A company needs real-time data ingestion: an API, streaming data transformation, and storage, with the LEAST operational overhead. Which solution meets these requirements?
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Correct answer: Configure an Amazon API Gateway API to send data to an Amazon Kinesis data stream. Create an Amazon Kinesis Data Firehose delivery stream that uses the Kinesis data stream as a data source. Use AWS Lambda functions to transform the data. Use the Kinesis Data Firehose delivery stream to send the data to Amazon S3..
Why this is the answer
The correct solution leverages Amazon API Gateway for the API, which is a fully managed service, eliminating the operational overhead of managing EC2 instances for the API. Data is then sent to Amazon Kinesis Data Streams for real-time ingestion. Kinesis Data Firehose is used for automated delivery to Amazon S3, and it can be configured to use a Kinesis Data Stream as a source. AWS Lambda functions provide serverless, scalable data transformation. This combination of fully managed and serverless services minimizes operational overhead while meeting all requirements. The incorrect options involve EC2 instances for the API, which introduces significant operational overhead for patching, scaling, and maintenance. AWS Glue is a powerful ETL service but is not typically used for real-time streaming ingestion directly from an API in this manner, nor is it the most efficient choice for real-time data transformation in this specific pipeline compared to Lambda with Firehose.
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