- A
Add a dead-letter queue and configure the Lambda function to retry on failure with exponential backoff.
Retries with backoff help handle throttling gracefully.
- B
Decrease the batch window to 0 seconds to process records immediately.
Why wrong: This increases write frequency.
- C
Increase the Lambda function's reserved concurrency to process more shards.
Why wrong: More concurrency = more writes, exacerbating the issue.
- D
Increase the batch size of the Kinesis event source mapping for the Lambda function.
Larger batches mean fewer writes, reducing the request rate to DynamoDB.
Question 874 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 is using Amazon Kinesis Data Streams to process real-time stock trade data. The data is consumed by a Lambda function that calculates moving averages and stores results in Amazon DynamoDB. The Lambda function is failing with 'ProvisionedThroughputExceededException' on the DynamoDB table. The table has on-demand capacity. Which TWO actions should the engineer take to resolve this issue?
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 a dead-letter queue and configure the Lambda function to retry on failure with exponential backoff.
Option A is correct because adding a dead-letter queue (DLQ) and configuring the Lambda function to retry on failure with exponential backoff allows the function to handle transient ProvisionedThroughputExceededExceptions from DynamoDB. Since the table uses on-demand capacity, the exception indicates a momentary throttle due to traffic spikes; exponential backoff with retries gives DynamoDB time to scale up, while the DLQ captures records that persistently fail for later analysis.
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.
- ✓
Add a dead-letter queue and configure the Lambda function to retry on failure with exponential backoff.
Why this is correct
Retries with backoff help handle throttling gracefully.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the batch window to 0 seconds to process records immediately.
Why it's wrong here
This increases write frequency.
- ✗
Increase the Lambda function's reserved concurrency to process more shards.
Why it's wrong here
More concurrency = more writes, exacerbating the issue.
- ✓
Increase the batch size of the Kinesis event source mapping for the Lambda function.
Why this is correct
Larger batches mean fewer writes, reducing the request rate to DynamoDB.
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 think increasing concurrency (Option C) helps with DynamoDB throttling, but it actually increases write pressure, while the correct approach is to reduce the request rate via batching (Option D) and handle retries with exponential backoff (Option A).
Detailed technical explanation
How to think about this question
DynamoDB on-demand capacity automatically scales to handle traffic, but it has a per-second throughput limit that can be exceeded during sudden spikes; the ProvisionedThroughputExceededException is a 400-level error that triggers a retryable response. Lambda's event source mapping for Kinesis supports a maximum batch size of 10,000 records, and increasing it (Option D) reduces the number of write operations by batching more records into a single DynamoDB write, which lowers the request rate and helps avoid throttling.
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.
Visual reference
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.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Add a dead-letter queue and configure the Lambda function to retry on failure with exponential backoff. — Option A is correct because adding a dead-letter queue (DLQ) and configuring the Lambda function to retry on failure with exponential backoff allows the function to handle transient ProvisionedThroughputExceededExceptions from DynamoDB. Since the table uses on-demand capacity, the exception indicates a momentary throttle due to traffic spikes; exponential backoff with retries gives DynamoDB time to scale up, while the DLQ captures records that persistently fail for later analysis.
What should I do if I get this DEA-C01 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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