What should a solutions architect do to meet these requirements?
Create an Amazon Connect contact flow to send the SMS messages. Use AWS Lambda to process the responses.
Build an Amazon Pinpoint journey. Configure Amazon Pinpoint to send events to an Amazon Kinesis data stream for analysis and archiving.
Use Amazon Simple Queue Service (Amazon SQS) to distribute the SMS messages. Use AWS Lambda to process the responses.
Create an Amazon Simple Notification Service (Amazon SNS) FIFO topic. Subscribe an Amazon Kinesis data stream to the SNS topic for analysis and archiving.
Explanations:
Amazon Connect is primarily designed for voice communications and contact center operations. While it can send SMS, it doesn’t inherently support the functionality for storing user responses effectively for long-term analysis.
Amazon Pinpoint is designed for targeted messaging and can handle SMS communication, including user replies. It can also track events and send them to Kinesis, allowing for storage and analysis of responses over time, meeting the one-year requirement.
Amazon SQS is designed for message queuing and doesn’t directly handle SMS communication or support storing responses. It lacks built-in functionality for SMS interaction, making it unsuitable for this use case.
Amazon SNS is primarily for sending notifications and does not provide a direct method for storing user responses. While it can trigger a Kinesis data stream, it doesn’t facilitate two-way SMS communication or long-term data retention.
I surmise that the answer is:
Build an Amazon Pinpoint journey. Configure Amazon Pinpoint to send events to an Amazon Kinesis data stream for analysis and archiving.