← MLS-C01·Amazon Web Services

Question 158 of 1,755

Data Engineering →mediumMultiple ChoiceObjective-mapped

MLS-C01 Data Engineering 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. 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 clickstream analytics pipeline on AWS. They need to ingest millions of events per second from mobile apps and websites, process them with low latency, and store the results in Amazon S3 for downstream analysis. Which combination of AWS services should the team use to minimize operational overhead while meeting these requirements?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

Question 1mediummultiple choice

Read the full NAT/PAT explanation →

A
Use Amazon MQ to ingest streaming data, AWS Lambda to process each message, and save output to Amazon S3.
Why wrong: Amazon MQ is for message queuing, not high-throughput streaming; Lambda may have concurrency limits and is not ideal for millions of events per second.
B
Use Amazon Kinesis Data Streams to ingest data, Amazon EMR to process with Spark Streaming, and save output to Amazon S3.
Why wrong: EMR is a managed cluster solution; it adds operational overhead compared to serverless options.
C
Use Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose to deliver results to Amazon S3.
This combination provides serverless, low-latency ingestion, processing, and delivery with minimal operational overhead.
D
Use AWS Glue to ingest data into Amazon RDS, then use AWS Glue ETL jobs to transform and load into Amazon S3.
Why wrong: AWS Glue is a batch ETL service; not suitable for real-time ingestion and processing.

Full breakdown with real-world context →

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 Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose to deliver results to Amazon S3.

Option C is correct because Amazon Kinesis Data Streams can handle high-throughput ingestion, Kinesis Data Analytics processes streaming data with low latency, and Kinesis Data Firehose delivers processed data to S3 with minimal overhead. Option A is wrong because AWS Glue is a batch ETL service, not suitable for real-time processing. Option B is wrong because Amazon EMR is a managed Hadoop cluster that requires more operational overhead. Option D is wrong because Amazon MQ is a message broker for standard messaging protocols, not optimized for real-time analytics.

Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

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 MQ to ingest streaming data, AWS Lambda to process each message, and save output to Amazon S3.
Why it's wrong here
Amazon MQ is for message queuing, not high-throughput streaming; Lambda may have concurrency limits and is not ideal for millions of events per second.
✗
Use Amazon Kinesis Data Streams to ingest data, Amazon EMR to process with Spark Streaming, and save output to Amazon S3.
Why it's wrong here
EMR is a managed cluster solution; it adds operational overhead compared to serverless options.
✓
Use Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose to deliver results to Amazon S3.
Why this is correct
This combination provides serverless, low-latency ingestion, processing, and delivery with minimal operational overhead.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
✗
Use AWS Glue to ingest data into Amazon RDS, then use AWS Glue ETL jobs to transform and load into Amazon S3.
Why it's wrong here
AWS Glue is a batch ETL service; not suitable for real-time ingestion and processing.

Common exam traps

Common exam trap: NAT rules depend on direction and matching traffic

NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.

Detailed technical explanation

How to think about this question

NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.

KKey Concepts to Remember

Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

Identify inside and outside interfaces first.
Check whether the scenario needs static NAT, dynamic NAT or PAT.
Do not confuse NAT matching ACLs with normal packet-filtering intent.

Key takeaway

NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

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.

Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.

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.

10 questions 20 questions 30 questions 50 questions Timed 30

MLS-C01 practice-test guide →Study guide →Browse all practice tests

FAQ

Questions learners often ask

What does this MLS-C01 question test?

Data Engineering — This question tests Data Engineering — Static NAT maps one inside address to one outside address..

What is the correct answer to this question?

The correct answer is: Use Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose to deliver results to Amazon S3. — Option C is correct because Amazon Kinesis Data Streams can handle high-throughput ingestion, Kinesis Data Analytics processes streaming data with low latency, and Kinesis Data Firehose delivers processed data to S3 with minimal overhead. Option A is wrong because AWS Glue is a batch ETL service, not suitable for real-time processing. Option B is wrong because Amazon EMR is a managed Hadoop cluster that requires more operational overhead. Option D is wrong because Amazon MQ is a message broker for standard messaging protocols, not optimized for real-time analytics.

What should I do if I get this MLS-C01 question wrong?

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Static NAT maps one inside address to one outside address.

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 →

How Courseiva writes practice questions · Editorial policy

Keep practising

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.

Loading comments…

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.