- A
Switch to Amazon Kinesis Data Firehose to deliver data directly to S3
Why wrong: Firehose is a different service; rewriting the consumer would cause delay.
- B
Increase the batch size of records written to S3
Why wrong: Larger batches can improve throughput but the consumer may still be limited by shard capacity.
- C
Increase the number of shards in the Kinesis stream
More shards increase parallelism and throughput, allowing the consumer to keep up.
- D
Reduce the retention period of the stream
Why wrong: Reducing retention only drops old data; it does not help the consumer process faster.
Question 1,751 of 1,786
How to Reduce Kinesis Consumer Lag by Increasing Shards
This DEA-C01 practice question tests your understanding of data operations and support. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often 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.
Detailed technical explanation
How to think about this question
Each Kinesis shard supports up to 5 read transactions per second, with a maximum aggregate read rate of 2 MB/s. When a consumer falls behind, it indicates that the consumer's processing rate is slower than the write rate to the stream; adding shards increases the total read capacity, allowing the consumer to use enhanced fan-out or multiple workers to process records in parallel. In practice, you must also ensure the consumer application is designed to scale horizontally with the number of shards, using the Kinesis Client Library (KCL) which automatically distributes shards across workers.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
What to study next
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Operations and Support — This question tests Data Operations and Support — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Same concept, more angles
1 more ways 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: Option C is correct because 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.
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Last reviewed: Jun 11, 2026
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