MLS-C01 Data Engineering Practice Question
A data engineering team is building a real-time clickstream analytics pipeline on AWS. They need to ingest millions of events per second from mobile apps and websites, process them with low latency, and store the results in Amazon S3 for downstream analysis. Which combination of AWS services should the team use to minimize operational overhead while meeting these requirements?
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
✓
Use Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose to deliver results to Amazon S3.
Amazon Kinesis Data Streams scales to handle millions of events per second with low latency, Kinesis Data Analytics provides real-time processing without managing infrastructure, and Kinesis Data Firehose delivers processed data to Amazon S3 with automatic buffering and compression, minimizing operational overhead. Option A is wrong because Amazon MQ is a managed message broker for standard protocols (e.g., JMS) and does not offer the high-throughput, real-time streaming capabilities required for clickstream analytics. Option B is wrong because, while Kinesis Data Streams works for ingestion, using Amazon EMR with Spark Streaming adds operational overhead for cluster management and scaling, and is less suited for low-latency, serverless processing compared to Kinesis Data Analytics. Option D is wrong because AWS Glue is a batch ETL service, not designed for real-time ingestion, and Amazon RDS is a relational database that cannot handle the throughput and streaming nature of clickstream data; Glue cannot directly ingest streaming data into RDS in real time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Amazon MQ to ingest streaming data, AWS Lambda to process each message, and save output to Amazon S3.
Why it's wrong here
Amazon MQ is for message queuing, not high-throughput streaming; Lambda may have concurrency limits and is not ideal for millions of events per second.
- ✗
Use Amazon Kinesis Data Streams to ingest data, Amazon EMR to process with Spark Streaming, and save output to Amazon S3.
Why it's wrong here
EMR is a managed cluster solution; it adds operational overhead compared to serverless options.
- ✓
Use Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose to deliver results to Amazon S3.
Why this is correct
This combination provides serverless, low-latency ingestion, processing, and delivery with minimal operational overhead.
- ✗
Use AWS Glue to ingest data into Amazon RDS, then use AWS Glue ETL jobs to transform and load into Amazon S3.
Why it's wrong here
AWS Glue is a batch ETL service; not suitable for real-time ingestion and processing.
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.