- A
Amazon Kinesis Data Streams
Why wrong: Kinesis Data Streams is for real-time streaming with custom consumer applications — Firehose is the simpler managed delivery service to AWS destinations without writing consumers.
- B
Amazon Kinesis Data Firehose
Kinesis Data Firehose is the managed streaming delivery service that loads data into Redshift, S3, and OpenSearch automatically — including optional Lambda transformation, with no consumer code needed.
- C
AWS Glue
Why wrong: Glue handles ETL batch processing — Kinesis Data Firehose is designed for streaming, near-real-time delivery to data stores.
- D
Amazon MSK
Why wrong: MSK is a managed Kafka service for streaming — it still requires consumer applications to deliver data to Redshift, unlike Firehose which handles delivery automatically.
Quick Answer
Amazon Kinesis Data Firehose is the correct choice because it is a fully managed service purpose-built for streaming ETL delivery to Redshift, handling the capture, transformation, and automatic loading of streaming data into Redshift in near real-time without any ongoing administration. This service excels at ingesting high-volume log data from thousands of servers, applying transformations like converting to Parquet or invoking Lambda functions, and then seamlessly delivering the processed results directly into Redshift tables for dashboard analysis. On the AWS Certified Cloud Practitioner CLF-C02 exam, this question tests your understanding of managed streaming services versus batch-oriented alternatives like AWS Glue or manual data loading; a common trap is confusing Kinesis Data Firehose with Kinesis Data Streams, which requires custom consumers and is not a fully managed ETL pipeline. For a memory tip, think of Firehose as the "fire hose" that blasts streaming data directly into Redshift with zero setup fuss—if the question says "fully managed streaming ETL delivery to Redshift," the answer is always Firehose.
CLF-C02 Cloud Technology and Services Practice Question
This CLF-C02 practice question tests your understanding of cloud technology and services. 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 needs to process and analyze streaming log data from thousands of servers in near real-time, loading the results into Amazon Redshift for dashboards. Which AWS service is designed for this streaming ETL delivery use case?
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
Amazon Kinesis Data Firehose is the correct choice because it is a fully managed service designed specifically for streaming ETL (extract, transform, load) delivery. It can capture, transform (e.g., convert to Parquet/ORC, perform Lambda-based data transformation), and automatically load streaming data into Amazon Redshift, Amazon S3, or Amazon OpenSearch Service in near real-time, with no ongoing administration required.
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.
- ✗
Amazon Kinesis Data Streams
Why it's wrong here
Kinesis Data Streams is for real-time streaming with custom consumer applications — Firehose is the simpler managed delivery service to AWS destinations without writing consumers.
- ✓
Amazon Kinesis Data Firehose
Why this is correct
Kinesis Data Firehose is the managed streaming delivery service that loads data into Redshift, S3, and OpenSearch automatically — including optional Lambda transformation, with no consumer code needed.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Glue
Why it's wrong here
Glue handles ETL batch processing — Kinesis Data Firehose is designed for streaming, near-real-time delivery to data stores.
- ✗
Amazon MSK
Why it's wrong here
MSK is a managed Kafka service for streaming — it still requires consumer applications to deliver data to Redshift, unlike Firehose which handles delivery automatically.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Kinesis Data Streams (raw ingestion) with Kinesis Data Firehose (managed ETL delivery), assuming both can directly load into Redshift, but only Firehose provides the built-in COPY command integration and automatic transformation capabilities.
Detailed technical explanation
How to think about this question
Under the hood, Kinesis Data Firehose buffers incoming data to a configurable size (1 MB minimum) or interval (60 seconds minimum) before writing to the destination. When delivering to Redshift, Firehose first writes data to an intermediate S3 bucket, then issues a COPY command to load the data into the Redshift table, ensuring efficient bulk loading. A subtle behavior is that if transformation fails (e.g., Lambda error), Firehose can route failed records to a separate S3 bucket for reprocessing, preventing data loss.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 CLF-C02 question test?
Cloud Technology and Services — This question tests Cloud Technology and Services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon Kinesis Data Firehose — Amazon Kinesis Data Firehose is the correct choice because it is a fully managed service designed specifically for streaming ETL (extract, transform, load) delivery. It can capture, transform (e.g., convert to Parquet/ORC, perform Lambda-based data transformation), and automatically load streaming data into Amazon Redshift, Amazon S3, or Amazon OpenSearch Service in near real-time, with no ongoing administration required.
What should I do if I get this CLF-C02 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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 11, 2026
This CLF-C02 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 CLF-C02 exam.
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