easyMultiple Choice
MLA-C01 Practice Question: A data engineer needs to ingest streaming…
A data engineer needs to ingest streaming clickstream data from a website into an S3 data lake for ML training. The data arrives continuously and must be written to S3 in near real-time. Which AWS service is best suited for this task?
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 Firehose with S3 as destination
Amazon Kinesis Data Firehose is the most appropriate service for loading streaming data into S3 with minimal effort and near-real-time latency. It can buffer, transform, and compress data before delivery.
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 Lambda function writing to S3 on every click event
Why it's wrong here
Invoking Lambda per click event creates one small object per request, producing severe S3 request-rate and file-count problems instead of a managed continuous stream. It is tempting because Lambda is serverless and event-driven, and it fits low-volume event handling, not sustained high-throughput clickstream ingestion.
- ✗
Amazon Athena queries running on the website's source database
Why it's wrong here
Athena runs SQL queries over data already in S3 or Glue catalogues; it cannot capture live clickstream events or write them into the data lake. It is tempting because Athena is genuinely useful for querying and analysing clickstream data after ingestion, which is a different task from continuous collection.
- ✓
Amazon Kinesis Data Firehose with S3 as destination
Why this is correct
Kinesis Data Firehose buffers incoming records and delivers them continuously to S3, providing the near real-time ingestion the clickstream pipeline demands without managing consumers. Managed scaling and native S3 delivery satisfy the continuous-write constraint for ML training data.
- ✗
AWS Glue ETL job triggered by a cron job every 5 minutes
Why it's wrong here
A cron-triggered Glue job processes data in five-minute batches, so it cannot deliver the near real-time continuous writes the stem demands. It is tempting because Glue ETL is the standard tool for transforming and loading data into S3, and scheduled runs suit periodic batch pipelines rather than streaming 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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-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 MLA-C01 exam.