MLS-C01 Lambda Timeout Practice Question
Exhibit
Refer to the exhibit.
```
{
"Records": [
{
"eventVersion": "2.1",
"eventSource": "aws:s3",
"awsRegion": "us-east-1",
"eventName": "ObjectCreated:Put",
"s3": {
"s3SchemaVersion": "1.0",
"bucket": {
"name": "my-data-lake",
"arn": "arn:aws:s3:::my-data-lake"
},
"object": {
"key": "data/2023/01/15/sample.json",
"size": 1024,
"eTag": "abc123"
}
}
}
]
}
```An S3 event notification triggers an AWS Lambda function when a new object is created. The Lambda function parses the event and processes the object. The function is failing with a timeout error for large objects. Which approach should be used to handle large objects efficiently?
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
✓
Increase the Lambda function timeout to 15 minutes
Increasing the Lambda function timeout to the maximum of 15 minutes directly addresses the timeout error for large objects. This allows the function to complete processing within the allotted time. Option B (SQS queue) does not solve the timeout issue because the processing time itself is too long; buffering events does not reduce processing time. Option C (Kinesis) adds unnecessary streaming complexity. Option D (Step Functions) adds orchestration overhead without addressing the timeout.
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 Lambda function timeout to 15 minutes
Why this is correct
Increasing the Lambda timeout is the direct solution to timeout errors. Lambda allows a maximum timeout of 15 minutes, which can accommodate processing of larger objects.
- ✗
Use an SQS queue to buffer event notifications and configure Lambda with a batch window
Why it's wrong here
Using an SQS queue to buffer events does not reduce the processing time of the Lambda function. The timeout error occurs because the processing takes too long, not because events arrive too quickly.
- ✗
Stream events to Amazon Kinesis Data Streams and process with Lambda
Why it's wrong here
Kinesis Data Streams are used for real-time streaming data and do not solve the Lambda timeout issue for large object processing.
- ✗
Use AWS Step Functions to orchestrate the processing
Why it's wrong here
Step Functions add orchestration but do not directly increase the processing time limit; the Lambda function would still time out.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
Related to this question
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JA
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.