- A
Enable SQS long polling and increase the maximum message size for the queue.
Why wrong: Long polling reduces empty receives, and message size changes allow larger payloads. Neither addresses messages that repeatedly fail processing, so poison messages could still repeatedly be delivered and waste consumer capacity.
- B
Send failing messages to an SQS dead-letter queue (DLQ) using a redrive policy based on receive count.
A DLQ with a redrive policy isolates poison messages. After a message is received and fails processing more than the configured maxReceiveCount, SQS moves it to the DLQ, preventing it from continually blocking retries in the source queue.
- C
Change the queue to a FIFO queue and handle duplicates in the worker code without DLQs.
Why wrong: FIFO queues help with ordering and deduplication, but they do not automatically quarantine messages that repeatedly fail validation. Without a DLQ, poison messages would still be retried indefinitely (or until operational limits are reached).
- D
Delete the queue and recreate it hourly to clear out any problematic messages.
Why wrong: Recreating queues is disruptive, can lead to loss of unprocessed messages, and is not a targeted mechanism. It also requires manual operational intervention instead of automatically isolating only the failing messages.
SAA-C03 Design Resilient Architectures Practice Question
This SAA-C03 practice question tests your understanding of design resilient architectures. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 worker consumes messages from an Amazon SQS queue. Some messages consistently fail validation and are retried until the worker can no longer process them. What is the most appropriate AWS mechanism to handle these poison messages while keeping the queue usable?
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
Send failing messages to an SQS dead-letter queue (DLQ) using a redrive policy based on receive count.
Option B is correct because an SQS dead-letter queue (DLQ) with a redrive policy based on receive count allows messages that repeatedly fail processing (poison pills) to be moved out of the main queue after a specified number of retries. This keeps the main queue operational for valid messages and isolates problematic messages for later analysis or manual intervention.
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.
- ✗
Enable SQS long polling and increase the maximum message size for the queue.
Why it's wrong here
Long polling reduces empty receives, and message size changes allow larger payloads. Neither addresses messages that repeatedly fail processing, so poison messages could still repeatedly be delivered and waste consumer capacity.
- ✓
Send failing messages to an SQS dead-letter queue (DLQ) using a redrive policy based on receive count.
Why this is correct
A DLQ with a redrive policy isolates poison messages. After a message is received and fails processing more than the configured maxReceiveCount, SQS moves it to the DLQ, preventing it from continually blocking retries in the source queue.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Change the queue to a FIFO queue and handle duplicates in the worker code without DLQs.
Why it's wrong here
FIFO queues help with ordering and deduplication, but they do not automatically quarantine messages that repeatedly fail validation. Without a DLQ, poison messages would still be retried indefinitely (or until operational limits are reached).
- ✗
Delete the queue and recreate it hourly to clear out any problematic messages.
Why it's wrong here
Recreating queues is disruptive, can lead to loss of unprocessed messages, and is not a targeted mechanism. It also requires manual operational intervention instead of automatically isolating only the failing messages.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may think increasing retries or message size (Option A) solves the problem, but the exam specifically tests the concept of isolating poison messages via a DLQ with a receive-count-based redrive policy to maintain queue availability.
Detailed technical explanation
How to think about this question
Under the hood, the SQS redrive policy uses the `maxReceiveCount` parameter to define how many times a message can be received (via `ReceiveMessage` API calls) before being moved to the DLQ. The DLQ itself must be a standard or FIFO queue of the same type, and the source queue must have a redrive permission policy allowing SQS to send messages to the DLQ. In real-world scenarios, poison messages often result from schema mismatches or transient data corruption, and the DLQ enables automated monitoring via CloudWatch alarms on `ApproximateNumberOfMessagesVisible` in the DLQ to trigger alerts or Lambda remediation.
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: Send failing messages to an SQS dead-letter queue (DLQ) using a redrive policy based on receive count. — Option B is correct because an SQS dead-letter queue (DLQ) with a redrive policy based on receive count allows messages that repeatedly fail processing (poison pills) to be moved out of the main queue after a specified number of retries. This keeps the main queue operational for valid messages and isolates problematic messages for later analysis or manual intervention.
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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