- A
Amazon EMR
Why wrong: EMR runs managed Hadoop/Spark clusters for big data processing. Unlike Glue, EMR requires cluster configuration and is not serverless — you provision and manage the cluster.
- B
AWS Data Pipeline
Why wrong: Data Pipeline is an older AWS ETL orchestration service. AWS Glue is the modern, recommended serverless ETL service with built-in schema discovery and data cataloguing.
- C
AWS Glue
Glue is a serverless ETL service. The Glue Crawler discovers and catalogues schemas from S3 and databases automatically. Glue Jobs run Spark-based transformations serverlessly, loading results to Redshift without any server provisioning.
- D
Amazon Kinesis Data Firehose
Why wrong: Kinesis Firehose streams data in near-real time to destinations like S3 or Redshift. It performs simple transformations via Lambda but is not designed for complex ETL workflows with schema discovery.
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 data team needs to extract data from S3 and RDS, transform it (clean, enrich, join), and load it into Amazon Redshift for analytics. They want a serverless service that discovers and catalogues data schemas automatically and runs the ETL jobs without provisioning servers. Which AWS service provides this?
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
AWS Glue
AWS Glue is a fully managed, serverless ETL service that automatically discovers and catalogs data schemas using its Crawler feature, which populates the AWS Glue Data Catalog. It can extract data from S3 and RDS, transform it (clean, enrich, join), and load it into Amazon Redshift without any server provisioning or management.
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 EMR
Why it's wrong here
EMR runs managed Hadoop/Spark clusters for big data processing. Unlike Glue, EMR requires cluster configuration and is not serverless — you provision and manage the cluster.
- ✗
AWS Data Pipeline
Why it's wrong here
Data Pipeline is an older AWS ETL orchestration service. AWS Glue is the modern, recommended serverless ETL service with built-in schema discovery and data cataloguing.
- ✓
AWS Glue
Why this is correct
Glue is a serverless ETL service. The Glue Crawler discovers and catalogues schemas from S3 and databases automatically. Glue Jobs run Spark-based transformations serverlessly, loading results to Redshift without any server provisioning.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon Kinesis Data Firehose
Why it's wrong here
Kinesis Firehose streams data in near-real time to destinations like S3 or Redshift. It performs simple transformations via Lambda but is not designed for complex ETL workflows with schema discovery.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse AWS Glue with Amazon EMR because both can run Spark-based ETL, but EMR requires server provisioning and lacks automatic schema discovery, while Glue is fully serverless and includes the Data Catalog.
Detailed technical explanation
How to think about this question
AWS Glue uses Apache Spark under the hood to execute ETL jobs, and its Crawler connects to data stores (e.g., S3, RDS) using JDBC or S3 prefixes to infer schemas by sampling data and storing metadata in the Data Catalog. A real-world scenario is a data lake where Glue Crawlers automatically detect new partitions in S3 (e.g., daily logs) and update the catalog, enabling Redshift Spectrum or Athena queries without manual schema management.
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.
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.
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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: AWS Glue — AWS Glue is a fully managed, serverless ETL service that automatically discovers and catalogs data schemas using its Crawler feature, which populates the AWS Glue Data Catalog. It can extract data from S3 and RDS, transform it (clean, enrich, join), and load it into Amazon Redshift without any server provisioning or management.
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.
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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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