[{"data":1,"prerenderedAt":40},["ShallowReactive",2],{"repo-sns-xray-active-tracing-blog-source-code":3},{"id":4,"title":5,"contributors":6,"date":8,"description":9,"diagram":10,"extension":11,"framework":12,"gitHub":14,"introBox":17,"language":22,"meta":24,"resources":25,"services":28,"simplicity":35,"stem":36,"type":37,"usecase":38,"__hash__":39},"repos\u002Frepos\u002Fsns-xray-active-tracing-blog-source-code.json","Monitor SNS-based apps with AWS X-Ray Active Tracing",[7],"content\u002Fcontributors\u002Fdaniel-lorch.json","2023-05-11","Identify bottlenecks and monitor the health of event-driven applications.","\u002Fassets\u002Fimages\u002Frepos\u002Fsns-xray-active-tracing-blog-source-code.png","json",[13],"AWS SAM",{"template":15},{"repoURL":16},"https:\u002F\u002Fgithub.com\u002Faws-samples\u002Fsns-xray-active-tracing-blog-source-code",{"headline":18,"text":19},"This sample application demonstrates Amazon SNS with AWS X-Ray active tracing",[20,21],"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.","In this sample application, we demonstrate 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. We cover two architectural patterns which allow you to gain accurate visibility of your end-to-end tracing: SNS to SQS queues and SNS topics to Amazon Data Firehose streams.",[23],"Python",{},{"headline":26,"bullets":27},"Additional resources",[],[29,30,31,32,33,34],"apigw","dynamodb","lambda-event-functions","s3","sns","sqs","300","repos\u002Fsns-xray-active-tracing-blog-source-code","Examples","Observability","oBY8SO4GESSxnppl5d669lejMb4qf_WGFNZwAbKchBo",1792578865143]