An Amazon Kinesis Data Firehose delivery stream receives records containing personally identifiable information. The data must have pattern-based customer identifiers removed before being stored in Amazon S3. What is the best way to implement this transformation?

The most effective method is to configure Firehose data transformation with an AWS Lambda function. Kinesis Data Firehose natively supports invoking a Lambda function to transform incoming records before delivery to the destination. This allows for custom logic, such as pattern-based removal of PII, to be applied directly within the Firehose stream. The transformed data is then delivered to the S3 bucket. Using an EC2 instance as a Firehose destination introduces unnecessary operational overhead, management, and potential single points of failure. Amazon OpenSearch Service is primarily for search and analytics, not for data transformation and direct export to S3 in this manner. AWS Step Functions is an orchestration service; while it can perform transformations, it's not a direct destination for Firehose and would add complexity for this specific use case.