- A
Increase the writer instance size so it can handle more reads and writes simultaneously.
Why wrong: Scaling the writer increases resources, but it does not isolate read workload from write workload. With a heavily read traffic pattern, the writer still becomes the bottleneck due to shared compute/storage resources for both reads and writes.
- B
Add Aurora reader instances (read replicas) and route read queries to the reader endpoint while keeping writes on the writer endpoint.
Aurora reader instances are designed for exactly this pattern: they provide dedicated compute capacity for read-only workloads. By sending read queries to the reader endpoint and keeping writes on the writer endpoint, the cluster can scale read performance without forcing reads to contend with write processing on the writer.
- C
Enable Multi-AZ failover only and rely on the standby to serve reads in normal operation.
Why wrong: Multi-AZ standby primarily provides high availability and failover behavior. It is not the same as adding dedicated reader capacity for steady-state read scaling, and it is not intended as a normal operational read offload path.
- D
Move the read workload to ElastiCache Redis while keeping DynamoDB as the SQL data source.
Why wrong: ElastiCache is a caching layer and Redis does not replace Aurora PostgreSQL SQL query execution for arbitrary read patterns without additional application/data redesign. The scenario asks for offloading reads from Aurora while keeping core query patterns, which aligns with Aurora readers rather than changing the data architecture.
Quick Answer
The answer is to add Aurora reader instances (read replicas) and route read queries to the reader endpoint while keeping writes on the writer endpoint. This is correct because Aurora’s reader endpoint automatically distributes read-only connections across all replicas, offloading the 85% read-heavy traffic from the writer instance without altering application query patterns. On the SAA-C03 exam, this scenario tests your understanding of Aurora’s separation of read and write endpoints, a key concept for scaling read-heavy workloads. A common trap is to suggest using a single read replica with a custom load balancer, but Aurora’s built-in reader endpoint handles distribution natively, making it simpler and more reliable. Remember the memory tip: “Writes to the writer, reads to the reader” — always pair the correct endpoint with the workload type to avoid misrouting traffic.
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 cluster is experiencing high read latency because 85% of traffic consists of read-only queries. The write workload must stay on the writer instance, and the team wants to offload reads without changing the application’s core query patterns. What is the best architectural option?
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
Add Aurora reader instances (read replicas) and route read queries to the reader endpoint while keeping writes on the writer endpoint.
Adding Aurora reader instances (read replicas) and routing read queries to the reader endpoint offloads read traffic from the writer instance without altering application query patterns. Aurora reader endpoints automatically distribute read-only connections across all replicas, reducing latency on the writer while keeping writes on the writer instance. This directly addresses the 85% read-heavy workload without requiring application changes.
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.
- ✗
Increase the writer instance size so it can handle more reads and writes simultaneously.
Why it's wrong here
Scaling the writer increases resources, but it does not isolate read workload from write workload. With a heavily read traffic pattern, the writer still becomes the bottleneck due to shared compute/storage resources for both reads and writes.
- ✓
Add Aurora reader instances (read replicas) and route read queries to the reader endpoint while keeping writes on the writer endpoint.
Why this is correct
Aurora reader instances are designed for exactly this pattern: they provide dedicated compute capacity for read-only workloads. By sending read queries to the reader endpoint and keeping writes on the writer endpoint, the cluster can scale read performance without forcing reads to contend with write processing on the writer.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Enable Multi-AZ failover only and rely on the standby to serve reads in normal operation.
Why it's wrong here
Multi-AZ standby primarily provides high availability and failover behavior. It is not the same as adding dedicated reader capacity for steady-state read scaling, and it is not intended as a normal operational read offload path.
- ✗
Move the read workload to ElastiCache Redis while keeping DynamoDB as the SQL data source.
Why it's wrong here
ElastiCache is a caching layer and Redis does not replace Aurora PostgreSQL SQL query execution for arbitrary read patterns without additional application/data redesign. The scenario asks for offloading reads from Aurora while keeping core query patterns, which aligns with Aurora readers rather than changing the data architecture.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Multi-AZ standby instances (which are passive and cannot serve reads) with Aurora reader replicas (which are active and can serve reads), leading them to incorrectly select Option C.
Trap categories for this question
Scenario analysis trap
ElastiCache is a caching layer and Redis does not replace Aurora PostgreSQL SQL query execution for arbitrary read patterns without additional application/data redesign. The scenario asks for offloading reads from Aurora while keeping core query patterns, which aligns with Aurora readers rather than changing the data architecture.
Detailed technical explanation
How to think about this question
Aurora reader instances connect to the same shared storage volume as the writer, so they serve reads with minimal replication lag (typically <100ms) and scale horizontally. The reader endpoint performs DNS round-robin across all available readers, enabling automatic load distribution without application-side connection pooling changes. In production, this pattern is commonly used for read-heavy workloads like reporting dashboards or analytics, where even a single reader can offload thousands of read queries per second from the writer.
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: Add Aurora reader instances (read replicas) and route read queries to the reader endpoint while keeping writes on the writer endpoint. — Adding Aurora reader instances (read replicas) and routing read queries to the reader endpoint offloads read traffic from the writer instance without altering application query patterns. Aurora reader endpoints automatically distribute read-only connections across all replicas, reducing latency on the writer while keeping writes on the writer instance. This directly addresses the 85% read-heavy workload without requiring application changes.
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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