caches where consistency matters.
What should I do if I get this SAA-C03 question wrong?
Review cache-aside reads from cache first, then source of truth on miss., then practise related SAA-C03 questions on the same topic to reinforce the concept.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Cache-aside reads from cache first, then source of truth on miss.
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Last reviewed: Jun 11, 2026
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