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---
title: Enable telemetry for feature flags in a Python application
titleSuffix: Azure App Configuration
description: Learn how to use telemetry in python for feature flags in Azure App Configuration.
ms.service: azure-app-configuration
author: mrm9084
ms.author: mametcal
ms.topic: how-to
ms.date: 05/06/2025
---
# Enable telemetry for feature flags in a Python application
In this tutorial, you use telemetry in your Python application to track feature flag evaluations and custom events. Telemetry allows you to make informed decisions about your feature management strategy. You utilize the feature flag with telemetry enabled created in the [overview for enabling telemetry for feature flags](./howto-telemetry.md). Before proceeding, ensure that you create a feature flag named *Greeting* in your Configuration store with telemetry enabled. This tutorial builds on top of the tutorial for [using variant feature flags in a Python application](./howto-variant-feature-flags-python.md).
## Prerequisites
- The variant feature flag with telemetry enabled from [Enable telemetry for feature flags](./howto-telemetry.md).
- The application from [Use variant feature flags in a Python application](./howto-variant-feature-flags-python.md).
## Add telemetry to your Python application
1. Install the required packages using pip:
```bash
pip install azure-appconfiguration-provider
pip install featuremanagement["AzureMonitor"]
pip install azure-monitor-opentelemetry
```
1. Open `app.py` and configure your code to connect to Application Insights to publish telemetry.
```python
import os
from azure.monitor.opentelemetry import configure_azure_monitor
# Configure Azure Monitor
configure_azure_monitor(connection_string=os.getenv("APPLICATIONINSIGHTS_CONNECTION_STRING"))
```
1. Also in `app.py` load your feature flags from App Configuration and load them into feature management. `FeatureManager` uses the `publish_telemetry` callback function to publish telemetry to Azure Monitor.
```python
from featuremanagement.azuremonitor import publish_telemetry
feature_manager = FeatureManager(config, on_feature_evaluated=publish_telemetry)
```
1. Open `routes.py` and update your code to track your own events in your application. When `track_event` is called, a custom event is published to Azure Monitor with the provided user.
```python
from featuremanagement import track_event
@bp.route("/heart", methods=["POST"])
def heart():
if current_user.is_authenticated:
user = current_user.username
# Track the appropriate event based on the action
track_event("Liked", user)
return jsonify({"status": "success"})
```
1. Open `index.html` and update the code to implement the like button. The like button sends a POST request to the `/heart` endpoint when clicked.
```html
<script>
function heartClicked(button) {
var icon = button.querySelector('i');
// Toggle the heart icon appearance
icon.classList.toggle('far');
icon.classList.toggle('fas');
// Only send a request to the dedicated heart endpoint when it's a like action
if (icon.classList.contains('fas')) {
fetch('/heart', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
}
});
}
}
</script>
```
## Build and run the app
1. Application insights requires a connection string to connect to your Application Insights resource. Set the `APPLICATIONINSIGHTS_CONNECTION_STRING` environment variable to the connection string for your Application Insights resource.
```cmd
setx APPLICATIONINSIGHTS_CONNECTION_STRING "applicationinsights-connection-string"
```
If you use PowerShell, run the following command:
```powershell
$Env:APPLICATIONINSIGHTS_CONNECTION_STRING = "applicationinsights-connection-string"
```
If you use macOS or Linux, run the following command:
```bash
export APPLICATIONINSIGHTS_CONNECTION_STRING='applicationinsights-connection-string'
```
## Collect telemetry
Deploy your application to begin collecting telemetry from your users. To test its functionality, you can simulate user activity by creating many test users. Each user will experience a different variant of greeting messages, and they can interact with the application by clicking the heart button to like a quote. As your user base grows, you can monitor the increasing volume of telemetry data collected in Azure App Configuration. Additionally, you can drill down into the data to analyze how each variant of the feature flag influences user behavior.
- [Review telemetry results in App Configuration](./howto-telemetry.md#review-telemetry-results-in-azure-app-configuration).
## Additional resources
- [Flask Quote of the Day sample](https://github.com/Azure-Samples/quote-of-the-day-python)
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