MLS-C01 Data Engineering Practice Question
A company needs to ingest real-time clickstream data from thousands of web servers into AWS for near-real-time analytics. The data volume varies and can spike during promotions. Which service should be used to capture and buffer the data before processing?
⚠ Common exam trap
A common pitfall is confusing the buffering capabilities of Kinesis Data Streams versus Kinesis Data Firehose. Candidates often choose Firehose because they think 'buffer' implies a simple staging area, but Firehose lacks the multi-consumer and replay capabilities required for near-real-time analytics.
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 choice because it is designed for real-time data ingestion and buffering of large streams of data, such as clickstream events from thousands of web servers. It provides durable, low-latency storage (up to 365 days retention) and supports multiple consumers for near-real-time analytics, making it ideal for handling variable and spiky data volumes during promotions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon SQS
Why it's wrong here
SQS is a message queue, not designed for streaming analytics. It's better for decoupling microservices.
- ✗
Amazon Kinesis Data Firehose
Why it's wrong here
Firehose is for near-real-time delivery to S3, Redshift, etc., but does not provide a buffer for processing streams.
- ✓
Amazon Kinesis Data Streams
Why this is correct
Kinesis Data Streams provides a durable buffer for real-time data, enabling multiple consumers.
- ✗
Amazon MQ
Why it's wrong here
Amazon MQ is a managed message broker, not optimized for high-throughput streaming.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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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.