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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.

You are a data engineer at a fintech company. The company processes real-time stock market data from multiple exchanges. The data is ingested via Amazon Kinesis Data Streams with 50 shards. Each record is about 1 KB, and the ingestion rate is 5,000 records per second. The data is consumed by a Java application running on Amazon ECS that performs real-time analytics and stores results in Amazon DynamoDB. Recently, the application has been experiencing high latency, and some records are stuck in the shards for minutes before being consumed. The CloudWatch metrics show that the application's CPU utilization is low, but the iterator age is increasing. The application uses the Kinesis Client Library (KCL) with a single worker. What is the most likely cause and how should it be fixed?

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.

A
Increase the number of shards to 200 to provide more throughput.
Why wrong: The ingestion rate is low; more shards will not reduce iterator age if the consumer is the bottleneck.
B
Increase the CPU capacity of the ECS task by moving to a larger instance type.
Why wrong: CPU utilization is low, so CPU is not the bottleneck.
C
Move the destination from DynamoDB to Amazon RDS to reduce write latency.
Why wrong: The destination is not the bottleneck; the issue is processing capacity.
D
Scale the number of KCL workers to match the number of shards (e.g., 50 workers) to process shards in parallel.
A single worker can only process one shard at a time; with 50 shards, records in other shards wait. Multiple workers can process shards concurrently, reducing latency.

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

✓

Scale the number of KCL workers to match the number of shards (e.g., 50 workers) to process shards in parallel.

Option D is correct because a single KCL worker processes all shards sequentially, causing high iterator age with 50 shards. Scaling to 50 workers (one per shard) enables parallel processing, reducing latency. Option A is incorrect because 50 shards provide up to 50 MB/s write capacity, far exceeding the actual ~5 MB/s (5000 records/sec * 1 KB). Option B is incorrect because CPU utilization is low, indicating the bottleneck is not compute but parallelization. Option C is incorrect because DynamoDB write latency is not the issue; the problem is ingestion-side processing delay.

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.

✗
Increase the number of shards to 200 to provide more throughput.
Why it's wrong here
The ingestion rate is low; more shards will not reduce iterator age if the consumer is the bottleneck.
✗
Increase the CPU capacity of the ECS task by moving to a larger instance type.
Why it's wrong here
CPU utilization is low, so CPU is not the bottleneck.
✗
Move the destination from DynamoDB to Amazon RDS to reduce write latency.
Why it's wrong here
The destination is not the bottleneck; the issue is processing capacity.
✓
Scale the number of KCL workers to match the number of shards (e.g., 50 workers) to process shards in parallel.
Why this is correct
A single worker can only process one shard at a time; with 50 shards, records in other shards wait. Multiple workers can process shards concurrently, reducing latency.
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.

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

An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.

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: Scale the number of KCL workers to match the number of shards (e.g., 50 workers) to process shards in parallel. — Option D is correct because a single KCL worker processes all shards sequentially, causing high iterator age with 50 shards. Scaling to 50 workers (one per shard) enables parallel processing, reducing latency. Option A is incorrect because 50 shards provide up to 50 MB/s write capacity, far exceeding the actual ~5 MB/s (5000 records/sec * 1 KB). Option B is incorrect because CPU utilization is low, indicating the bottleneck is not compute but parallelization. Option C is incorrect because DynamoDB write latency is not the issue; the problem is ingestion-side processing delay.

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: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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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.