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Difficulty: MediumInstrumenting Distributed Tracing with AWS X-Ray

A developer is troubleshooting a serverless application where an Amazon API Gateway stage triggers an AWS Lambda function written in Python. The function processes incoming requests and retrieves secrets from AWS Secrets Manager using the `boto3` library. Active tracing is enabled on both the API Gateway stage and the Lambda function. However, the AWS X-Ray trace map shows the segments for API Gateway and the Lambda function, but does not display any segments for the calls to AWS Secrets Manager. How should the developer resolve this issue to ensure the Secrets Manager calls are visible in the trace map?

  1. A
    Initialize the Secrets Manager client by hardcoding temporary AWS access keys and session tokens in the `boto3.client` constructor.
  2. B
    Increase the Lambda function's execution timeout to ensure the background thread of the X-Ray SDK has sufficient time to flush the tracing segments.
  3. Import the AWS X-Ray SDK for Python and call `patch_all()` or `patch(['boto3'])` before initializing the Secrets Manager client.Answer
  4. D
    Change the API Gateway integration type to a custom integration and use a mapping template to inject the tracing header into the Lambda event payload.

Answer

Import the AWS X-Ray SDK for Python and call `patch_all()` or `patch(['boto3'])` before initializing the Secrets Manager client.
To trace downstream calls made by the AWS SDK (such as `boto3` in Python) within an AWS Lambda function, the developer must instrument the SDK. Using the AWS X-Ray SDK for Python to patch `boto3` (using `patch_all()` or `patch(['boto3'])`) intercepts all downstream calls to AWS services, records the segment details, and propagates the tracing context.

Step-by-Step Solution

1
Analyze the missing segments in the X-Ray trace map.
The trace map only displays the nodes for API Gateway and the Lambda function, but is missing the node for AWS Secrets Manager.
Although active tracing is enabled on Lambda, the AWS SDK client inside the function code must be explicitly instrumented or patched to generate downstream trace segments.
2
Use the AWS X-Ray SDK for Python to patch the boto3 library.
The boto3 library is dynamically patched at startup, wrapping all client operations with X-Ray interceptors.
Patching ensures that all subsequent AWS SDK calls created via boto3 automatically capture metadata and create subsegments linked to the parent execution context.
3
Redeploy the function and execute a test request.
The updated trace map shows the complete end-to-end flow, including the AWS Secrets Manager calls.
The instrumented boto3 client successfully transmits the subsegment data to the X-Ray daemon, which is then sent to AWS X-Ray.

Key Concept

AWS SDK instrumentation using the AWS X-Ray SDK for Python to trace downstream calls.
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Topics

Instrumenting Distributed Tracing with AWS X-Ray

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