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Is there a way to invoke lambda with X-Ray by using sam invoke local?
According to the idea which PaulMaddox mentioned, I have tried the step below, and I don't know whether I misunderstood :
ENV AWS_XRAY_DAEMON_ADDRESS: 0.0.0.0:2000
Missing AWS Lambda trace data for X-Ray. Expected _X_AMZN_TRACE_ID to be set
Here is part of template.yaml setting, I used the environment variable to set AWS_XRAY_DAEMON_ADDRESS
It would be nice if you could provide more information.
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You can invoke your function locally by using the sam local invoke command and providing its function logical ID and an event file. Alternatively, sam local invoke also accepts stdin as an event. For more information about events, see Event in the AWS Lambda Developer Guide.
What is needed to use AWS X-Ray to trace Lambda-based applications? A. Send logs from the Lambda application to an S3 bucket; trigger a Lambda function from the bucket to send data to AWS X-Ray.
Lambda Functions can be triggered in different ways: an HTTP request, a new document upload to S3, a scheduled Job, an AWS Kinesis data stream, or a notification from AWS Simple Notification Service (SNS).
You can use AWS X-Ray to trace your AWS Lambda functions. Lambda runs the X-Ray daemon and records a segment with details about the function invocation and execution.
While we could enable X-Ray via AWS console, it is always better to have your application be fully deployable with a push of a button and a stack definition. On June 6, 2017 AWS CloudFormation released the TracingConfig property, that, along with a permissions change enables AWS X-Ray on your Lambda function.
The Lambda layer for AWS Lambda provides a plug-and-play user experience by automatically instrumenting a Lambda function, by packaging the OpenTelemetry Python SDK together with an out-of-the-box configuration for AWS Lambda and AWS X-Ray.
You can run the AWS X-Ray daemon locally on Linux, MacOS, Windows, or in a Docker container. Run the daemon to relay trace data to X-Ray when you are developing and testing your instrumented application. Download and extract the daemon by using the instructions here .
I'm not too familiar with SAM, but...
You need to set the _X_AMZN_TRACE_ID environment variable. Currently, the X-Ray Node SDK works by cross communicating between the Lambda runtime start-up code and the user code.
Lambda starts the segment in their start-up code, records information such as timing and exceptions, and sends the segment to the X-Ray service. Then, it forwards the trace ID/parent ID/sampling decision to the user code via setting the _X_AMZN_TRACE_ID environment variable. This allows the SDK to create a separate subsegment, inferring a connection to the original segment, which gets "weaved" into the original on the service end without actually being directly related. Both are sent out of band, asynchronously from each other.
The _X_AMZN_TRACE_ID variable fits the same format as the tracing header here as discussed here: https://docs.aws.amazon.com/xray/latest/devguide/xray-concepts.html#xray-concepts-tracingheader
If you want to send traces through the Daemon to the X-Ray service, you'll need to figure out how to get SAM to construct this Lambda segment initially and set the _X_AMZN_TRACE_ID prior to importing the SDK.
Since the SDK auto-detects the presence of Lambda (which as I understand, SAM mimics), you'll have to set the _X_AMZN_TRACE_ID variable before importing in the SDK. Which, is kind of a catch-22, because you need to import the SDK (in the non-Lambda mode) to construct the Lambda segment before you can populate the _X_AMZN_TRACE_ID.
The problem lies here: https://github.com/aws/aws-xray-sdk-node/blob/master/packages/core/lib/aws-xray.js#L361
If you flip the SDK into LOG_ERROR mode (ignoring the Lambda errors), create and send the Lambda segment (just manually create a segment, load the generated ID/Parent ID/Sampling into _X_AMZN_TRACE_ID then close the segment) and then clear cache/re-import the SDK after, then that should work.
Otherwise, I suspect there may be some work on the SAM end to have this built in. But, hopefully this work around works.
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