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 used for voice communications and is not designed for sending SMS messages directly to users. While it can handle contact flows, it does not provide the SMS reply handling and storage capabilities required for analysis.
Amazon Pinpoint is designed for targeted communication with mobile app users, including SMS messaging. It allows for user replies and can integrate with Amazon Kinesis for real-time data processing and analysis, thus meeting the requirements for storing responses for a year.
Amazon SQS is a message queuing service that does not natively support SMS messaging. While it can be used for processing messages, it lacks the SMS capabilities and reply handling that are essential for this scenario.
Amazon SNS is used for sending notifications but does not support bidirectional communication or storing responses from SMS replies. Using SNS with a FIFO topic does not fulfill the requirement for capturing and analyzing user responses over time.
If I’m not mistaken, the answer is:
Build an Amazon Pinpoint journey. Configure Amazon Pinpoint to send events to an Amazon Kinesis data stream for analysis and archiving.
I outline 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.