DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data is transformed using an AWS Lambda function. Recently, the transformation errors have increased due to Lambda timeouts. The data engineer needs to diagnose and resolve the issue without losing data. What should the engineer do?
⚠ Common exam trap
Watch out — candidates often confuse logging (CloudWatch Logs) with actual data preservation, or assume that SQS is a native Firehose failure destination, when in fact Firehose only supports S3 or Redshift as backup destinations for failed records.
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 and ensure that failed records are sent to a backup S3 bucket
Increasing the Lambda function timeout directly addresses the root cause of transformation errors (timeouts), and configuring a backup S3 bucket for failed records ensures no data loss. Kinesis Data Firehose can be configured to send failed records to a separate S3 bucket as a dead-letter queue, which preserves the data for later reprocessing while the primary transformation pipeline is fixed.
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 and ensure that failed records are sent to a backup S3 bucket
Why this is correct
Increasing timeout reduces failures, and configuring a backup bucket prevents data loss.
- ✗
Enable Amazon CloudWatch Logs for the Lambda function to capture errors and store failed records in CloudWatch
Why it's wrong here
CloudWatch Logs captures logs but is not designed for storing failed records.
- ✗
Configure the Lambda function to write failed records to an Amazon SQS queue for later reprocessing
Why it's wrong here
Lambda transformation in Firehose cannot directly write to SQS; Firehose manages failure handling.
- ✗
Modify the Lambda function to store failed records in Amazon S3 before processing
Why it's wrong here
Lambda does not store data; Firehose manages the flow.
Visual reference
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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