- 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 the cache-aside pattern with TTL plus explicit invalidation after writes. This approach directly addresses the ElastiCache cache-aside pattern for DynamoDB consistency by ensuring that when a user profile is updated in DynamoDB, the stale entry in Redis is immediately removed, forcing the next read to fetch the fresh data from the database and repopulate the cache. The TTL acts as a safety net to eventually expire any missed stale entries, while explicit invalidation minimizes the window of inconsistency. On the SAA-C03 exam, this scenario tests your understanding of how to balance read performance with data freshness in a caching layer—a common trap is choosing write-through caching, which adds latency to writes and can overload the database. Remember the key: invalidate on write, lazy load on read. A useful memory tip is “Delete the old, load the new”—explicit removal after a write ensures the cache never serves stale data.
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. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. 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.
The cache-aside (lazy loading) pattern with TTL plus explicit invalidation ensures that after a write to DynamoDB, the stale Redis entry is removed, forcing the next read to fetch the updated profile from DynamoDB and repopulate the cache. This minimizes the window of inconsistency while keeping cache management simple and efficient for user profile workloads.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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
Read the scenario before looking for a memorised answer.
- ✗
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 may confuse cache-aside with write-through or write-behind patterns, or assume that Redis replication alone can solve cache consistency, when in fact explicit invalidation is required to ensure reads see the latest value after a write to the primary data store.
Detailed technical explanation
How to think about this question
Under the hood, the cache-aside pattern works by having the application check the cache first; on a miss, it reads from DynamoDB, stores the result in Redis with a TTL (e.g., 300 seconds), and returns it. After a write to DynamoDB, the application explicitly deletes the corresponding Redis key, so the next read triggers a cache miss and fetches the fresh data. In real-world scenarios, this pattern balances read performance with consistency, and the TTL acts as a safety net to eventually evict data even if invalidation is missed due to application errors.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. 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.
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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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a cache-aside approach with TTL plus explicit invalidation after writes. — The cache-aside (lazy loading) pattern with TTL plus explicit invalidation ensures that after a write to DynamoDB, the stale Redis entry is removed, forcing the next read to fetch the updated profile from DynamoDB and repopulate the cache. This minimizes the window of inconsistency while keeping cache management simple and efficient for user profile workloads.
What should I do if I get this SAA-C03 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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