DEA-C01 Data Ingestion and Transformation Practice Question
A company is using Amazon Kinesis Data Streams to ingest clickstream data from a website. The data is consumed by an AWS Lambda function that enriches records and writes to Amazon S3. The Lambda function is experiencing high error rates due to records exceeding the 256 KB payload limit. Which TWO actions should the team take to resolve this issue?
⚠ Common exam trap
Many candidates confuse increasing shards (which increases throughput) with reducing record size, or think that switching to Firehose bypasses the 256 KB limit, when in fact Firehose also has a per-record size limit and does not address the root cause.
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 compression on the producer side before sending records to Kinesis.
Enabling compression on the producer side reduces the size of each record before it is sent to Kinesis Data Streams, directly addressing the 256 KB payload limit. Option C is correct because the Kinesis Producer Library (KPL) aggregates multiple small records into a single larger record, which is then stored as one Kinesis record, reducing the number of records that exceed the limit and improving throughput.
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.
Why it's wrong here
Timeout does not affect record size; errors are due to payload size, not processing time.
- ✓
Enable compression on the producer side before sending records to Kinesis.
Why this is correct
Compression reduces record size below the 256 KB limit.
- ✓
Use the Kinesis Producer Library (KPL) to aggregate multiple small records into a single larger record.
Why this is correct
KPL aggregation packs small records into a single Kinesis record, reducing overhead.
- ✗
Switch from Kinesis Data Streams to Kinesis Data Firehose.
Why it's wrong here
Firehose has a 1 MB limit per record; still may not fit if records are large.
- ✗
Increase the number of shards in the Kinesis stream.
Why it's wrong here
More shards increase throughput but do not reduce record size.
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 |
Go deeper
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JA
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.