The answer is to increase the Lambda function’s reserved concurrency to 1000. This directly resolves the lambda throttling kinesis stream bottleneck because each of the 10 shards can trigger multiple concurrent Lambda invocations, and with a default batch size of 100, the required concurrency quickly exceeds the current limit of 100, causing throttles and retries. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of how Lambda’s reserved concurrency acts as a hard cap on parallel executions—a common trap is to blame DynamoDB write capacity, but the primary issue here is Lambda throttling, not the database. Remember that for a Kinesis stream, the number of concurrent Lambda invocations equals the number of shards multiplied by the number of batches processed in parallel, so always ensure reserved concurrency is set high enough to handle peak shard-level parallelism. Memory tip: “Shards scale concurrency—don’t let your reserved cap be the bottleneck.”
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. 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 engineering team is building a real-time fraud detection pipeline. The pipeline ingests transaction data from an Amazon Kinesis Data Stream with 10 shards. Each shard produces about 500 records per second, each record is 2 KB. The data is processed by a Lambda function that runs for about 200 ms and then writes results to an Amazon DynamoDB table. The team notices that the Lambda function is experiencing a high number of throttles, and there are increasing numbers of records being retried. The Lambda function's reserved concurrency is set to 100. The DynamoDB table has 100 read capacity units and 100 write capacity units. Which change would most effectively reduce throttling and improve processing throughput?
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 1000.
The Lambda function is throttling because the concurrent executions needed exceed the reserved concurrency. Each shard invokes Lambda with batches, and with 10 shards and a batch size of 100 (default), the number of concurrent invocations can be high. Increasing reserved concurrency to a higher value (e.g., 1000) allows more concurrent executions, reducing throttling. However, if DynamoDB write capacity is also a bottleneck, increasing it might help. But the primary issue is Lambda 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.
✗
Decrease the Lambda function's batch size to 10.
Why it's wrong here
Smaller batch size increases the number of invocations, exacerbating throttling.
✗
Increase the DynamoDB write capacity units to 1000.
Why it's wrong here
This might help if DynamoDB is throttling, but the immediate problem is Lambda throttling.
✗
Increase the number of shards in the Kinesis stream to 100.
Why it's wrong here
More shards increase the number of Lambda invocations, worsening throttling.
✓
Increase the Lambda function's reserved concurrency to 1000.
Why this is correct
More concurrency allows the function to handle more concurrent invocations.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Data Engineering — This question tests Data Engineering — 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 1000. — The Lambda function is throttling because the concurrent executions needed exceed the reserved concurrency. Each shard invokes Lambda with batches, and with 10 shards and a batch size of 100 (default), the number of concurrent invocations can be high. Increasing reserved concurrency to a higher value (e.g., 1000) allows more concurrent executions, reducing throttling. However, if DynamoDB write capacity is also a bottleneck, increasing it might help. But the primary issue is Lambda throttling.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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