DEA-C01 Data Operations and Support Practice Question
A data engineer maintains an Amazon Kinesis Data Firehose delivery stream that writes JSON records to Amazon S3 and then invokes an AWS Lambda function for transformation. The Lambda function occasionally times out, causing records to be delivered untransformed. The engineer must ensure failed records are captured for later reprocessing without blocking delivery. What should the engineer do?
⚠ Common exam trap
The trap here is assuming a Lambda dead-letter queue captures Kinesis Data Firehose transformation failures, when Firehose invokes the function synchronously and cannot consume from an SQS queue.
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
✓
Enable the Kinesis Data Firehose data transformation failure option to send failed records to a separate S3 bucket for later reprocessing.
Kinesis Data Firehose transformation supports a failure destination for records that the Lambda function cannot process. Enabling it sends failed records to a separate S3 bucket for later reprocessing while successful records continue to the primary destination. The other options either mask timeouts, change the destination without capturing failures, or use a dead-letter queue mechanism that does not apply to synchronous Firehose invocations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable the Kinesis Data Firehose data transformation failure option to send failed records to a separate S3 bucket for later reprocessing.
Why this is correct
Kinesis Data Firehose supports a processing configuration with a Lambda function and a failure destination for records that fail transformation. Enabling that option writes failed records to a designated S3 bucket so they can be reprocessed later, while successful records continue to the main destination. This meets the requirement without blocking delivery.
- ✗
Increase the Lambda function's timeout to 15 minutes and memory to 10 GB so transformations always complete.
Why it's wrong here
Raising timeout and memory may reduce timeouts but cannot guarantee they never occur, and it increases cost for every invocation. It also does not capture failed records for reprocessing, which is the explicit requirement. This addresses symptoms rather than providing a failure-capture mechanism.
- ✗
Configure the delivery stream to use Amazon Redshift as the destination and enable S3 backup for all records.
Why it's wrong here
Changing the destination to Redshift does not capture Lambda transformation failures; S3 backup copies delivered records but does not isolate failed transformations for reprocessing. This alters the architecture unnecessarily and still leaves failed records mixed with successful ones. It does not satisfy the failure-capture requirement.
- ✗
Attach a dead-letter queue to the Lambda function and configure Kinesis Data Firehose to read from that queue.
Why it's wrong here
A Lambda dead-letter queue captures asynchronous invocation failures, but Kinesis Data Firehose invokes the function synchronously for transformation, and Firehose cannot read from an SQS dead-letter queue. This mechanism does not apply to Firehose transformation failures. It would leave failed records uncaptured for reprocessing.
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
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.