How should a solutions architect integrate the microservices?
Implement code in microservice 1 to send data to an Amazon S3 bucket. Use S3 event notifications to invoke microservice 2.
Implement code in microservice 1 to publish data to an Amazon SNS topic. Implement code in microservice 2 to subscribe to this topic.
Implement code in microservice 1 to send data to Amazon Kinesis Data Firehose. Implement code in microservice 2 to read from Kinesis Data Firehose.
Implement code in microservice 1 to send data to an Amazon SQS queue. Implement code in microservice 2 to process messages from the queue.
Explanations:
Amazon S3 is designed for storage, not for real-time data processing. While S3 event notifications can trigger actions, it is not ideal for processing data between microservices with low latency.
While Amazon SNS can be used for decoupling services, it is typically used for event notifications, not for guaranteed delivery and processing of messages in a way that microservices typically require.
Kinesis Data Firehose is designed for loading data to destinations like S3, Redshift, or Elasticsearch, not for enabling real-time processing between microservices. It’s not suited for direct communication between microservices.
Amazon SQS provides a reliable, scalable, and decoupled messaging system. Microservice 1 can send messages to SQS, and Microservice 2 can process these messages in a reliable manner, making it the best option for this scenario.