- A
Increase the Lambda function's memory allocation.
Why wrong: Memory does not affect Kinesis throughput.
- B
Increase the number of shards in the Kinesis stream.
More shards increase throughput capacity.
- C
Enable enhanced fan-out for the stream.
Why wrong: Enhanced fan-out reduces latency, not throughput limits.
- D
Reduce the batch size in the Lambda event source mapping.
Why wrong: Would reduce processing rate.
Quick Answer
The correct action is to increase the number of shards in the Kinesis stream. This resolves the ProvisionedThroughputExceededException because each shard has a fixed read throughput limit of 2 MB per second or 5 read transactions per second, and when your Lambda consumer exceeds that per-shard capacity, the stream throttles requests. By adding more shards, you distribute the read load across additional parallel units, raising the total available read throughput for your Lambda function. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of Kinesis shard architecture and the relationship between shard count and throughput limits—a common trap is confusing write limits (1 MB/s per shard) with read limits, so always check which direction the error comes from. Remember the memory tip: “More shards, more cards” — each shard is like a lane on a highway; to handle more traffic, you add lanes, not widen the existing ones.
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. 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 Kinesis Data Streams to ingest real-time clickstream data. The data is processed by a Lambda function that writes to an S3 bucket. Recently, the Lambda function has been failing with 'ProvisionedThroughputExceededException' errors. Which action should be taken 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
Increase the number of shards in the Kinesis stream.
The 'ProvisionedThroughputExceededException' error indicates that the Lambda function is reading data from the Kinesis stream faster than the stream's shard-level throughput limits allow. Each shard in a Kinesis Data Stream supports up to 2 MB/s read throughput or 5 read transactions per second. Increasing the number of shards distributes the read load across more shards, raising the total available read throughput and resolving the throttling.
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.
- ✗
Increase the Lambda function's memory allocation.
Why it's wrong here
Memory does not affect Kinesis throughput.
- ✓
Increase the number of shards in the Kinesis stream.
Why this is correct
More shards increase throughput capacity.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Enable enhanced fan-out for the stream.
Why it's wrong here
Enhanced fan-out reduces latency, not throughput limits.
- ✗
Reduce the batch size in the Lambda event source mapping.
Why it's wrong here
Would reduce processing rate.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse ProvisionedThroughputExceededException (a read-side throttling error) with write-side throttling, leading them to choose options like reducing batch size or increasing memory, which do not address the shard-level read throughput limit.
Detailed technical explanation
How to think about this question
Under the hood, Kinesis Data Streams enforces a shard-level read quota of 5 transactions per second and a total data read rate of 2 MB/s per shard. The Lambda event source mapping uses the Kinesis Client Library (KCL) to poll shards, and when the combined read rate from all Lambda invocations on a shard exceeds these limits, the service throws ProvisionedThroughputExceededException. A real-world scenario is a sudden spike in clickstream data volume; adding shards horizontally scales the stream's read capacity, allowing the Lambda consumer to process more data without throttling.
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.
What to study next
Got this wrong? Here's your next step.
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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 'ProvisionedThroughputExceededException' error indicates that the Lambda function is reading data from the Kinesis stream faster than the stream's shard-level throughput limits allow. Each shard in a Kinesis Data Stream supports up to 2 MB/s read throughput or 5 read transactions per second. Increasing the number of shards distributes the read load across more shards, raising the total available read throughput and resolving the throttling.
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 AWS Kinesis Data Streams to ingest real-time data. The data engineer notices that the stream's 'WriteProvisionedThroughputExceeded' error occurs frequently during peaks. Which action should be taken to resolve this issue?
medium- ✓ A.Increase the number of shards in the stream.
- B.Modify the producer to use a different partition key.
- C.Compress the data before sending to the stream.
- D.Enable enhanced fan-out for consumers.
Why A: Increasing the number of shards increases the write capacity, directly addressing the throughput exceeded error. Option B is wrong because the error is not from the producer side. Option C is wrong because the error is about write throughput, not read. Option D is wrong because the error is not about data format.
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Last reviewed: Jun 24, 2026
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