- A
Increase the Lambda function's reserved concurrency to 200.
More concurrency allows more parallel invocations to process records faster.
- B
Increase the number of Kinesis shards to 20.
More shards increase the stream's ingestion capacity and reduce IteratorAgeMilliseconds.
- C
Decrease the Lambda function's batch size from 100 to 50.
Why wrong: Smaller batch size means more invocations, increasing rate of API calls and potentially worsening rate limits.
- D
Enable S3 multipart upload for the Lambda function.
Why wrong: Multipart upload is for large objects, not for rate limiting issues; the problem is upstream of S3.
- E
Replace the Lambda function with Amazon Kinesis Data Firehose to write directly to S3.
Why wrong: This changes the architecture but does not address the immediate rate limiting; also, KDF has its own limits.
Quick Answer
The correct answer is to increase the Lambda function’s reserved concurrency to 200 and double the Kinesis shard count to 20. This resolves the “Rate exceeded” errors because each Kinesis shard supports up to 1 MB/s or 1,000 records per second for reads, and with 10 shards processing 15 MB/s, each shard handles roughly 1.5 MB/s—exceeding the per-shard throughput limit and causing Lambda to throttle. By increasing concurrency, you allow more parallel Lambda invocations to keep up with the stream’s data rate, while adding shards distributes the load across more parallel pipelines, directly reducing the elevated IteratorAgeMilliseconds. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of Kinesis shard limits and Lambda concurrency as a throttling bottleneck—a common trap is to only increase concurrency without adjusting shards, which still leaves per-shard throughput exceeded. Memory tip: “Shards for speed, concurrency for compute”—shards handle data volume, concurrency handles processing parallelism.
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 runs a data pipeline that ingests clickstream data from a web application into Amazon Kinesis Data Streams. A Lambda function processes records from the stream and writes them to an Amazon S3 bucket in JSON format. The pipeline has been running smoothly, but for the past hour, the Lambda function has been failing with 'Rate exceeded' errors, and the Kinesis stream shows elevated 'IteratorAgeMilliseconds' metrics. The Lambda function has a reserved concurrency of 100, and the Kinesis stream has 10 shards. The average record size is 5 KB, and the data rate is approximately 15 MB per second. Which combination of actions should a data engineer take to resolve the issue and prevent recurrence? (Choose TWO.)
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 Lambda function's reserved concurrency to 200.
The 'Rate exceeded' errors indicate that the Lambda function's concurrency is insufficient to keep up with the incoming data rate from Kinesis. With 10 shards and a 15 MB/s data rate, each shard processes ~1.5 MB/s, and with 5 KB records, that's ~300 records per second per shard. Increasing reserved concurrency to 200 allows more parallel invocations to handle the load, reducing the iterator age.
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 reserved concurrency to 200.
Why this is correct
More concurrency allows more parallel invocations to process records faster.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Increase the number of Kinesis shards to 20.
Why this is correct
More shards increase the stream's ingestion capacity and reduce IteratorAgeMilliseconds.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the Lambda function's batch size from 100 to 50.
Why it's wrong here
Smaller batch size means more invocations, increasing rate of API calls and potentially worsening rate limits.
- ✗
Enable S3 multipart upload for the Lambda function.
Why it's wrong here
Multipart upload is for large objects, not for rate limiting issues; the problem is upstream of S3.
- ✗
Replace the Lambda function with Amazon Kinesis Data Firehose to write directly to S3.
Why it's wrong here
This changes the architecture but does not address the immediate rate limiting; also, KDF has its own limits.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often focus only on Lambda concurrency (Option A) and overlook the Kinesis shard count (Option B), not realizing that both the consumer (Lambda) and the stream capacity must be scaled together to resolve throughput bottlenecks.
Detailed technical explanation
How to think about this question
Kinesis Data Streams uses shard-level parallelism: each shard can support up to 1 MB/s write and 2 MB/s read throughput. With 10 shards, the total read capacity is 20 MB/s, but the Lambda function's concurrency limit of 100 means only 100 invocations can run simultaneously, and each shard can trigger one Lambda invocation per batch. The 'IteratorAgeMilliseconds' metric measures how far behind the consumer is; increasing shards to 20 doubles the read capacity and allows more parallel processing, directly reducing the backlog.
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.
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 Lambda function's reserved concurrency to 200. — The 'Rate exceeded' errors indicate that the Lambda function's concurrency is insufficient to keep up with the incoming data rate from Kinesis. With 10 shards and a 15 MB/s data rate, each shard processes ~1.5 MB/s, and with 5 KB records, that's ~300 records per second per shard. Increasing reserved concurrency to 200 allows more parallel invocations to handle the load, reducing the iterator age.
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: Jun 11, 2026
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