X-Ray Tracing for Lambda and API Gateway

X-Ray is the core distributed tracing service on AWS, and both the DOP-C02 exam and real-world troubleshooting demand that you can configure it end-to-end. Turning on tracing is not enough — you need to know how to read the service map, parse the trace timeline, and isolate exactly which segment caused the problem.

In this lab you will:

• Create an IAM execution role with Lambda, API Gateway, and X-Ray write permissions
• Write and deploy a Node.js Lambda function that simulates a multi-phase order-processing pipeline with an intentional 1.5-second payment-processing delay and an error-injection switch
• Build a REST API Gateway with a `/orders` POST endpoint, wire it to the Lambda, and enable X-Ray on the API stage
• Generate traffic with `curl`, then use `aws xray get-service-graph` and `batch-get-traces` to locate the slowest segment and measure its contribution to overall latency
• Inject a fault by submitting an invalid payment amount, trace the error through the service map, and identify the failing subsegment from its fault flag and error metadata
• Add X-Ray annotations to the Lambda code, create a sampling rule, and confirm that annotations appear in downstream trace views

Everything runs inside a TeKanAid-provisioned AWS lab account using API Gateway (REST), Lambda, X-Ray, CloudWatch Logs, and IAM.