- A
Publish the event to an Amazon SNS topic and subscribe a separate SQS queue for each downstream service.
SNS fan-out with separate SQS queues decouples the producer from each consumer. Every downstream service gets its own buffered queue, so a slow or unavailable consumer does not block the others or the order service.
- B
Have the order service call all downstream services synchronously so failures are visible immediately.
Why wrong: Synchronous fan-out couples the order path to downstream availability and latency. If shipping or analytics is slow, the order request becomes slow or can fail even when the order itself was accepted successfully.
- C
Use one shared SQS queue for all three consumers so they always process the same message.
Why wrong: A single shared queue creates a competing-consumers model, not fan-out. Only one consumer receives each message, so it does not independently deliver the same event to inventory, shipping, and analytics.
- D
Store the event in a relational database and poll it from every consumer on a fixed schedule.
Why wrong: Polling a database adds latency, lock contention, and operational overhead. It also increases the chance that consumers fall behind or miss events during failures compared with a purpose-built messaging pattern.
- E
Configure a dead-letter queue on each consumer queue to isolate poison messages.
Separate dead-letter queues prevent repeatedly failing messages from blocking a consumer's main queue. This isolates poison messages so healthy events continue to process and operations can inspect or replay the failures later.
Quick Answer
The answer is to publish the event to an SNS topic and configure a dead-letter queue on each consumer SQS queue. This combination works because SNS-SQS fan-out decouple downstream services resilience by letting the order service emit a single notification that SNS automatically distributes to separate SQS queues for inventory, shipping, and analytics. Each SQS queue independently buffers messages and retries processing, so even if the shipping service is slow or unavailable, the order service keeps accepting new orders without blocking. On the SAA-C03 exam, this tests your understanding of asynchronous decoupling patterns and poison-message handling; a common trap is choosing a synchronous solution like direct Lambda invocations, which would couple the services. Remember the memory tip: “Fan-out for decoupling, DLQ for poison” — the topic fans out to queues, and each queue’s DLQ catches messages that fail repeatedly, isolating the problem without affecting other consumers.
SAA-C03 Design Resilient Architectures Practice Question
This SAA-C03 practice question tests your understanding of design resilient 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 order service must notify inventory, shipping, and analytics independently when payment succeeds. The shipping service may be slow, but the order service should keep accepting new orders even if one consumer is unavailable. Which two changes best improve resilience? Select two.
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
Publish the event to an Amazon SNS topic and subscribe a separate SQS queue for each downstream service.
Option A is correct because publishing the event to an SNS topic allows the order service to emit a single notification that is then fanned out to multiple SQS queues, one per downstream service. This decouples the order service from the consumers, so even if the shipping service is slow or unavailable, the order service can continue accepting new orders without blocking. Each SQS queue provides independent buffering and retry logic, ensuring resilience against individual consumer failures.
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.
- ✓
Publish the event to an Amazon SNS topic and subscribe a separate SQS queue for each downstream service.
Why this is correct
SNS fan-out with separate SQS queues decouples the producer from each consumer. Every downstream service gets its own buffered queue, so a slow or unavailable consumer does not block the others or the order service.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Have the order service call all downstream services synchronously so failures are visible immediately.
Why it's wrong here
Synchronous fan-out couples the order path to downstream availability and latency. If shipping or analytics is slow, the order request becomes slow or can fail even when the order itself was accepted successfully.
- ✗
Use one shared SQS queue for all three consumers so they always process the same message.
Why it's wrong here
A single shared queue creates a competing-consumers model, not fan-out. Only one consumer receives each message, so it does not independently deliver the same event to inventory, shipping, and analytics.
- ✗
Store the event in a relational database and poll it from every consumer on a fixed schedule.
Why it's wrong here
Polling a database adds latency, lock contention, and operational overhead. It also increases the chance that consumers fall behind or miss events during failures compared with a purpose-built messaging pattern.
- ✓
Configure a dead-letter queue on each consumer queue to isolate poison messages.
Why this is correct
Separate dead-letter queues prevent repeatedly failing messages from blocking a consumer's main queue. This isolates poison messages so healthy events continue to process and operations can inspect or replay the failures later.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse a single shared queue (Option C) with a fan-out pattern, not realizing that each consumer needs its own queue to process messages independently and avoid head-of-line blocking.
Detailed technical explanation
How to think about this question
Under the hood, Amazon SNS uses a publish-subscribe model where each SQS queue subscribed to the topic receives a copy of the message via a push-based delivery (HTTP/S or AWS internal protocol). The SQS queues then provide at-least-once delivery, visibility timeouts, and configurable redrive policies to a dead-letter queue (DLQ) after a specified number of receive attempts. This pattern is commonly called 'fan-out' and is a core architectural pattern for decoupling microservices in event-driven architectures.
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 Resilient Architectures — This question tests Design Resilient Architectures — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Publish the event to an Amazon SNS topic and subscribe a separate SQS queue for each downstream service. — Option A is correct because publishing the event to an SNS topic allows the order service to emit a single notification that is then fanned out to multiple SQS queues, one per downstream service. This decouples the order service from the consumers, so even if the shipping service is slow or unavailable, the order service can continue accepting new orders without blocking. Each SQS queue provides independent buffering and retry logic, ensuring resilience against individual consumer failures.
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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