MLS-C01 Data Engineering Practice Question
A company uses Amazon Kinesis Data Streams to collect clickstream data. The data is consumed by a Lambda function that writes to DynamoDB. Occasionally, the Lambda function fails due to throttling from DynamoDB. How can the company resolve this issue without losing data?
⚠ Common exam trap
Candidates often assume increasing shards or adding a buffer will solve throttling, but the real issue is the downstream write volume per invocation, which is directly controlled by the batch size in the event source mapping.
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
✓
Decrease the batch size in the Lambda event source mapping.
Decreasing the batch size in the Lambda event source mapping reduces the number of records sent to each Lambda invocation. This lowers the write throughput demand on DynamoDB per invocation, mitigating throttling while still allowing Lambda to retry failed records individually. The Kinesis stream retains data for up to 365 days, so no data is lost as long as the Lambda function eventually processes all records.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ignore the throttling errors and let Lambda retry.
Why it's wrong here
Retries don't solve the root cause and may lead to data loss if retention exceeded.
- ✗
Increase the number of shards in the Kinesis stream.
Why it's wrong here
More shards increase parallelism, potentially more writes to DynamoDB.
- ✗
Use an Amazon SQS queue as a buffer between Kinesis and Lambda.
Why it's wrong here
SQS adds complexity and delay; not necessary.
- ✓
Decrease the batch size in the Lambda event source mapping.
Why this is correct
Smaller batches reduce the write rate, avoiding throttling.
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 MLS-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 MLS-C01 exam.