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Answer: Use a unified Amazon SNS topic with Amazon SQS queues subscribed to it, applying SNS message filtering to route messages to the correct queue based on quote type, and configure backend servers with individual SQS queues.
Option C is the best solution for the given requirements. It involves creating a single Amazon Simple Notification Service (SNS) topic with Amazon Simple Queue Service (SQS) queues subscribed to it. SNS message filtering can be configured to route messages to the appropriate SQS queue based on the quote type. Each backend application server will use its own SQS queue. This setup ensures that quotes are reliably delivered and separated by type, and it simplifies maintenance by using managed services (SNS and SQS) for message routing and processing.
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An AWS-based web application requires processing insurance quotes with the following criteria: quotes must be categorized by type, responded to within 24 hours, and must be reliable to avoid loss. The system should prioritize operational efficiency and minimal maintenance. Identify the optimal solution:
A
Utilize Amazon Kinesis data streams categorized by quote type, with the web app directing messages appropriately and backend servers using KCL to process their respective streams.
B
Implement AWS Lambda functions and corresponding Amazon SNS topics for each quote type, with the Lambda functions subscribed to the relevant SNS topics and the app publishing quote requests to the correct topics.
C
Use a unified Amazon SNS topic with Amazon SQS queues subscribed to it, applying SNS message filtering to route messages to the correct queue based on quote type, and configure backend servers with individual SQS queues.
D
Establish Amazon Kinesis Data Firehose delivery streams for each quote type, directing them to an Amazon OpenSearch Service cluster, with the application sending messages to the corresponding stream and backend servers searching and processing messages from OpenSearch Service.