- A
Use AWS Glue ETL to read from the stream in micro-batches and write to S3
Why wrong: Glue ETL is batch-oriented and has higher latency; not ideal for real-time streaming.
- B
Use Kinesis Data Analytics for SQL transformations and then output to Firehose
Why wrong: Kinesis Data Analytics is more expensive and intended for real-time analytics, not simple transformations.
- C
Use Kinesis Data Firehose with AWS Lambda transformation
Firehose can transform data using a Lambda function before delivering to S3, cost-effective and fully managed.
- D
Use Kinesis Client Library (KCL) to consume the stream, transform, and write to S3
Why wrong: Running a custom consumer on EC2 is more expensive and requires management.
Question 460 of 1,000
hardMultiple ChoiceObjective-mapped
Cost-Effective Streaming Data Transformation with Kinesis Firehose and Lambda
This MLA-C01 practice question tests your understanding of mla-c01 exam topics. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses Amazon Kinesis Data Streams to ingest real-time user interactions and wants to store the data in Amazon S3 for historical analysis. They need to transform the data (e.g., add timestamps, filter records) before storage. Which approach is MOST cost-effective?
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 Kinesis Data Firehose with AWS Lambda transformation
Option C is the most cost-effective because Kinesis Data Firehose natively integrates with AWS Lambda for near-real-time, per-record transformations, and directly writes to S3 without requiring a separate compute resource to manage. This serverless approach minimizes operational overhead and cost compared to running continuous ETL jobs or managing a custom consumer application.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 AWS Glue ETL to read from the stream in micro-batches and write to S3
Why it's wrong here
Glue ETL is batch-oriented and has higher latency; not ideal for real-time streaming.
- ✗
Use Kinesis Data Analytics for SQL transformations and then output to Firehose
Why it's wrong here
Kinesis Data Analytics is more expensive and intended for real-time analytics, not simple transformations.
- ✓
Use Kinesis Data Firehose with AWS Lambda transformation
Why this is correct
Firehose can transform data using a Lambda function before delivering to S3, cost-effective and fully managed.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Kinesis Client Library (KCL) to consume the stream, transform, and write to S3
Why it's wrong here
Running a custom consumer on EC2 is more expensive and requires management.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often over-engineer the solution by choosing a more complex analytics or ETL service (like Kinesis Data Analytics or AWS Glue) when a simple, serverless Lambda transformation within Firehose is sufficient and more cost-effective for basic per-record transformations.
Detailed technical explanation
How to think about this question
Kinesis Data Firehose invokes a Lambda function synchronously for each batch of records (up to 3 MB or 60 seconds), allowing you to add timestamps, filter, or modify records before they are delivered to S3. The Lambda function must return the transformed records in the same order and with the same partition key structure, or Firehose will treat failed transformations as delivery failures. This pattern is ideal for lightweight, stateless transformations where you don't need to maintain state across records.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Use Kinesis Data Firehose with AWS Lambda transformation — Option C is the most cost-effective because Kinesis Data Firehose natively integrates with AWS Lambda for near-real-time, per-record transformations, and directly writes to S3 without requiring a separate compute resource to manage. This serverless approach minimizes operational overhead and cost compared to running continuous ETL jobs or managing a custom consumer application.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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