Individual SQS queues and Lambda functions are set up for processing requests via various back-office services (customer notification, customer accounting, and others).An SNS topic serves as a fan-out for ride requests.An Amazon DynamoDB table serves as a store for rides.An AWS Lambda function processes ride requests.An Amazon API Gateway receives ride requests from users.This is how the sample serverless application works: The application uses a microservices architecture which implements asynchronous messaging for integrating independent systems. To demonstrate AWS X-Ray active tracing for SNS, we will use the Wild Rydes serverless application as shown in the following figure. Getting started with the sample serverless application We cover two architectural patterns which allow you to gain accurate visibility of your end-to-end tracing: SNS to Amazon Simple Queue Service (Amazon SQS) queues and SNS topics to Amazon Kinesis Data Firehose streams. This blog post reviews common use cases where AWS X-Ray active tracing enabled for SNS provides a consistent view of tracing data across AWS services in real-world scenarios. With AWS X-Ray active tracing enabled for SNS, you can identify bottlenecks and monitor the health of event-driven applications by looking at segment details for SNS topics, such as resource metadata, faults, errors, and message delivery latency for each subscriber. This post is written by Daniel Lorch, Senior Consultant and David Mbonu, Senior Solutions Architect.Īmazon Simple Notification Service (Amazon SNS), a messaging service that provides high-throughput, push-based, many-to-many messaging between distributed systems, microservices, and event-driven serverless applications, now supports active tracing with AWS X-Ray.
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