- A
Configure the Lambda function with a reserved concurrency of 1 and a batch size of 1 to process records sequentially.
Configuring the Lambda function with a reserved concurrency of 1 and a batch size of 1 ensures that only one instance processes one record at a time, maintaining order within a shard. While this helps with ordering, exactly-once processing requires additional idempotency logic.
- B
Use the Kinesis Producer Library (KPL) with a sequence number for each record.
Why wrong: The Kinesis Producer Library (KPL) is a producer-side tool that assigns sequence numbers, but it does not ensure exactly-once processing on the consumer side. The Lambda consumer must implement idempotency and track sequence numbers to achieve exactly-once delivery.
- C
Use Amazon SQS FIFO queues to decouple Kinesis and Lambda, ensuring ordering and exactly-once delivery.
Why wrong: Amazon SQS FIFO queues do not integrate directly with Kinesis Data Streams. Using them would not preserve the ordering from Kinesis and adds complexity without guaranteeing exactly-once.
- D
Enable S3 Event Notifications to trigger Lambda for each object.
Why wrong: S3 Event Notifications are asynchronous and do not provide ordering or exactly-once delivery guarantees. They are not suitable for processing streaming data in order.
- E
Use Kinesis Data Firehose to buffer and deliver data to S3, then use Lambda to process.
Why wrong: Kinesis Data Firehose buffers and delivers data to S3 but does not guarantee exactly-once delivery; it may produce duplicates. It also does not provide granular per-record ordering.
MLS-C01 Exactly-once processing Practice Question
This MLS-C01 practice question tests your understanding of data engineering. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. A key principle to apply: exactly-once processing. 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 engineer is building a data pipeline that ingests streaming data from Amazon Kinesis Data Streams, transforms the data using AWS Lambda, and stores the results in Amazon S3. The engineer needs to ensure that each record is processed exactly once and in order. Which TWO approaches should the engineer consider? (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
Configure the Lambda function with a reserved concurrency of 1 and a batch size of 1 to process records sequentially.
To achieve exactly-once processing and ordering from Kinesis Data Streams with Lambda, option A helps maintain order but does not guarantee exactly-once on its own; however, it is the only listed approach that addresses ordering. Option B is incorrect because the Kinesis Producer Library (KPL) is a producer-side tool; while it assigns sequence numbers, the consumer must implement idempotency using those sequence numbers to achieve exactly-once processing. The question asks for approaches to ensure exactly-once and ordering, but among the choices, only option A is partially valid for ordering. Option C is incorrect because SQS FIFO queues do not integrate directly with Kinesis Data Streams and would not preserve Kinesis ordering. Option D is incorrect because S3 Event Notifications are asynchronous and do not provide ordering or exactly-once. Option E is incorrect because Kinesis Data Firehose may deliver duplicates and does not guarantee exactly-once.
Key principle: Exactly-once processing
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure the Lambda function with a reserved concurrency of 1 and a batch size of 1 to process records sequentially.
Why this is correct
Configuring the Lambda function with a reserved concurrency of 1 and a batch size of 1 ensures that only one instance processes one record at a time, maintaining order within a shard. While this helps with ordering, exactly-once processing requires additional idempotency logic.
Related concept
Exactly-once processing
- ✗
Use the Kinesis Producer Library (KPL) with a sequence number for each record.
Why it's wrong here
The Kinesis Producer Library (KPL) is a producer-side tool that assigns sequence numbers, but it does not ensure exactly-once processing on the consumer side. The Lambda consumer must implement idempotency and track sequence numbers to achieve exactly-once delivery.
- ✗
Use Amazon SQS FIFO queues to decouple Kinesis and Lambda, ensuring ordering and exactly-once delivery.
Why it's wrong here
Amazon SQS FIFO queues do not integrate directly with Kinesis Data Streams. Using them would not preserve the ordering from Kinesis and adds complexity without guaranteeing exactly-once.
- ✗
Enable S3 Event Notifications to trigger Lambda for each object.
Why it's wrong here
S3 Event Notifications are asynchronous and do not provide ordering or exactly-once delivery guarantees. They are not suitable for processing streaming data in order.
- ✗
Use Kinesis Data Firehose to buffer and deliver data to S3, then use Lambda to process.
Why it's wrong here
Kinesis Data Firehose buffers and delivers data to S3 but does not guarantee exactly-once delivery; it may produce duplicates. It also does not provide granular per-record ordering.
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
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Exactly-once processing
- Kinesis Shard Ordering
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
Exactly-once processing
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.
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
Got this wrong? Here's your next step.
Review exactly-once processing, then practise related MLS-C01 questions on the same topic to reinforce the concept.
- →
Data Engineering — study guide chapter
Learn the concepts, then practise the questions
- →
Data Engineering practice questions
Targeted practice on this topic area only
- →
All MLS-C01 questions
1,755 questions across all exam domains
- →
AWS Certified Machine Learning Specialty MLS-C01 study guide
Full concept coverage aligned to exam objectives
- →
MLS-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related MLS-C01 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Data Engineering practice questions
Practise MLS-C01 questions linked to Data Engineering.
Machine Learning Implementation and Operations practice questions
Practise MLS-C01 questions linked to Machine Learning Implementation and Operations.
Modeling practice questions
Practise MLS-C01 questions linked to Modeling.
Exploratory Data Analysis practice questions
Practise MLS-C01 questions linked to Exploratory Data Analysis.
MLS-C01 fundamentals practice questions
Practise MLS-C01 questions linked to MLS-C01 fundamentals.
MLS-C01 scenario practice questions
Practise MLS-C01 questions linked to MLS-C01 scenario.
MLS-C01 troubleshooting practice questions
Practise MLS-C01 questions linked to MLS-C01 troubleshooting.
Practice this exam
Start a free MLS-C01 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this MLS-C01 question test?
Data Engineering — This question tests Data Engineering — Exactly-once processing.
What is the correct answer to this question?
The correct answer is: Configure the Lambda function with a reserved concurrency of 1 and a batch size of 1 to process records sequentially. — To achieve exactly-once processing and ordering from Kinesis Data Streams with Lambda, option A helps maintain order but does not guarantee exactly-once on its own; however, it is the only listed approach that addresses ordering. Option B is incorrect because the Kinesis Producer Library (KPL) is a producer-side tool; while it assigns sequence numbers, the consumer must implement idempotency using those sequence numbers to achieve exactly-once processing. The question asks for approaches to ensure exactly-once and ordering, but among the choices, only option A is partially valid for ordering. Option C is incorrect because SQS FIFO queues do not integrate directly with Kinesis Data Streams and would not preserve Kinesis ordering. Option D is incorrect because S3 Event Notifications are asynchronous and do not provide ordering or exactly-once. Option E is incorrect because Kinesis Data Firehose may deliver duplicates and does not guarantee exactly-once.
What should I do if I get this MLS-C01 question wrong?
Review exactly-once processing, then practise related MLS-C01 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Exactly-once processing
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
More MLS-C01 practice questions
- A company needs to transfer 10 TB of data from an on-premises data center to Amazon S3. The network bandwidth is limited…
- A company is using Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Lambda fu…
- A team is building a data pipeline to process terabytes of log data daily using Amazon EMR. The data arrives in 5-minute…
- A data science team is building a real-time fraud detection system. Transactions are streamed via Amazon Kinesis Data St…
- A company uses Amazon SageMaker to train and deploy machine learning models. The training data is stored in Amazon S3 (P…
- A data engineering team is designing a data lake on AWS for machine learning workloads. The data includes structured, se…
Last reviewed: Jun 20, 2026
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.