[{"data":1,"prerenderedAt":566},["ShallowReactive",2],{"content-svc-lambda-guides-aws-lambda-operator-guide-trace-requests":3},{"markdown":4,"frontMatterAttributes":5,"bodyRaw":8,"menu":9,"menuType":563,"isCollapseableMenu":12,"nextDocItem":462,"previousDocItem":452,"contributorPaths":564,"contentName":565,"slug":461,"readingTime":58},"\u003Cp>While monitoring individual Lambda functions is useful, most serverless applications consist of multiple service integrations. Tracking performance problems or errors usually means following a transaction from the source caller through all the downstream services. While it’s possible to do this with each service’s logs, it’s faster and more convenient to use a tracing tool like AWS X-Ray.\u003C\u002Fp>\n\u003Cp>To use \u003Ca href=\"https:\u002F\u002Fdocs.aws.amazon.com\u002Flambda\u002Flatest\u002Fdg\u002Fservices-xray.html#services-xray-permissions\">X-Ray in Lambda\u003C\u002Fa>, you can activate it in the Lambda console for a selected function or enable the service in the AWS SAM template:\u003C\u002Fp>\n\u003Cpre>\u003Ccode class=\"language-yaml\">Resources:\n  GetLocations:\n    Type: AWS::Serverless::Function\n    Properties:\n      Tracing: Active\n\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>You must also provide permission, which can be granted using the \u003Ca href=\"https:\u002F\u002Fconsole.aws.amazon.com\u002Fiam\u002Fhome?#\u002Fpolicies\u002Farn:aws:iam::aws:policy\u002FAWSXRayDaemonWriteAccess$jsonEditor\">AWSXRayDaemonWriteAccess\u003C\u002Fa> managed policy. For each service in your workload, you must also activate X-Ray on the workload’s resources. Once enabled, X-Ray starts collecting tracing data for events. You can instrument calls via the AWS SDK by wrapping the object instantiation with the AWS X-Ray SDK. In Node.js:\u003C\u002Fp>\n\u003Cpre>\u003Ccode class=\"language-js\">    const AWSXRay = require('aws-xray-sdk-core')\n    const AWS = AWSXRay.captureAWS(require('aws-sdk'))\n\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>This provides additional subsegment granularity and generates additional information captured for calls to DynamoDB, S3, and SQS. By tracing a request from the API endpoint through to the Lambda function and resulting service interactions, you can isolate which part of the system is causing the most latency using the X-Ray service map. X-Ray tracing can be combined with load testing to identify bottlenecks and throttled or exhausted resources.\u003C\u002Fp>\n\u003Cp>To learn about configuring X-Ray for a serverless application, see \u003Ca href=\"https:\u002F\u002Fdocs.aws.amazon.com\u002Fxray\u002Flatest\u002Fdevguide\u002Fxray-services-lambda.html\">https:\u002F\u002Fdocs.aws.amazon.com\u002Fxray\u002Flatest\u002Fdevguide\u002Fxray-services-lambda.html\u003C\u002Fa>.\u003C\u002Fp>\n",{"title":6,"order":7},"Tracing requests with AWS X-Ray",73,"While monitoring individual Lambda functions is useful, most serverless applications consist of multiple service integrations. Tracking performance problems or errors usually means following a transaction from the source caller through all the downstream services. While it’s possible to do this with each service’s logs, it’s faster and more convenient to use a tracing tool like AWS X-Ray.\n\nTo use [X-Ray in Lambda](https:\u002F\u002Fdocs.aws.amazon.com\u002Flambda\u002Flatest\u002Fdg\u002Fservices-xray.html#services-xray-permissions), you can activate it in the Lambda console for a selected function or enable the service in the AWS SAM template:\n\n```yaml\nResources:\n  GetLocations:\n    Type: AWS::Serverless::Function\n    Properties:\n      Tracing: Active\n```\n\nYou must also provide permission, which can be granted using the [AWSXRayDaemonWriteAccess](https:\u002F\u002Fconsole.aws.amazon.com\u002Fiam\u002Fhome?#\u002Fpolicies\u002Farn:aws:iam::aws:policy\u002FAWSXRayDaemonWriteAccess$jsonEditor) managed policy. For each service in your workload, you must also activate X-Ray on the workload’s resources. Once enabled, X-Ray starts collecting tracing data for events. You can instrument calls via the AWS SDK by wrapping the object instantiation with the AWS X-Ray SDK. In Node.js:\n\n```js\n    const AWSXRay = require('aws-xray-sdk-core')\n    const AWS = AWSXRay.captureAWS(require('aws-sdk'))\n```\n\nThis provides additional subsegment granularity and generates additional information captured for calls to DynamoDB, S3, and SQS. By tracing a request from the API endpoint through to the Lambda function and resulting service interactions, you can isolate which part of the system is causing the most latency using the X-Ray service map. X-Ray tracing can be combined with load testing to identify bottlenecks and throttled or exhausted resources.\n\nTo learn about configuring X-Ray for a serverless application, see https:\u002F\u002Fdocs.aws.amazon.com\u002Fxray\u002Flatest\u002Fdevguide\u002Fxray-services-lambda.html.",[10,21,139,247,314,384,486,555],{"title":-1,"collapsible":11,"isCollapsed":12,"content":13},false,true,[14],{"title":15,"order":16,"time":17,"path":18,"id":19,"link":20},"Introduction",1,"4 min","intro","intro.md","\u002Fcontent\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fintro",{"title":22,"collapsible":12,"isCollapsed":12,"content":23},"Event-driven architectures",[24,30,37,43,49,55,62,68,74,80,86,92,98,104,110,116,122,128,133],{"title":22,"order":25,"time":26,"path":27,"id":28,"link":29},2,"1 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