Which solution will meet these requirements with the LEAST implementation effort?
Create an Amazon Timestream database to keep a list of affiliated partners. Implement an AWS Lambda function to read the list. Configure the Lambda function to send user IDs to each partner when the company gives users points.
Create an Amazon Simple Notification Service (Amazon SNS) topic. Choose an endpoint protocol. Subscribe the partners to the topic. Publish user IDs to the topic when the company gives users points.
Create an AWS Step Functions state machine. Create a task for every affiliated partner. Invoke the state machine with user IDs as input when the company gives users points.
Create a data stream in Amazon Kinesis Data Streams. Implement producer and consumer applications. Store a list of affiliated partners in the data stream. Send user IDs when the company gives users points.
Explanations:
Amazon Timestream is mainly for time-series data. Lambda would require looping over each partner, which is not scalable as the number of partners grows.
Amazon SNS allows easy, scalable subscription of multiple partners. Each partner can subscribe via an HTTP endpoint to receive notifications whenever user IDs are published to the topic.
AWS Step Functions is designed for workflow orchestration, not ideal for dynamically adding new partners and broadcasting to them.
Amazon Kinesis Data Streams is suitable for real-time streaming but would require additional complexity for managing partner endpoints and ensuring each partner receives notifications.
I plot that the answer is:
Create an Amazon Simple Notification Service (Amazon SNS) topic. Choose an endpoint protocol. Subscribe the partners to the topic. Publish user IDs to the topic when the company gives users points.