DEA-C01 Data Ingestion and Transformation Practice Question
A company streams clickstream data from websites to Amazon Kinesis Data Streams. A Lambda function processes each record and writes it to Amazon S3. Recently, the function has been timing out under high load. Which solution should a data engineer implement to handle the increased throughput?
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 number of shards in the Kinesis data stream.
Increasing the number of shards in the Kinesis data stream increases the level of parallelism. Each shard can be processed by a separate Lambda invocation, allowing more concurrent processing of records. This directly addresses the high load and timeout issue. Option A is incorrect because increasing the timeout does not increase throughput; it only allows the function to run longer, but under high load it will still timeout. Option C is incorrect because increasing memory may improve performance per invocation but does not increase the number of concurrent invocations; the bottleneck is limited by the number of shards. Option D is incorrect because S3 Event Notifications are for object creation events in S3, not for real-time streaming; they do not help with Kinesis ingestion.
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's timeout value.
Why it's wrong here
Timeout increase does not solve the throughput bottleneck from limited shards.
- ✓
Increase the number of shards in the Kinesis data stream.
Why this is correct
More shards increase parallelism and allow Lambda to process more records concurrently.
- ✗
Increase the memory allocated to the Lambda function.
Why it's wrong here
More memory can improve performance but does not increase parallelism from shards.
- ✗
Configure Amazon S3 Event Notifications to trigger Lambda directly.
Why it's wrong here
This does not help with processing Kinesis records; it's for S3 events.
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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Same concept, more angles
1 more way this is tested on DEA-C01
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Variation 1. A company uses Amazon Kinesis Data Streams to ingest clickstream data from a website. The data is then consumed by a custom application for real-time analytics. Recently, the application has been experiencing high latency. The operations team suspects the shard count is insufficient. How should the team increase the shard count of the existing stream?
easy- ✓ A.Use the UpdateShardCount API to increase the shard count for the stream.
- B.Delete the existing stream and create a new one with a higher shard count.
- C.Manually split a shard using the SplitShard API on each existing shard.
- D.Modify the PutRecord calls to include a new shard key that distributes data across more shards.
Why A: The UpdateShardCount API is the correct method to increase the shard count of an existing Kinesis Data Stream without data loss or downtime. It allows you to specify a target shard count, and Kinesis automatically splits shards to achieve that count, redistributing the hash key range across the new shards. This directly addresses the high latency caused by insufficient shard count by increasing the stream's throughput capacity.
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.