SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company runs a serverless application using AWS Lambda functions that process messages from an Amazon SQS queue. The company wants to improve the reliability of message processing by ensuring that failed messages are not lost and can be reprocessed later. Which solution should a solutions architect recommend?
⚠ Common exam trap
A common mix-up: candidates confuse visibility timeout or long polling with failure handling, when only a dead-letter queue can capture and retain failed messages.
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
✓
Configure a dead-letter queue (DLQ) for the source SQS queue and set a maximum receive count.
Configuring a dead-letter queue on the source SQS queue ensures that messages that repeatedly fail processing are moved to a separate queue for later analysis and reprocessing. This prevents message loss and is a built-in reliability feature of SQS.
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 visibility timeout of the SQS queue to allow more time for Lambda to process messages.
Why it's wrong here
Increasing visibility timeout only gives Lambda more time to process a message before it becomes visible again. It does not prevent message loss after repeated failures. Without a DLQ, messages could be processed indefinitely or lost if the queue's retention period expires.
- ✗
Enable long polling on the SQS queue to reduce the number of empty responses.
Why it's wrong here
Long polling reduces cost and latency by waiting for messages, but it does not address failed message handling. It does not prevent message loss or provide a mechanism to reprocess failed messages. It is unrelated to the requirement.
- ✓
Configure a dead-letter queue (DLQ) for the source SQS queue and set a maximum receive count.
Why this is correct
A dead-letter queue captures messages that fail processing after a specified number of receives, preventing them from being lost. The messages can be analyzed and reprocessed later. This is a standard SQS feature that improves reliability without application changes.
- ✗
Use an Amazon SNS topic to fan out messages to multiple SQS queues for redundancy.
Why it's wrong here
Fan-out with SNS and multiple SQS queues provides redundancy but does not handle failed message processing. Each queue would still need a DLQ to capture failures. This adds complexity without directly solving the problem of reprocessing failed messages.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This SAP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SAP-C02 exam.