- A
Use Amazon MSK (Managed Streaming for Apache Kafka) and configure an MSK Connect S3 sink connector.
MSK is fully managed Kafka, and MSK Connect can stream data to S3 in Parquet format.
- B
Set up a Kinesis Data Firehose delivery stream that reads from Kafka and writes to S3.
Why wrong: Firehose cannot read directly from Kafka; it requires a Kinesis stream or other sources.
- C
Use AWS Glue ETL jobs to pull data from Kafka cluster periodically.
Why wrong: Glue ETL is batch-oriented and not designed for streaming ingestion.
- D
Create a Kinesis Data Analytics application to read from Kafka and write to S3.
Why wrong: Kinesis Data Analytics is for real-time analytics, not for direct data lake ingestion.
Quick Answer
The correct choice is Amazon MSK with MSK Connect and an S3 sink connector, because this fully managed solution directly ingests streaming Kafka data into an S3 data lake in Parquet format while partitioning by date and event type with minimal operational overhead. MSK Connect runs the sink connector as a worker within the managed Kafka cluster, handling schema conversion and partition assignment automatically, which eliminates the need for custom code or separate ingestion services. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of managed streaming ingestion patterns versus batch or analytics-focused services—a common trap is confusing Kinesis Data Firehose (which requires a Kinesis stream, not Kafka) or Glue ETL (which adds batch latency) with the direct Kafka-to-S3 path. Remember the memory tip: “MSK Connect sinks straight to S3, no Kinesis middleman needed.”
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 needs to set up a data pipeline that ingests streaming data from an Apache Kafka cluster running on Amazon EKS into an S3 data lake. The data must be stored in Parquet format, partitioned by date and event type. The team wants a fully managed solution with minimal operational overhead. Which solution should they choose?
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
Use Amazon MSK (Managed Streaming for Apache Kafka) and configure an MSK Connect S3 sink connector.
Option D is correct because Amazon MSK (Managed Streaming for Kafka) is a fully managed Kafka service, and MSK Connect with an S3 sink connector can deliver data directly to S3 in Parquet format. Option A (Kinesis Data Analytics) is for real-time analytics, not for data lake ingestion. Option B (Kinesis Data Firehose) works with Kinesis streams, not Kafka directly. Option C (Glue ETL) is batch-oriented and adds latency.
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.
- ✓
Use Amazon MSK (Managed Streaming for Apache Kafka) and configure an MSK Connect S3 sink connector.
Why this is correct
MSK is fully managed Kafka, and MSK Connect can stream data to S3 in Parquet format.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set up a Kinesis Data Firehose delivery stream that reads from Kafka and writes to S3.
Why it's wrong here
Firehose cannot read directly from Kafka; it requires a Kinesis stream or other sources.
- ✗
Use AWS Glue ETL jobs to pull data from Kafka cluster periodically.
Why it's wrong here
Glue ETL is batch-oriented and not designed for streaming ingestion.
- ✗
Create a Kinesis Data Analytics application to read from Kafka and write to S3.
Why it's wrong here
Kinesis Data Analytics is for real-time analytics, not for direct data lake ingestion.
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 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.
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.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
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: Use Amazon MSK (Managed Streaming for Apache Kafka) and configure an MSK Connect S3 sink connector. — Option D is correct because Amazon MSK (Managed Streaming for Kafka) is a fully managed Kafka service, and MSK Connect with an S3 sink connector can deliver data directly to S3 in Parquet format. Option A (Kinesis Data Analytics) is for real-time analytics, not for data lake ingestion. Option B (Kinesis Data Firehose) works with Kinesis streams, not Kafka directly. Option C (Glue ETL) is batch-oriented and adds latency.
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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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.
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