Instrumented Python Lambda

This is a "Hello, World" style Lambda function in Python, instrumented with the New Relic Agent.

This example is both instructive, and a diagnostic tool: if you can deploy this Lambda function, and see its events in NR One, you'll know that all the telemetry plumbing is connected correctly.

Building and deploying

Prerequisites

• The AWS CLI v2
• Docker
• The AWS SAM CLI
• newrelic-lambda CLI tool

Make sure you've run the newrelic-lambda integrations install command in your AWS Region, and included the --enable-license-key-secret flag.

To build and deploy your application for the first time, run the following in your shell:

sam build --use-container
sam deploy --guided

The first command will build the source of your application. The second command will package and deploy your application to AWS, with a series of prompts:

• Stack Name: The name of the stack to deploy to CloudFormation. This should be unique to your account and region, and a good starting point would be something matching your project name.
• AWS Region: The AWS region you want to deploy your app to.
• Confirm changes before deploy: If set to yes, any change sets will be shown to you before execution for manual review. If set to no, the AWS SAM CLI will automatically deploy application changes.
• Allow SAM CLI IAM role creation: Many AWS SAM templates, including this example, create AWS IAM roles required for the AWS Lambda function(s) included to access AWS services. By default, these are scoped down to minimum required permissions. To deploy an AWS CloudFormation stack which creates or modifies IAM roles, the CAPABILITY_IAM value for capabilities must be provided. If permission isn't provided through this prompt, to deploy this example you must explicitly pass --capabilities CAPABILITY_IAM to the sam deploy command.
• Save arguments to samconfig.toml: If set to yes, your choices will be saved to a configuration file inside the project, so that in the future you can just re-run sam deploy without parameters to deploy changes to your application.

At this point, you can invoke the function. As provided, the example function doesn't pay attention to its invocation event. If everything has gone well, each invocation gets reported to New Relic, and its telemetry appears in NR One.

Code Structure

Now is also a good time to look at the structure of the example code.

.
├── README.md                   <-- This instructions file
├── newrelic_example_python     <-- Source code for a lambda function
│   ├── app.py                  <-- Lambda function code
├── tests                       <-- Unit tests
└── template.yaml

template.yaml

This function is deployed using a SAM template, which is a CloudFormation template with some extra syntactic sugar for Lambda functions. In it, we tell CloudFormation where to find lambda function code, what layers to use, and what IAM policies to add to the Lambda function's execution role. We also set environment variables that are available to the handler function.

app.py

Lambda functions written in Python are Python modules. The runtime loads them just like any python module, and then invokes the handler function for each invocation event. New Relic publishes a Lambda Layer that wraps your handler function, and initializes the New Relic agent, allowing us to collect telemetry.

There are a couple examples here of how you might add custom events and attributes to the default telemetry.

Since Python is a dynamic, interpreted language, the Agent can inject instrumentation into the various client libraries you might be using in your function. This happens once, during cold start, and provides rich, detailed instrumentation out of the box, with minimal developer effort.

Cleanup

To delete the sample application that you created, use the AWS CLI. Assuming you used your project name for the stack name, you can run the following:

sam delete --stack-name "newrelic_example_python"