Courseiva
Data EngineeringmediumMultiple ChoiceObjective-mapped

MLS-C01 Data Engineering Practice Question

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?

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

Increase the number of shards in the Kinesis data stream.

Increase the number of shards in the Kinesis data stream. Each shard supports a fixed number of read transactions per second and a maximum data read rate. Increasing the number of shards increases the parallelism of the stream, allowing the Lambda function to process records from multiple shards concurrently, thus increasing throughput. Option A is incorrect because adding a second stream would require duplicating data and does not address the throttling on the existing stream. Option B is incorrect because increasing the batch size may reduce the number of Lambda invocations but does not increase the parallelism of the stream; the bottleneck is the shard count. Option D is incorrect because increasing reserved concurrency does not overcome the limitation that each shard can only trigger one Lambda invocation at a time; the main constraint is the number of shards.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Add a second Kinesis data stream and send duplicate records to both.

    Why it's wrong here

    Duplicating data is inefficient and not a best practice.

  • Increase the batch size in the event source mapping for Lambda.

    Why it's wrong here

    Larger batch size can improve efficiency but shard count is the limiting factor.

  • Increase the number of shards in the Kinesis data stream.

    Why this is correct

    More shards increase the stream's capacity and number of Lambda consumers.

  • Increase the reserved concurrency of the Lambda function.

    Why it's wrong here

    Reserved concurrency prevents throttling but does not increase stream throughput.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

About these practice questions

This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.