Azure Functions

H.init("<YOUR_PROJECT_ID>", {
  tracingOrigins: ['localhost', 'example.myapp.com/backend'],
  networkRecording: {
    enabled: true,
    recordHeadersAndBody: true,
  },
});

Install the highlight-io python package.

Download the package from pypi and save it to your requirements. If you use a zip or s3 file upload to publish your function, you will want to make sure highlight-io is part of the build.

poetry add highlight-io
# or with pip
pip install highlight-io

Initialize the Highlight SDK.

Setup the SDK. Add the @observe_handler decorator to your azure functions.

import azure.functions as func

import highlight_io
from highlight_io.integrations.azure import observe_handler

H = highlight_io.H("1", record_logs=True)


@observe_handler
def main(req: func.HttpRequest) -> func.HttpResponse:
    return func.HttpResponse(
        "This HTTP triggered function executed successfully.",
        status_code=200,
    )

Verify your installation.

Check that your installation is valid by throwing an error. Add an operation that raises an exception to your azure function. Setup an HTTP trigger and visit your azure function on the internet. You should see a DivideByZero error in the Highlight errors page within a few moments.

import azure.functions as func

import highlight_io
from highlight_io.integrations.azure import observe_handler

H = highlight_io.H("1", record_logs=True)


@observe_handler
def main(req: func.HttpRequest) -> func.HttpResponse:
    return func.HttpResponse(
        f"Not a good idea: {5 / 0}.",
    )

Set up logging.

With the Python SDK, your logs are reported automatically from builtin logging methods. See the Python logging setup guide for more details.

AWS Lambda Django