DEA-C01 Data Operations and Support Practice Question
A company uses Amazon Kinesis Data Streams with a Lambda consumer. The Lambda function is failing with 'ProvisionedThroughputExceededException' when writing to a DynamoDB table. Which action should the data engineer take to resolve this without losing data?
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) on the Lambda function and increase the DynamoDB write capacity.
The 'ProvisionedThroughputExceededException' occurs when the Lambda function exceeds the DynamoDB table's write capacity. To resolve this without data loss, the data engineer should both increase the DynamoDB write capacity to accommodate the throughput and configure a dead-letter queue (DLQ) on the Lambda function. The DLQ captures records that fail after all retries, preventing data loss. Option A (reducing shards) would lower the ingestion rate but may cause data loss and does not address the root cause. Option B (increasing read capacity) is irrelevant because the issue is with writes. Option D (disabling retries) would cause data loss because failed records would not be retried.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the number of Kinesis shards to lower the ingestion rate.
Why it's wrong here
Reducing shards would lower ingestion but may cause data loss if the shard is deleted.
- ✗
Increase the DynamoDB table's read capacity.
Why it's wrong here
The error is about write capacity, not read.
- ✓
Configure a dead-letter queue (DLQ) on the Lambda function and increase the DynamoDB write capacity.
Why this is correct
The DLQ captures failed records, and increasing write capacity reduces throttling. Together, they prevent data loss.
- ✗
Disable retries on the Lambda function to avoid throttling.
Why it's wrong here
Disabling retries would cause data to be lost if the write fails.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 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 DEA-C01 exam.