---
name: azure-monitor-opentelemetry-py
description: "|"
Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.
Triggers: "azure-monitor-opentelemetry", "configure_azure_monitor", "Application Insights", "OpenTelemetry distro", "auto-instrumentation".
package: azure-monitor-opentelemetry
risk: unknown
source: community
---
# Azure Monitor OpenTelemetry Distro for Python
One-line setup for Application Insights with OpenTelemetry auto-instrumentation.
## Installation
```bash
pip install azure-monitor-opentelemetry
```
## Environment Variables
```bash
APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/
```
## Quick Start
```python
from azure.monitor.opentelemetry import configure_azure_monitor
# One-line setup - reads connection string from environment
configure_azure_monitor()
# Your application code...
```
## Explicit Configuration
```python
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor(
connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/"
)
```
## With Flask
```python
from flask import Flask
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
app = Flask(__name__)
@app.route("/")
def hello():
return "Hello, World!"
if __name__ == "__main__":
app.run()
```
## With Django
```python
# settings.py
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
# Django settings...
```
## With FastAPI
```python
from fastapi import FastAPI
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
app = FastAPI()
@app.get("/")
async def root():
return {"message": "Hello World"}
```
## Custom Traces
```python
from opentelemetry import trace
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("my-operation") as span:
span.set_attribute("custom.attribute", "value")
# Do work...
```
## Custom Metrics
```python
from opentelemetry import metrics
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
meter = metrics.get_meter(__name__)
counter = meter.create_counter("my_counter")
counter.add(1, {"dimension": "value"})
```
## Custom Logs
```python
import logging
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
logger.info("This will appear in Application Insights")
logger.error("Errors are captured too", exc_info=True)
```
## Sampling
```python
from azure.monitor.opentelemetry import configure_azure_monitor
# Sample 10% of requests
configure_azure_monitor(
sampling_ratio=0.1
)
```
## Cloud Role Name
Set cloud role name for Application Map:
```python
from azure.monitor.opentelemetry import configure_azure_monitor
from opentelemetry.sdk.resources import Resource, SERVICE_NAME
configure_azure_monitor(
resource=Resource.create({SERVICE_NAME: "my-service-name"})
)
```
## Disable Specific Instrumentations
```python
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor(
instrumentations=["flask", "requests"] # Only enable these
)
```
## Enable Live Metrics
```python
from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor(
enable_live_metrics=True
)
```
## Azure AD Authentication
```python
from azure.monitor.opentelemetry import configure_azure_monitor
from azure.identity import DefaultAzureCredential
configure_azure_monitor(
credential=DefaultAzureCredential()
)
```
## Auto-Instrumentations Included
| Library | Telemetry Type |
|---------|---------------|
| Flask | Traces |
| Django | Traces |
| FastAPI | Traces |
| Requests | Traces |
| urllib3 | Traces |
| httpx | Traces |
| aiohttp | Traces |
| psycopg2 | Traces |
| pymysql | Traces |
| pymongo | Traces |
| redis | Traces |
## Configuration Options
| Parameter | Description | Default |
|-----------|-------------|---------|
| `connection_string` | Application Insights connection string | From env var |
| `credential` | Azure credential for AAD auth | None |
| `sampling_ratio` | Sampling rate (0.0 to 1.0) | 1.0 |
| `resource` | OpenTelemetry Resource | Auto-detected |
| `instrumentations` | List of instrumentations to enable | All |
| `enable_live_metrics` | Enable Live Metrics stream | False |
## Best Practices
1. **Call configure_azure_monitor() early** — Before importing instrumented libraries
2. **Use environment variables** for connection string in production
3. **Set cloud role name** for multi-service applications
4. **Enable sampling** in high-traffic applications
5. **Use structured logging** for better log analytics queries
6. **Add custom attributes** to spans for better debugging
7. **Use AAD authentication** for production workloads
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.