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Answer: Use AWS Lambda for data transformation within Kinesis Data Firehose, targeting the removal of customer identifiers, with S3 as the output destination.
The correct answer is A. AWS Lambda can be used for serverless data transformation within Kinesis Data Firehose. This approach allows the developer to implement a Lambda function that processes and removes customer identifiers from the streaming data. The Lambda function can then output the sanitized data to an Amazon S3 bucket, meeting the requirements efficiently and effectively. Other options, such as using EC2 instances, OpenSearch Service, or Step Functions, are not as optimal or straightforward for this specific use case.
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How can a developer process a Kinesis Data Firehose stream containing sensitive customer data by removing identifiable information and storing the sanitized data in an Amazon S3 bucket?
A
Use AWS Lambda for data transformation within Kinesis Data Firehose, targeting the removal of customer identifiers, with S3 as the output destination.
B
Deploy an EC2 instance to handle the stream, apply data cleansing operations to eliminate identifiers, and subsequently store the output in S3.
C
Utilize Amazon OpenSearch Service for the stream's destination, perform identifier removal through search and replace, then export cleaned data to S3.
D
Employ AWS Step Functions to manage identifier removal, with the sequence concluding in data storage within an S3 bucket, using the workflow as the stream's destination.
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