- A
Add a global secondary index for every frequently viewed product attribute.
Why wrong: A GSI helps with alternative query patterns, but it does not function as an in-memory cache for repeated reads of the same items. Creating more indexes also increases write cost and design complexity. The workload already has a good key design, so the real problem is read latency on hot items, not the absence of a query path.
- B
Enable DynamoDB Accelerator to cache frequently accessed items in memory.
DynamoDB Accelerator, or DAX, is the best fit for repeated reads of the same items when eventual consistency is acceptable. It provides an in-memory cache in front of DynamoDB and can dramatically reduce read latency for hot catalog items during traffic spikes. Because the table schema is already sound, DAX adds performance without forcing a redesign of keys or access patterns.
- C
Switch the table to on-demand capacity mode to reduce latency.
Why wrong: On-demand capacity simplifies scaling, but it does not provide caching or directly reduce per-request latency for repeated reads. It helps absorb traffic variability, yet the underlying read path still goes to DynamoDB. In this scenario, the issue is fast access to hot items, so capacity mode alone is not enough.
- D
Move the catalog to Aurora and use a read replica for every region.
Why wrong: Migrating to Aurora would introduce a different database model and does not address the immediate problem in the simplest way. Read replicas can help with relational read scaling, but they are not a drop-in optimization for this DynamoDB workload. The question specifically asks for the least disruptive change, and DAX preserves the current architecture.
SAA-C03 Design Secure Architectures Practice Question
This SAA-C03 practice question tests your understanding of design secure 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.
A mobile app reads the same product catalog items repeatedly throughout the day. The DynamoDB table is already properly keyed, but read latency is still a problem during sales events. The team can tolerate eventually consistent reads and wants the least disruptive change. What should they add?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"least"Why it matters: You want the option with minimum overhead, fewest steps, or lowest impact — not the most feature-rich or comprehensive answer.
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 to cache frequently accessed items in memory.
DynamoDB Accelerator (DAX) is a fully managed, in-memory cache that reduces read latency for frequently accessed items by orders of magnitude, from single-digit milliseconds to microseconds. Since the team can tolerate eventually consistent reads, DAX is ideal because it caches read results and serves them without additional DynamoDB read capacity consumption, making it the least disruptive change — no schema changes or application rewrites are required.
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.
- ✗
Add a global secondary index for every frequently viewed product attribute.
Why it's wrong here
A GSI helps with alternative query patterns, but it does not function as an in-memory cache for repeated reads of the same items. Creating more indexes also increases write cost and design complexity. The workload already has a good key design, so the real problem is read latency on hot items, not the absence of a query path.
When this WOULD be correct
A question where the app needs to query items by non-key attributes (e.g., filtering or sorting by product category) and the current table key does not support those access patterns efficiently.
- ✓
Enable DynamoDB Accelerator to cache frequently accessed items in memory.
Why this is correct
DynamoDB Accelerator, or DAX, is the best fit for repeated reads of the same items when eventual consistency is acceptable. It provides an in-memory cache in front of DynamoDB and can dramatically reduce read latency for hot catalog items during traffic spikes. Because the table schema is already sound, DAX adds performance without forcing a redesign of keys or access patterns.
Clue confirmation
The clue word "least" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Switch the table to on-demand capacity mode to reduce latency.
Why it's wrong here
On-demand capacity simplifies scaling, but it does not provide caching or directly reduce per-request latency for repeated reads. It helps absorb traffic variability, yet the underlying read path still goes to DynamoDB. In this scenario, the issue is fast access to hot items, so capacity mode alone is not enough.
When this WOULD be correct
A DynamoDB table experiences frequent throttling errors due to unpredictable traffic spikes, and the team wants to avoid manual capacity management. On-demand capacity mode would be correct to automatically scale throughput.
- ✗
Move the catalog to Aurora and use a read replica for every region.
Why it's wrong here
Migrating to Aurora would introduce a different database model and does not address the immediate problem in the simplest way. Read replicas can help with relational read scaling, but they are not a drop-in optimization for this DynamoDB workload. The question specifically asks for the least disruptive change, and DAX preserves the current architecture.
When this WOULD be correct
This option would be correct in a scenario where the application requires complex SQL queries, joins, or transactions that DynamoDB cannot support, and the team is already considering migrating to a relational database. For example: 'A company needs to run complex analytical queries on product catalog data and requires high availability across multiple regions.'
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The SAA-C03 exam frequently reuses these exact scenarios with slightly different constraints.
✓Enable DynamoDB Accelerator to cache frequently accessed items in memory.Correct answer▾
Why this is correct
DynamoDB Accelerator, or DAX, is the best fit for repeated reads of the same items when eventual consistency is acceptable. It provides an in-memory cache in front of DynamoDB and can dramatically reduce read latency for hot catalog items during traffic spikes. Because the table schema is already sound, DAX adds performance without forcing a redesign of keys or access patterns.
✗Add a global secondary index for every frequently viewed product attribute.Wrong answer — click to see why▾
Why this is wrong here
Adding a GSI for every frequently viewed attribute does not reduce read latency for repeated reads of the same items; it adds storage and write costs without addressing the latency caused by repeated reads from disk.
★ When this WOULD be the correct answer
A question where the app needs to query items by non-key attributes (e.g., filtering or sorting by product category) and the current table key does not support those access patterns efficiently.
Why candidates choose this
Candidates may think that indexing more attributes will speed up reads, but GSIs are for alternative query patterns, not for caching repeated reads of the same items.
✗Switch the table to on-demand capacity mode to reduce latency.Wrong answer — click to see why▾
Why this is wrong here
Switching to on-demand capacity mode addresses throughput provisioning, not read latency. Latency issues from repeated reads are better solved by caching, not capacity mode changes.
★ When this WOULD be the correct answer
A DynamoDB table experiences frequent throttling errors due to unpredictable traffic spikes, and the team wants to avoid manual capacity management. On-demand capacity mode would be correct to automatically scale throughput.
Why candidates choose this
Candidates may confuse throughput provisioning with latency optimization, assuming that 'on-demand' automatically reduces latency by scaling instantly.
✗Move the catalog to Aurora and use a read replica for every region.Wrong answer — click to see why▾
Why this is wrong here
Moving to Aurora and using read replicas is a much more disruptive change than enabling DAX, and it does not address the core issue of caching frequently accessed items in memory for low-latency reads. Aurora is a relational database, not a key-value store like DynamoDB, and the question specifies the team wants the least disruptive change.
★ When this WOULD be the correct answer
This option would be correct in a scenario where the application requires complex SQL queries, joins, or transactions that DynamoDB cannot support, and the team is already considering migrating to a relational database. For example: 'A company needs to run complex analytical queries on product catalog data and requires high availability across multiple regions.'
Why candidates choose this
Candidates may think that moving to a more powerful database like Aurora with read replicas will solve latency issues, especially if they are more familiar with relational databases than DynamoDB caching solutions. They might also overestimate the disruption of enabling DAX compared to a full database migration.
Analysis generated from the official SAA-C03blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse throughput scaling (on-demand capacity) with latency reduction, or they over-engineer the solution by migrating to a different database when a simple caching layer (DAX) is the least disruptive and most cost-effective fix.
Trap categories for this question
Scenario analysis trap
On-demand capacity simplifies scaling, but it does not provide caching or directly reduce per-request latency for repeated reads. It helps absorb traffic variability, yet the underlying read path still goes to DynamoDB. In this scenario, the issue is fast access to hot items, so capacity mode alone is not enough.
Detailed technical explanation
How to think about this question
DAX maintains a write-through cache that is eventually consistent with the DynamoDB table, meaning reads from DAX may return stale data until the cache is invalidated or updated. Under the hood, DAX uses a cluster of nodes with a primary node handling writes and replicas serving reads, and it supports both strongly consistent and eventually consistent read modes. In real-world scenarios, DAX is particularly effective for read-heavy workloads like product catalogs, gaming leaderboards, or session stores where latency spikes during flash sales or viral events.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
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FAQ
Questions learners often ask
What does this SAA-C03 question test?
Design Secure Architectures — This question tests Design Secure Architectures — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable DynamoDB Accelerator to cache frequently accessed items in memory. — DynamoDB Accelerator (DAX) is a fully managed, in-memory cache that reduces read latency for frequently accessed items by orders of magnitude, from single-digit milliseconds to microseconds. Since the team can tolerate eventually consistent reads, DAX is ideal because it caches read results and serves them without additional DynamoDB read capacity consumption, making it the least disruptive change — no schema changes or application rewrites are required.
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: "least". You want the option with minimum overhead, fewest steps, or lowest impact — not the most feature-rich or comprehensive answer.
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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