- A
Add a random prefix to the S3 object key to distribute writes across multiple prefixes
Random prefixes increase the number of S3 partitions, raising the PUT request limit.
- B
Switch to Amazon Kinesis Data Firehose to write to S3
Why wrong: Firehose can batch records and reduce PUT requests, but adding prefixes is a simpler fix.
- C
Increase the Lambda function's reserved concurrency
Why wrong: More concurrent Lambda invocations would increase the PUT request rate, making throttling worse.
- D
Increase the number of Kinesis shards
Why wrong: More shards increase parallelism but don't change the S3 rate limit issue.
Question 899 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 company uses Amazon Kinesis Data Streams to ingest IoT sensor data. The data is processed by an AWS Lambda function that transforms the records and writes to an Amazon S3 bucket. Recently, the Lambda function has been failing with 'Rate exceeded' errors for the S3 PUT API calls. The data volume is 10 MB/s with average record size 2 KB. What should be done to resolve this issue?
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
✓
Add a random prefix to the S3 object key to distribute writes across multiple prefixes
The 'Rate exceeded' error for S3 PUT API calls indicates that the Lambda function is hitting S3 request rate limits. S3 buckets have a default limit of 3,500 PUT requests per second per prefix. With a data volume of 10 MB/s and an average record size of 2 KB, the Lambda function is generating approximately 5,000 PUT requests per second (10 MB/s ÷ 2 KB), which exceeds the per-prefix limit. Adding a random prefix to the S3 object key distributes writes across multiple prefixes, effectively increasing the aggregate request rate limit to 3,500 PUT requests per second per prefix, thereby resolving the throttling issue.
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.
- ✓
Add a random prefix to the S3 object key to distribute writes across multiple prefixes
Why this is correct
Random prefixes increase the number of S3 partitions, raising the PUT request limit.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Switch to Amazon Kinesis Data Firehose to write to S3
Why it's wrong here
Firehose can batch records and reduce PUT requests, but adding prefixes is a simpler fix.
- ✗
Increase the Lambda function's reserved concurrency
Why it's wrong here
More concurrent Lambda invocations would increase the PUT request rate, making throttling worse.
- ✗
Increase the number of Kinesis shards
Why it's wrong here
More shards increase parallelism but don't change the S3 rate limit issue.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Kinesis shard scaling (Option D) or Lambda concurrency (Option C) with S3 rate limits, not realizing that the bottleneck is the S3 API request rate per prefix, not the data ingestion pipeline throughput.
Detailed technical explanation
How to think about this question
S3's request rate limits are per prefix (e.g., 's3://bucket/prefix/'), and the default limit is 3,500 PUT requests per second per prefix. By adding a random prefix (e.g., using a hash of the object key or a UUID), the writes are spread across multiple prefixes, each with its own 3,500 PUT/s limit, effectively allowing unlimited aggregate throughput. This is a common pattern for high-volume S3 ingestion, and AWS recommends using random prefixes for workloads exceeding 3,500 PUT/s.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
What to study next
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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: Add a random prefix to the S3 object key to distribute writes across multiple prefixes — The 'Rate exceeded' error for S3 PUT API calls indicates that the Lambda function is hitting S3 request rate limits. S3 buckets have a default limit of 3,500 PUT requests per second per prefix. With a data volume of 10 MB/s and an average record size of 2 KB, the Lambda function is generating approximately 5,000 PUT requests per second (10 MB/s ÷ 2 KB), which exceeds the per-prefix limit. Adding a random prefix to the S3 object key distributes writes across multiple prefixes, effectively increasing the aggregate request rate limit to 3,500 PUT requests per second per prefix, thereby resolving the throttling issue.
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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Last reviewed: Jul 4, 2026
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