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MLS-C01 Data Engineering Practice Question

A company is building a real-time anomaly detection system for network traffic logs. The logs are ingested via Amazon Kinesis Data Streams and processed with an Amazon SageMaker endpoint for inference. The team needs to ensure that the inference results are stored durably and can be replayed for model retraining. The system must handle at least 10,000 records per second with low latency. Which three AWS services should the team use to build this architecture? (Select THREE.)

⚠ Common exam trap

Watch out — candidates often confuse Kinesis Data Firehose with Kinesis Data Streams, assuming Firehose's simplicity and S3 integration make it suitable for real-time inference, but Firehose lacks the record-level replay and low-latency processing required for this use case.

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

Amazon Kinesis Data Streams

Amazon Kinesis Data Streams is the correct ingestion layer because it provides durable, real-time data streaming with the ability to handle over 10,000 records per second. It acts as the source of truth for network traffic logs, enabling low-latency processing and replay for model retraining.

Answer analysis

Option-by-option breakdown

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

  • AWS Glue ETL

    Why it's wrong here

    Glue ETL is designed for batch processing, not real-time streaming.

  • Amazon Kinesis Data Streams

    Why this is correct

    Kinesis Data Streams provides the ingestion layer with low latency and high throughput.

  • Amazon Kinesis Data Analytics for Apache Flink

    Why this is correct

    Kinesis Data Analytics can process streaming data in real time with Flink and invoke SageMaker endpoints.

  • Amazon Kinesis Data Firehose

    Why it's wrong here

    Firehose delivers data in batches, introducing latency and not suitable for real-time inference.

  • Amazon SageMaker

    Why this is correct

    SageMaker hosts the anomaly detection model for real-time inference.

About these practice questions

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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.