- A
Enable compression on the Firehose delivery stream
Why wrong: Compression reduces storage but does not affect throttling.
- B
Increase the buffer size and buffer interval
Larger buffer reduces the number of write requests.
- C
Decrease the buffer size to flush more frequently
Why wrong: Smaller buffer increases calls, making throttling worse.
- D
Increase the number of shards in the Kinesis stream
Why wrong: Firehose does not use shards; this applies to Kinesis Data Streams.
Question 587 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 data pipeline uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The delivery occasionally fails with 'Firehose is throttled'. What should be done to reduce throttling?
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 buffer size and buffer interval
Option B is correct because increasing the buffer size and buffer interval gives Kinesis Data Firehose more time and data volume to accumulate before delivering to S3, reducing the frequency of PutRecord.Batch calls to the underlying Kinesis stream. This directly mitigates throttling by lowering the request rate, as Firehose throttling typically occurs when the per-shard write throughput limit (1,000 records/second or 1 MB/second) is exceeded.
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.
- ✗
Enable compression on the Firehose delivery stream
Why it's wrong here
Compression reduces storage but does not affect throttling.
- ✓
Increase the buffer size and buffer interval
Why this is correct
Larger buffer reduces the number of write requests.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the buffer size to flush more frequently
Why it's wrong here
Smaller buffer increases calls, making throttling worse.
- ✗
Increase the number of shards in the Kinesis stream
Why it's wrong here
Firehose does not use shards; this applies to Kinesis Data Streams.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The DEA-C01 exam often tests the misconception that Firehose throttling is resolved by scaling shards (like in Kinesis Data Streams), but Firehose manages its own internal shards and the correct fix is to adjust buffer settings to reduce API call frequency.
Detailed technical explanation
How to think about this question
Under the hood, Kinesis Data Firehose uses a single shard (or a fixed number) for its internal buffer, and throttling occurs when the aggregate write throughput exceeds 1 MB/second or 1,000 records/second per shard. Increasing buffer size (e.g., from 5 MB to 64 MB) and buffer interval (e.g., from 60 seconds to 300 seconds) reduces the number of PutRecord.Batch calls, allowing the stream to stay within its limits. In real-world scenarios, this is critical for high-volume pipelines where spikes in data ingestion can trigger throttling errors like 'Firehose is throttled'.
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the buffer size and buffer interval — Option B is correct because increasing the buffer size and buffer interval gives Kinesis Data Firehose more time and data volume to accumulate before delivering to S3, reducing the frequency of PutRecord.Batch calls to the underlying Kinesis stream. This directly mitigates throttling by lowering the request rate, as Firehose throttling typically occurs when the per-shard write throughput limit (1,000 records/second or 1 MB/second) is exceeded.
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.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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