- A
Add Aurora Replicas to scale out the read workload.
Aurora Replicas provide additional read capacity, which lets you spread read-only traffic away from the writer instance.
- B
Send read-only application traffic to the reader endpoint.
The reader endpoint automatically distributes reads across available replicas, reducing load on the writer and improving throughput.
- C
Scale up only the writer instance and keep all queries on it.
Why wrong: A larger writer may help briefly, but it does not address the core issue of separating read-heavy traffic from writes.
- D
Replace the cluster with a single-AZ RDS instance to reduce replication overhead.
Why wrong: A single instance removes read scaling options and usually makes availability and read performance worse, not better.
- E
Move the dashboard to DynamoDB without changing the query model.
Why wrong: This is not a direct fix for an Aurora read bottleneck and would require a major application redesign.
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.
An Aurora PostgreSQL application has an OLTP writer and a reporting dashboard that issues many read-only queries. The writer is healthy, but read latency rises noticeably during reporting windows. Which two changes should you make? Select two.
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
Add Aurora Replicas to scale out the read workload.
Adding Aurora Replicas (Option A) is correct because Aurora Replicas are dedicated read-only instances that share the same underlying storage volume as the writer, allowing you to scale read capacity linearly without impacting write performance. Sending read-only traffic to the reader endpoint (Option B) is correct because the reader endpoint automatically load-balances connections across all available Aurora Replicas, ensuring that dashboard queries are distributed and do not overload a single instance.
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 Aurora Replicas to scale out the read workload.
Why this is correct
Aurora Replicas provide additional read capacity, which lets you spread read-only traffic away from the writer instance.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Send read-only application traffic to the reader endpoint.
Why this is correct
The reader endpoint automatically distributes reads across available replicas, reducing load on the writer and improving throughput.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Scale up only the writer instance and keep all queries on it.
Why it's wrong here
A larger writer may help briefly, but it does not address the core issue of separating read-heavy traffic from writes.
When this WOULD be correct
In a scenario where the database is CPU-bound on the writer due to write-heavy workload and read latency is acceptable, scaling up the writer instance (vertical scaling) would be correct to increase write throughput.
- ✗
Replace the cluster with a single-AZ RDS instance to reduce replication overhead.
Why it's wrong here
A single instance removes read scaling options and usually makes availability and read performance worse, not better.
- ✗
Move the dashboard to DynamoDB without changing the query model.
Why it's wrong here
This is not a direct fix for an Aurora read bottleneck and would require a major application redesign.
When this WOULD be correct
This option would be correct in a scenario where the reporting dashboard requires extremely low-latency access to a simple, high-traffic dataset (e.g., user session data or IoT events) and the application can be refactored to use DynamoDB's query patterns, with the original Aurora cluster handling only transactional writes.
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.
✓Add Aurora Replicas to scale out the read workload.Correct answer▾
Why this is correct
Aurora Replicas provide additional read capacity, which lets you spread read-only traffic away from the writer instance.
✗Scale up only the writer instance and keep all queries on it.Wrong answer — click to see why▾
Why this is wrong here
Scaling up the writer instance does not offload read queries; the writer still handles all traffic, so read latency remains high during reporting windows. Aurora Replicas are needed to distribute read-only queries.
★ When this WOULD be the correct answer
In a scenario where the database is CPU-bound on the writer due to write-heavy workload and read latency is acceptable, scaling up the writer instance (vertical scaling) would be correct to increase write throughput.
Why candidates choose this
Candidates may think that a more powerful writer can handle both reads and writes faster, overlooking that Aurora's architecture separates read scaling via replicas.
✗Move the dashboard to DynamoDB without changing the query model.Wrong answer — click to see why▾
Why this is wrong here
Moving the dashboard to DynamoDB without changing the query model is wrong because DynamoDB is a NoSQL database with a different query model (key-value and document), so existing SQL queries from the reporting dashboard would not work without significant application changes.
★ When this WOULD be the correct answer
This option would be correct in a scenario where the reporting dashboard requires extremely low-latency access to a simple, high-traffic dataset (e.g., user session data or IoT events) and the application can be refactored to use DynamoDB's query patterns, with the original Aurora cluster handling only transactional writes.
Why candidates choose this
Candidates may think DynamoDB is always a good choice for read-heavy workloads due to its scalability and low latency, overlooking the fact that the existing query model (SQL) is incompatible with DynamoDB's NoSQL interface.
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 may think scaling up the writer instance (Option C) is sufficient, but they overlook that read-heavy workloads require horizontal read scaling via replicas, not just vertical scaling of the writer.
Detailed technical explanation
How to think about this question
Aurora Replicas use the same cluster volume as the writer, so there is no replication lag from copying data; they can serve read traffic with minimal latency. The reader endpoint performs DNS round-robin across all Aurora Replicas, but for consistent load balancing in production, consider using an application-level connection pool or a proxy like Amazon RDS Proxy. In a real-world scenario, if the reporting dashboard runs complex aggregation queries, you might also need to tune the replica instance class or use Aurora’s parallel query feature to push down filtering to the storage layer.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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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: Add Aurora Replicas to scale out the read workload. — Adding Aurora Replicas (Option A) is correct because Aurora Replicas are dedicated read-only instances that share the same underlying storage volume as the writer, allowing you to scale read capacity linearly without impacting write performance. Sending read-only traffic to the reader endpoint (Option B) is correct because the reader endpoint automatically load-balances connections across all available Aurora Replicas, ensuring that dashboard queries are distributed and do not overload a single instance.
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.
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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