MLS-C01 Data Engineering Practice Question
A data engineering team needs to ingest streaming data from thousands of IoT devices into Amazon S3 for near-real-time analytics. The solution must handle data that arrives in bursts and must be able to reprocess failed records automatically. Which combination of AWS services should the team use?
⚠ Common exam trap
Test-takers frequently confuse SQS with Kinesis, but SQS lacks the ordered, replayable stream semantics and high-throughput shard scaling needed for bursty IoT data ingestion and reprocessing.
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 with AWS Lambda
Amazon Kinesis Data Streams is designed for real-time ingestion of large volumes of streaming data, such as from thousands of IoT devices, and can handle bursty traffic by scaling shards. AWS Lambda can be used as a consumer to process records in near-real-time, and Kinesis Data Streams supports automatic retries and checkpointing, enabling reprocessing of failed records without data loss.
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 with Amazon S3
Why it's wrong here
Glue is batch-oriented, not designed for real-time streaming ingestion.
- ✗
Amazon SQS with AWS Lambda
Why it's wrong here
SQS is message queue, not ideal for high-throughput streaming and lacks long retention for replay.
- ✓
Amazon Kinesis Data Streams with AWS Lambda
Why this is correct
Kinesis Data Streams can ingest bursty streaming data and retain it for replay; Lambda can process and load to S3.
- ✗
Amazon DynamoDB Streams with AWS Lambda
Why it's wrong here
DynamoDB Streams capture table changes, not direct IoT data ingestion.
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.