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.
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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.