Quick Answer
The answer is that the Kinesis stream has too few shards for the data volume, as the ProvisionedThroughputExceededException directly signals that the write capacity of the existing shards has been overwhelmed. Each shard in Kinesis Data Streams supports a maximum of 1 MB per second or 1,000 records per second for writes, so when the clickstream data ingestion rate exceeds this limit, the Lambda consumer fails with this error. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of Kinesis shard scaling as a core throughput management concept, often appearing in scenarios involving real-time data pipelines where Lambda is the consumer. A common trap is to assume the Lambda function itself is throttled or that the S3 bucket is the bottleneck, but the exception name explicitly points to the stream’s write capacity. Remember the mnemonic: “Shards shield throughput”—if you see ProvisionedThroughputExceededException, think shard count first.
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 company is using Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Lambda function that writes to an S3 bucket. Recently, the Lambda function started failing with 'ProvisionedThroughputExceededException' errors. What is the MOST likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
The data retention period of the stream is too short.
Why wrong: Retention period does not affect throughput.
The S3 bucket has insufficient write capacity.
Why wrong: S3 scales automatically.
The Kinesis stream has too few shards for the data volume.
Insufficient shards cause ProvisionedThroughputExceededException.
The Lambda function's reserved concurrency is set too high.
Why wrong: High concurrency would not cause throttling.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
The Kinesis stream has too few shards for the data volume.
The 'ProvisionedThroughputExceededException' error in Amazon Kinesis Data Streams indicates that the data ingestion rate exceeds the write capacity of the stream's shards. Each shard supports up to 1 MB/s or 1,000 records/s for writes. If the clickstream data volume surpasses this limit, the Lambda function, which reads from the stream, will encounter this exception. Increasing the number of shards scales the write capacity to match the data volume.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
The data retention period of the stream is too short.
Why it's wrong here
Retention period does not affect throughput.
The S3 bucket has insufficient write capacity.
Why it's wrong here
S3 scales automatically.
The Kinesis stream has too few shards for the data volume.
Why this is correct
Insufficient shards cause ProvisionedThroughputExceededException.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
The Lambda function's reserved concurrency is set too high.
Why it's wrong here
High concurrency would not cause throttling.
Common exam traps
The trap here is that candidates confuse Kinesis throughput limits with Lambda concurrency or S3 capacity, but the specific exception name 'ProvisionedThroughputExceededException' is a direct indicator of insufficient shard write capacity in Kinesis.
Detailed technical explanation
Under the hood, each Kinesis shard has a fixed write capacity of 1 MB/s and 1,000 records/s. When the combined write rate from producers exceeds this, the stream returns a ProvisionedThroughputExceededException to the consumer (Lambda). The Lambda function reads from the stream via the Kinesis Data Streams API, which enforces these limits. In real-world scenarios, a sudden spike in clickstream traffic (e.g., during a flash sale) can overwhelm an undersharded stream, requiring a shard split or auto-scaling via AWS Application Auto Scaling.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
The correct answer is: The Kinesis stream has too few shards for the data volume. — The 'ProvisionedThroughputExceededException' error in Amazon Kinesis Data Streams indicates that the data ingestion rate exceeds the write capacity of the stream's shards. Each shard supports up to 1 MB/s or 1,000 records/s for writes. If the clickstream data volume surpasses this limit, the Lambda function, which reads from the stream, will encounter this exception. Increasing the number of shards scales the write capacity to match the data volume.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Read the scenario before looking for a memorised answer.
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Same concept, more angles
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 is using Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Kinesis Data Analytics application that runs SQL queries. The application has been failing intermittently with 'ProvisionedThroughputExceededException' errors. Which action should be taken to resolve this issue?
mediumWhy D: The error indicates that the shard's read throughput limit (5 transactions/second per shard) is being exceeded. Increasing the number of shards increases the total throughput. Option A (increase shard count) is the correct solution. Option B (increase record size) could worsen the problem. Option C (use Kinesis Firehose) changes the architecture but does not address the shard throughput. Option D (disable error logging) does not solve the underlying issue.
Variation 2. A company uses Amazon Kinesis Data Streams for real-time clickstream analysis. The data is consumed by a Lambda function that enriches the records and stores them in Amazon S3. Recently, the Lambda function has been failing with throttling errors, and the consumer is falling behind. The team needs to increase the throughput of the consumer without changing the data format or the Lambda function code. What should the team do?
mediumWhy C: Option A is correct because increasing the number of shards increases the parallelism of the stream, allowing more Lambda invocations in parallel. Option B is wrong because increasing Lambda concurrency limits may help but the bottleneck is the stream's throughput. Option C is wrong because changing the batch size may help but not as effectively as increasing shards. Option D is wrong because adding a second stream would require splitting the data, which is not a direct solution.
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Last reviewed: Jun 11, 2026
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