DEA-C01 Data Ingestion and Transformation Practice Question

A data engineer is troubleshooting a Kinesis Data Firehose delivery stream that ingests JSON log data from web servers. The stream is configured to transform records with an AWS Lambda function and deliver to an Amazon S3 bucket. Recently, the stream has been failing with 'InvalidData' errors. Which action should the engineer take to resolve the issue?

⚠ Common exam trap

Test-takers frequently confuse 'InvalidData' errors with S3 permission issues or buffer configuration problems, but the error specifically points to a failure in the data transformation step, not the delivery destination or batching settings.

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

✓

Check the CloudWatch Logs for the Lambda function to identify transformation errors.

The 'InvalidData' error in Kinesis Data Firehose typically indicates that the Lambda function used for data transformation is failing or returning malformed records. By checking the CloudWatch Logs for the Lambda function, the engineer can identify specific transformation errors, such as incorrect JSON parsing, missing fields, or exceptions, which cause Firehose to reject the records. This is the most direct troubleshooting step because Firehose relies on the Lambda function to return valid transformed data in the expected format.

Answer analysis

Option-by-option breakdown

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

✗
Verify the S3 bucket policy allows Firehose to write.
Why it's wrong here
InvalidData errors originate from Lambda transformation output that Firehose cannot parse or from malformed source records, not from permissions; a denied write surfaces as an access or delivery error instead. Bucket policies matter when Firehose returns AccessDenied during S3 delivery.
✗
Increase the buffer size and interval in the Firehose delivery stream.
Why it's wrong here
Buffer size and interval govern how long records are buffered before delivery; they do not alter record parsing, so malformed JSON still triggers InvalidData. Tuning buffers suits throughput or latency optimisation, not data-format failures. The Lambda transformation's output format or error handling must be corrected instead.
✗
Change the data format to CSV in the Firehose configuration.
Why it's wrong here
Changing the Firehose destination format to CSV does not fix malformed incoming JSON; Firehose validates source records before transformation, so InvalidData persists. Format conversion suits downstream analytics needs, not ingestion errors. The Lambda function's parsing or the source record structure must be corrected.
✓
Check the CloudWatch Logs for the Lambda function to identify transformation errors.
Why this is correct
Firehose returns InvalidData when the Lambda transform function throws an error or returns a malformed record. Inspecting the function's CloudWatch Logs reveals the exact transformation exception, letting the engineer correct the code rather than guessing at stream configuration.

Visual reference

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

Go deeper

DEA-C01 Data Ingestion and Transformation Practice Question

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

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