DEA-C01 Data Operations and Support Practice Question
A company uses Amazon Kinesis Data Streams to ingest clickstream data. The data is consumed by a custom consumer application that writes to Amazon S3 every 5 minutes. The consumer is falling behind and processing lag is increasing. Which action is MOST effective to reduce the lag?
⚠ Common exam trap
Test-takers frequently confuse throughput scaling with batch size or delivery destination changes, but the only way to increase read throughput from a Kinesis stream is to increase the number of shards or use enhanced fan-out.
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 stream
The consumer is falling behind because the stream's throughput capacity is insufficient for the incoming data volume. Increasing the number of shards in the Kinesis stream directly increases the total read capacity (each shard provides 2 MB/s read throughput and 5 transactions/second), allowing the consumer to process more data in parallel and reduce lag.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to Amazon Kinesis Data Firehose to deliver data directly to S3
Why it's wrong here
Firehose is a different service; rewriting the consumer would cause delay.
- ✗
Increase the batch size of records written to S3
Why it's wrong here
Larger batches can improve throughput but the consumer may still be limited by shard capacity.
- ✓
Increase the number of shards in the Kinesis stream
Why this is correct
More shards increase parallelism and throughput, allowing the consumer to keep up.
- ✗
Reduce the retention period of the stream
Why it's wrong here
Reducing retention only drops old data; it does not help the consumer process faster.
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
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses Amazon Kinesis Data Streams to ingest clickstream data from web applications. The data is consumed by a Kinesis Data Analytics application that runs SQL queries. Recently, the data analytics application has been falling behind, and the 'MillisBehindLatest' metric for the consumer has been increasing steadily. The shard count is 4, and the average records per second per shard is 200, with an average record size of 1 KB. The provisioned shard limit for the account is 10. Which action will resolve the issue?
medium- A.Enable enhanced fan-out on the Kinesis stream and subscribe the analytics application to it.
- B.Reduce the checkpoint interval on the Kinesis Client Library (KCL) consumer to commit offsets more frequently.
- ✓ C.Increase the number of shards in the Kinesis stream to 8.
- D.Increase the provisioned write capacity of the Kinesis stream by requesting a shard limit increase.
Why C: The consumer is falling behind due to insufficient read capacity. Increasing the number of shards increases the total read capacity and allows the consumer to keep up. Option A is wrong because the write capacity is not the issue; the consumer is behind. Option B is wrong because switching to enhanced fan-out does not address the shard count limitation; it improves dedicated throughput per consumer but the total throughput is still limited by shard count. Option D is wrong because the consumer is already using KCL, and the issue is not related to checkpointing.
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.