- A
Use Amazon SQS to buffer the requests and have Lambda pull from the queue with a reserved concurrency limit.
Why wrong: Does not directly address DynamoDB throttling.
- B
Increase the DynamoDB provisioned read and write capacity units to a high fixed value.
Why wrong: Fixed high capacity is not cost-effective.
- C
Provision DynamoDB Accelerator (DAX) to cache reads and reduce throttling.
Why wrong: DAX helps with read-heavy workloads, not write throttling.
- D
Configure DynamoDB auto scaling and implement a dead-letter queue in Lambda to retry failed events.
Auto scaling handles peaks; DLQ ensures no data loss.
Question 1,732 of 1,750
Handling DynamoDB Throttling from Lambda
This DOP-C02 practice question tests your understanding of resilient cloud solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 company uses AWS Lambda with Amazon DynamoDB to process orders. During peak hours, the Lambda function sometimes fails with throttling errors from DynamoDB. The system must be resilient and cost-effective. What should a DevOps engineer do?
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 DynamoDB auto scaling and implement a dead-letter queue in Lambda to retry failed events.
Option D is correct because configuring DynamoDB auto scaling allows the table to adjust its provisioned capacity based on actual traffic patterns, preventing throttling during peak hours while remaining cost-effective during low usage. Implementing a dead-letter queue (DLQ) in Lambda ensures that failed events (e.g., due to transient throttling) are captured and can be retried or investigated, providing resilience without 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.
- ✗
Use Amazon SQS to buffer the requests and have Lambda pull from the queue with a reserved concurrency limit.
Why it's wrong here
Does not directly address DynamoDB throttling.
- ✗
Increase the DynamoDB provisioned read and write capacity units to a high fixed value.
Why it's wrong here
Fixed high capacity is not cost-effective.
- ✗
Provision DynamoDB Accelerator (DAX) to cache reads and reduce throttling.
Why it's wrong here
DAX helps with read-heavy workloads, not write throttling.
- ✓
Configure DynamoDB auto scaling and implement a dead-letter queue in Lambda to retry failed events.
Why this is correct
Auto scaling handles peaks; DLQ ensures no data loss.
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 may confuse read caching solutions (DAX) or queue-based decoupling (SQS) with the direct need to scale write capacity and handle retries, overlooking the combination of auto scaling and DLQ as the most resilient and cost-effective approach for write-throttling scenarios.
Detailed technical explanation
How to think about this question
DynamoDB auto scaling uses the AWS Application Auto Scaling service to dynamically adjust provisioned throughput based on target utilization (e.g., 70% of consumed capacity), using CloudWatch alarms on the ConsumedWriteCapacity and ConsumedReadCapacity metrics. The dead-letter queue in Lambda, configured via the event source mapping or function-async invocation, captures events that fail after all retry attempts (default: 3 retries with exponential backoff), allowing for later reprocessing or analysis without data loss.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Resilient Cloud Solutions — study guide chapter
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FAQ
Questions learners often ask
What does this DOP-C02 question test?
Resilient Cloud Solutions — This question tests Resilient Cloud Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure DynamoDB auto scaling and implement a dead-letter queue in Lambda to retry failed events. — Option D is correct because configuring DynamoDB auto scaling allows the table to adjust its provisioned capacity based on actual traffic patterns, preventing throttling during peak hours while remaining cost-effective during low usage. Implementing a dead-letter queue (DLQ) in Lambda ensures that failed events (e.g., due to transient throttling) are captured and can be retried or investigated, providing resilience without manual intervention.
What should I do if I get this DOP-C02 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: Jul 4, 2026
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