Quick Answer
The answer is AWS Glue and Amazon S3. AWS Glue is the correct serverless ETL service because it provides a fully managed, pay-per-execution environment that can directly read from Amazon RDS, transform the data, and write it to S3 in Parquet format without provisioning any underlying infrastructure. Amazon S3 serves as the cost-effective, durable destination for the transformed data. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of which services are truly serverless versus those that require management; a common trap is selecting AWS Lambda, which can trigger jobs but cannot run complex ETL transformations, or AWS Data Pipeline, which is not serverless. Remember the memory tip: “Glue connects and transforms, S3 stores and costs less.”
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 engineer needs to schedule a nightly ETL job that reads from an Amazon RDS database and writes to Amazon S3 in Parquet format. The solution must be serverless and minimize cost. Which TWO AWS services should be used? (Choose TWO.)
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
AWS Data Pipeline
Why wrong: Data Pipeline is not serverless; it runs on EC2 instances.
AWS Lambda
Why wrong: Lambda can trigger jobs but is not suitable for long-running ETL with large data volumes.
Amazon Athena
Why wrong: Athena is for querying data, not for transforming and writing it.
Amazon S3
S3 is the destination for the transformed data.
AWS Glue
Glue provides serverless Spark ETL jobs that can read from RDS and write to S3.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Amazon S3
AWS Glue can run serverless ETL jobs. Amazon S3 is the destination. Lambda could trigger but not run the ETL itself; Data Pipeline is not serverless; Athena is query-only.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
AWS Data Pipeline
Why it's wrong here
Data Pipeline is not serverless; it runs on EC2 instances.
AWS Lambda
Why it's wrong here
Lambda can trigger jobs but is not suitable for long-running ETL with large data volumes.
Amazon Athena
Why it's wrong here
Athena is for querying data, not for transforming and writing it.
Amazon S3
Why this is correct
S3 is the destination for the transformed data.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
AWS Glue
Why this is correct
Glue provides serverless Spark ETL jobs that can read from RDS and write to S3.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
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.
What to study next
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
Data Ingestion and Transformation — study guide chapter
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FAQ
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Static NAT maps one inside address to one outside address..
The correct answer is: Amazon S3 — AWS Glue can run serverless ETL jobs. Amazon S3 is the destination. Lambda could trigger but not run the ETL itself; Data Pipeline is not serverless; Athena is query-only.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 20, 2026
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