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Question 787 of 1,786

Data Ingestion and Transformation →hardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record. This approach directly handles Lambda enrichment failures in Kinesis Firehose by ensuring that a transient DynamoDB throttling issue does not cause the entire record to be rejected; instead, the failed enrichment is gracefully degraded by writing a null value, allowing the record to proceed to S3 without blocking other records in the batch. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of idempotent error handling within Lambda transformations for streaming pipelines—a common trap is assuming you need a dead-letter queue or separate stream, but Firehose’s Lambda integration expects the function to return a valid response for every record, even if enrichment fails. Remember the memory tip: “Catch, null, continue—don’t let one bad lookup sink the whole batch.”

DEA-C01 Data Ingestion and Transformation Practice Question

This DEA-C01 practice question tests your understanding of data ingestion and transformation. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 runs an e-commerce platform that generates clickstream data from user interactions on their website. The data is sent as JSON objects via HTTP POST to an API Gateway endpoint, which triggers a Lambda function that writes each record to a Kinesis Data Stream (100 shards). A second Lambda function consumes the stream, transforms the data (enriches with geolocation from a DynamoDB table), and writes to a Kinesis Data Firehose delivery stream that delivers Parquet files to an S3 data lake every 5 minutes. The system has been working for months, but recently the Firehose delivery stream started showing 'DeliveryFailed' errors for a subset of records. The errors point to 'InvalidData' from the Lambda transformation. The engineer reviews the Lambda transformation code and notices that the geolocation lookup occasionally fails because the DynamoDB table has a throttling issue. The engineer needs to handle these failures gracefully so that records that fail enrichment are still delivered to S3 with a null geolocation field, without blocking other records. Which course of action should the engineer take?

Question 1hardmultiple choice

Full question →

A
Configure the Kinesis Data Firehose delivery stream to send failed records to a dead-letter queue (DLQ) for later reprocessing.
Why wrong: Firehose does not support DLQ natively; it can send failed records to an S3 bucket for failed data, but the records would not be enriched.
B
Modify the Lambda function to send failed records to a separate Kinesis Data Stream for manual processing.
Why wrong: This adds complexity and does not solve the immediate need to deliver records with null geolocation.
C
Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record.
This ensures all records are delivered with a default value, maintaining pipeline throughput.
D
Increase the read capacity units (RCUs) on the DynamoDB table to eliminate throttling.
Why wrong: Eliminating throttling may not be possible and increases cost; failures can still occur due to other reasons.

Full breakdown with real-world context →

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

✓

Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record.

Option D is correct because modifying the Lambda to catch exceptions, set geolocation to null, and continue processing ensures that failed records are still delivered. Option A is wrong because configuring a dead-letter queue for Firehose is not directly supported; Firehose can send failed records to an S3 bucket for failed data, but that would not include the enriched data. Option B is wrong because increasing DynamoDB read capacity might reduce throttling but does not guarantee no failures; also it increases cost. Option C is wrong because sending failed records to a separate stream adds complexity and does not ensure they are delivered with null geolocation.

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

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Configure the Kinesis Data Firehose delivery stream to send failed records to a dead-letter queue (DLQ) for later reprocessing.
Why it's wrong here
Firehose does not support DLQ natively; it can send failed records to an S3 bucket for failed data, but the records would not be enriched.
✗
Modify the Lambda function to send failed records to a separate Kinesis Data Stream for manual processing.
Why it's wrong here
This adds complexity and does not solve the immediate need to deliver records with null geolocation.
✓
Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record.
Why this is correct
This ensures all records are delivered with a default value, maintaining pipeline throughput.
Related concept
Static NAT maps one inside address to one outside address.
✗
Increase the read capacity units (RCUs) on the DynamoDB table to eliminate throttling.
Why it's wrong here
Eliminating throttling may not be possible and increases cost; failures can still occur due to other reasons.

Common exam traps

Common exam trap: NAT rules depend on direction and matching traffic

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

How to think about this question

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.

KKey Concepts to Remember

Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

Identify inside and outside interfaces first.
Check whether the scenario needs static NAT, dynamic NAT or PAT.
Do not confuse NAT matching ACLs with normal packet-filtering intent.

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

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.

What to study next

Got this wrong? Here's your next step.

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.

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FAQ

Questions learners often ask

What does this DEA-C01 question test?

Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Static NAT maps one inside address to one outside address..

What is the correct answer to this question?

The correct answer is: Modify the Lambda function to catch exceptions during the geolocation lookup, set the geolocation field to null, and continue processing the record. — Option D is correct because modifying the Lambda to catch exceptions, set geolocation to null, and continue processing ensures that failed records are still delivered. Option A is wrong because configuring a dead-letter queue for Firehose is not directly supported; Firehose can send failed records to an S3 bucket for failed data, but that would not include the enriched data. Option B is wrong because increasing DynamoDB read capacity might reduce throttling but does not guarantee no failures; also it increases cost. Option C is wrong because sending failed records to a separate stream adds complexity and does not ensure they are delivered with null geolocation.

What should I do if I get this DEA-C01 question wrong?

What is the key concept behind this question?

Static NAT maps one inside address to one outside address.

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