Track incoming requests with OpenCensus Python

OpenCensus Python and its integrations collect incoming request data. You can track incoming request data sent to your web applications built on top of the popular web frameworks Django, Flask, and Pyramid. Application Insights receives the data as requests telemetry.

First, instrument your Python application with the latest OpenCensus Python SDK.

1. Download and install opencensus-ext-django from PyPI. Instrument your application with the django middleware. Incoming requests sent to your Django application are tracked.

2. Include opencensus.ext.django.middleware.OpencensusMiddleware in your settings.py file under MIDDLEWARE.

   MIDDLEWARE = (
       ...
       'opencensus.ext.django.middleware.OpencensusMiddleware',
       ...
   )
   

3. Make sure AzureExporter is configured properly in your settings.py under OPENCENSUS. For requests from URLs that you don't want to track, add them to EXCLUDELIST_PATHS.

   OPENCENSUS = {
       'TRACE': {
           'SAMPLER': 'opencensus.trace.samplers.ProbabilitySampler(rate=1)',
           'EXPORTER': '''opencensus.ext.azure.trace_exporter.AzureExporter(
               connection_string="InstrumentationKey=<your-ikey-here>"
           )''',
           'EXCLUDELIST_PATHS': ['https://example.com'],  <--- These sites will not be traced if a request is sent to it.
       }
   }
   

You can find a Django sample application in the Azure Monitor OpenCensus Python samples repository.

1. Download and install opencensus-ext-flask from PyPI. Instrument your application with the flask middleware. Incoming requests sent to your Flask application are tracked.

   
   from flask import Flask
   from opencensus.ext.azure.trace_exporter import AzureExporter
   from opencensus.ext.flask.flask_middleware import FlaskMiddleware
   from opencensus.trace.samplers import ProbabilitySampler
   
   app = Flask(__name__)
   middleware = FlaskMiddleware(
       app,
       exporter=AzureExporter(connection_string="InstrumentationKey=<your-ikey-here>"),
       sampler=ProbabilitySampler(rate=1.0),
   )
   
   @app.route('/')
   def hello():
       return 'Hello World!'
   
   if __name__ == '__main__':
       app.run(host='localhost', port=8080, threaded=True)
   
   

2. You can also configure your flask application through app.config. For requests from URLs that you don't want to track, add them to EXCLUDELIST_PATHS.

   app.config['OPENCENSUS'] = {
       'TRACE': {
           'SAMPLER': 'opencensus.trace.samplers.ProbabilitySampler(rate=1.0)',
           'EXPORTER': '''opencensus.ext.azure.trace_exporter.AzureExporter(
               connection_string="InstrumentationKey=<your-ikey-here>",
           )''',
           'EXCLUDELIST_PATHS': ['https://example.com'],  <--- These sites will not be traced if a request is sent to it.
       }
   }
   

   Note

   To run Flask under uWSGI in a Docker environment, you must first add lazy-apps = true to the uWSGI configuration file (uwsgi.ini). For more information, see the issue description.

You can find a Flask sample application that tracks requests in the Azure Monitor OpenCensus Python samples repository.

1. Download and install opencensus-ext-django from PyPI. Instrument your application with the pyramid tween. Incoming requests sent to your Pyramid application are tracked.

   def main(global_config, **settings):
       config = Configurator(settings=settings)
   
       config.add_tween('opencensus.ext.pyramid'
                        '.pyramid_middleware.OpenCensusTweenFactory')
   

2. You can configure your pyramid tween directly in the code. For requests from URLs that you don't want to track, add them to EXCLUDELIST_PATHS.

   settings = {
       'OPENCENSUS': {
           'TRACE': {
               'SAMPLER': 'opencensus.trace.samplers.ProbabilitySampler(rate=1.0)',
               'EXPORTER': '''opencensus.ext.azure.trace_exporter.AzureExporter(
                   connection_string="InstrumentationKey=<your-ikey-here>",
               )''',
               'EXCLUDELIST_PATHS': ['https://example.com'],  <--- These sites will not be traced if a request is sent to it.
           }
       }
   }
   config = Configurator(settings=settings)
   

1. The following dependencies are required:

   • fastapi

   • uvicorn

     In a production setting, we recommend that you deploy uvicorn with gunicorn.

2. Download and install opencensus-ext-fastapi from PyPI.

   pip install opencensus-ext-fastapi

3. Instrument your application with the fastapi middleware.

   from fastapi import FastAPI
   from opencensus.ext.fastapi.fastapi_middleware import FastAPIMiddleware
   
   app = FastAPI(__name__)
   app.add_middleware(FastAPIMiddleware)
   
   @app.get('/')
   def hello():
       return 'Hello World!'
   

4. Run your application. Calls made to your FastAPI application should be automatically tracked. Telemetry should be logged directly to Azure Monitor.

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