azure-monitor-opentelemetry-exporter-py
microsoft/skills
Exportieren Sie OpenTelemetry-Traces, Metriken und Logs mit Python an Azure Application Insights.
...Alle erweiternAzure Monitor OpenTelemetry Exporter für Python
Low-Level-Exporter zum Senden von OpenTelemetry-Traces, Metriken und Protokollen an Application Insights.
Installation
pip install azure-monitor-opentelemetry-exporter
Umgebungsvariablen
APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/ # Erforderlich für alle Authentifizierungsmethoden
AZURE_TOKEN_CREDENTIALS=prod # Nur erforderlich, wenn DefaultAzureCredential in der Produktion verwendet wird
🔑 Authentifizierung & Lebenszyklus: Diese Exporter sind konzeptionell auf eine Verbindungszeichenfolge ausgelegt, jedoch wird für AAD-authentifizierte Datenerfassung (wo unterstützt)
DefaultAzureCredentialüber den Parametercredential=bevorzugt – siehe Abschnitt zur Azure AD-Authentifizierung. Alle Azure SDK-Clients, die Sie parallel zum Exporter erstellen, sollten inwith-/async with-Blöcken eingebettet werden (und asynchrone Anmeldeinformationen ausazure.identity.aioentsprechend).
Wann ist die Verwendung sinnvoll?
| Szenario | Verwendung |
|---|---|
| Schnelle Einrichtung, automatische Instrumentierung | `azure-monitor-opentelemetry` (Distro) |
| Benutzerdefinierte OpenTelemetry-Pipeline | `azure-monitor-opentelemetry-exporter` (dies) |
| Feingranulare Steuerung der Telemetriedaten | `azure-monitor-opentelemetry-exporter` (dies) |
Trace-Exporter
from azure.identity import DefaultAzureCredential
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Liest APPLICATIONINSIGHTS_CONNECTION_STRING aus der Umgebung, um die Ressource zu identifizieren;
# DefaultAzureCredential authentifiziert die Datenerfassung über Microsoft Entra ID.
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
# Konfiguriert Tracer-Provider
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(
BatchSpanProcessor(exporter)
)
# Verwendet Tracer
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("my-span"):
print("Hello, World!")
Metrik-Exporter
from azure.identity import DefaultAzureCredential
from opentelemetry import metrics
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
# Liest APPLICATIONINSIGHTS_CONNECTION_STRING aus der Umgebung; AAD-authentifizierte Datenerfassung über DefaultAzureCredential.
exporter = AzureMonitorMetricExporter(
credential=DefaultAzureCredential(),
)
# Konfiguriert Meter-Provider
reader = PeriodicExportingMetricReader(exporter, export_interval_millis=60000)
metrics.set_meter_provider(MeterProvider(metric_readers=[reader]))
# Verwendet Meter
meter = metrics.get_meter(__name__)
counter = meter.create_counter("requests_total")
counter.add(1, {"route": "/api/users"})
Protokoll-Exporter
import logging
from azure.identity import DefaultAzureCredential
from opentelemetry._logs import set_logger_provider
from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler
from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
# Liest APPLICATIONINSIGHTS_CONNECTION_STRING aus der Umgebung; AAD-authentifizierte Datenerfassung über DefaultAzureCredential.
exporter = AzureMonitorLogExporter(
credential=DefaultAzureCredential(),
)
# Konfiguriert Logger-Provider
logger_provider = LoggerProvider()
logger_provider.add_log_record_processor(BatchLogRecordProcessor(exporter))
set_logger_provider(logger_provider)
# Fügt Python-Logging einen Handler hinzu
handler = LoggingHandler(level=logging.INFO, logger_provider=logger_provider)
logging.getLogger().addHandler(handler)
# Verwendet Logging
logger = logging.getLogger(__name__)
logger.info("This will be sent to Application Insights")
Aus Umgebungsvariable
Exporter lesen APPLICATIONINSIGHTS_CONNECTION_STRING automatisch aus:
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Verbindungszeichenfolge aus der Umgebung; AAD-authentifizierte Datenerfassung über DefaultAzureCredential.
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
Azure AD-Authentifizierung
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Lokale Entwicklung: DefaultAzureCredential. Produktion: AZURE_TOKEN_CREDENTIALS=prod oder AZURE_TOKEN_CREDENTIALS=<specific_credential> festlegen
credential = DefaultAzureCredential(require_envvar=True)
# Oder verwenden Sie direkt ein spezifisches Anmeldecredential in der Produktion:
# Siehe https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
exporter = AzureMonitorTraceExporter(
credential=credential
)
</specific_credential>Sampling
Verwenden Sie ApplicationInsightsSampler für ein konsistentes Sampling:
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.sampling import ParentBasedTraceIdRatio
from azure.monitor.opentelemetry.exporter import ApplicationInsightsSampler
# 10 % der Traces werden gesampelt
sampler = ApplicationInsightsSampler(sampling_ratio=0.1)
trace.set_tracer_provider(TracerProvider(sampler=sampler))
Offline-Speicher
Konfigurieren Sie Offline-Speicher für Wiederholungsversuche:
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
storage_directory="/path/to/storage", # Benutzerdefinierter Speicherpfad
disable_offline_storage=False # Wiederholungsversuch aktivieren (Standard)
)
Offline-Speicher deaktivieren
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
disable_offline_storage=True # Kein Wiederholungsversuch bei Fehler
)
Souveräne Clouds
from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Azure Government
credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_GOVERNMENT)
exporter = AzureMonitorTraceExporter(
connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.us/",
credential=credential
)
Exportertypen
| Exporter | Telemetrietyp | Application Insights-Tabelle |
|---|---|---|
| `AzureMonitorTraceExporter` | Traces/Spans | requests, dependencies, exceptions |
| `AzureMonitorMetricExporter` | Metriken | customMetrics, performanceCounters |
| `AzureMonitorLogExporter` | Protokolle | traces, customEvents |
Konfigurationsoptionen
| Parameter | Beschreibung | Standardwert |
|---|---|---|
| `connection_string` | Verbindungszeichenfolge für Application Insights | Aus Umgebungsvariable |
| `credential` | Azure-Anmeldecredential für AAD-Authentifizierung | None |
| `disable_offline_storage` | Speicher für Wiederholungsversuche deaktivieren | False |
| `storage_directory` | Benutzerdefinierter Speicherpfad | Temp-Verzeichnis |
Best Practices
- Entscheiden Sie sich für synchron ODER asynchron und bleiben Sie konsistent. Mischen Sie keine synchronen
azure.xxx-Clients mit asynchronenazure.xxx.aio-Clients im selben Aufrufpfad. Wählen Sie pro Modul einen Modus. - Flushen und beenden Sie Provider beim Prozessende. Rufen Sie die Shutdown-/Flush-APIs (z. B.
tracer_provider.shutdown(),meter_provider.shutdown(),logger_provider.shutdown()) beim Prozessende auf, um Telemetriedaten zu flushen, bevor der Prozess beendet wird. - Verwenden Sie BatchSpanProcessor für die Produktion (nicht SimpleSpanProcessor)
- Verwenden Sie ApplicationInsightsSampler für ein konsistentes Sampling über Dienste hinweg
- Aktivieren Sie Offline-Speicher für Zuverlässigkeit in der Produktion
- Verwenden Sie Microsoft Entra-Authentifizierung anstelle von Instrumentierungsschlüsseln
- Legen Sie Exportintervalle fest, die für Ihre Arbeitslast geeignet sind
- Verwenden Sie die Distro (
azure-monitor-opentelemetry), es sei denn, Sie benötigen benutzerdefinierte Pipelines
---
name: azure-monitor-opentelemetry-exporter-py
description: Export OpenTelemetry traces, metrics, and logs to Azure Application Insights using Python.
license: MIT
---
# Azure Monitor OpenTelemetry Exporter for Python
Low-level exporter for sending OpenTelemetry traces, metrics, and logs to Application Insights.
## Installation
```bash
pip install azure-monitor-opentelemetry-exporter
```
## Environment Variables
```bash
APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/ # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
```
> **🔑 Auth & lifecycle:** These exporters take a connection string by design, but for *AAD-authenticated ingestion* (where supported) prefer `DefaultAzureCredential` via the `credential=` parameter — see the [Azure AD Authentication](#azure-ad-authentication) section. Any Azure SDK clients you create alongside the exporter should be wrapped in `with`/`async with` blocks (and async credentials from `azure.identity.aio` likewise).
## When to Use
| Scenario | Use |
|----------|-----|
| Quick setup, auto-instrumentation | `azure-monitor-opentelemetry` (distro) |
| Custom OpenTelemetry pipeline | `azure-monitor-opentelemetry-exporter` (this) |
| Fine-grained control over telemetry | `azure-monitor-opentelemetry-exporter` (this) |
## Trace Exporter
```python
from azure.identity import DefaultAzureCredential
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Reads APPLICATIONINSIGHTS_CONNECTION_STRING from env to identify the resource;
# DefaultAzureCredential authenticates ingestion via Microsoft Entra ID.
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
# Configure tracer provider
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(
BatchSpanProcessor(exporter)
)
# Use tracer
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("my-span"):
print("Hello, World!")
```
## Metric Exporter
```python
from azure.identity import DefaultAzureCredential
from opentelemetry import metrics
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
# Reads APPLICATIONINSIGHTS_CONNECTION_STRING from env; AAD-authenticated ingestion via DefaultAzureCredential.
exporter = AzureMonitorMetricExporter(
credential=DefaultAzureCredential(),
)
# Configure meter provider
reader = PeriodicExportingMetricReader(exporter, export_interval_millis=60000)
metrics.set_meter_provider(MeterProvider(metric_readers=[reader]))
# Use meter
meter = metrics.get_meter(__name__)
counter = meter.create_counter("requests_total")
counter.add(1, {"route": "/api/users"})
```
## Log Exporter
```python
import logging
from azure.identity import DefaultAzureCredential
from opentelemetry._logs import set_logger_provider
from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler
from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
# Reads APPLICATIONINSIGHTS_CONNECTION_STRING from env; AAD-authenticated ingestion via DefaultAzureCredential.
exporter = AzureMonitorLogExporter(
credential=DefaultAzureCredential(),
)
# Configure logger provider
logger_provider = LoggerProvider()
logger_provider.add_log_record_processor(BatchLogRecordProcessor(exporter))
set_logger_provider(logger_provider)
# Add handler to Python logging
handler = LoggingHandler(level=logging.INFO, logger_provider=logger_provider)
logging.getLogger().addHandler(handler)
# Use logging
logger = logging.getLogger(__name__)
logger.info("This will be sent to Application Insights")
```
## From Environment Variable
Exporters read `APPLICATIONINSIGHTS_CONNECTION_STRING` automatically:
```python
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Connection string from environment; AAD-authenticated ingestion via DefaultAzureCredential.
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
```
## Azure AD Authentication
```python
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
exporter = AzureMonitorTraceExporter(
credential=credential
)
```
## Sampling
Use `ApplicationInsightsSampler` for consistent sampling:
```python
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.sampling import ParentBasedTraceIdRatio
from azure.monitor.opentelemetry.exporter import ApplicationInsightsSampler
# Sample 10% of traces
sampler = ApplicationInsightsSampler(sampling_ratio=0.1)
trace.set_tracer_provider(TracerProvider(sampler=sampler))
```
## Offline Storage
Configure offline storage for retry:
```python
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
storage_directory="/path/to/storage", # Custom storage path
disable_offline_storage=False # Enable retry (default)
)
```
## Disable Offline Storage
```python
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
disable_offline_storage=True # No retry on failure
)
```
## Sovereign Clouds
```python
from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Azure Government
credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_GOVERNMENT)
exporter = AzureMonitorTraceExporter(
connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.us/",
credential=credential
)
```
## Exporter Types
| Exporter | Telemetry Type | Application Insights Table |
|----------|---------------|---------------------------|
| `AzureMonitorTraceExporter` | Traces/Spans | requests, dependencies, exceptions |
| `AzureMonitorMetricExporter` | Metrics | customMetrics, performanceCounters |
| `AzureMonitorLogExporter` | Logs | traces, customEvents |
## Configuration Options
| Parameter | Description | Default |
|-----------|-------------|---------|
| `connection_string` | Application Insights connection string | From env var |
| `credential` | Azure credential for AAD auth | None |
| `disable_offline_storage` | Disable retry storage | False |
| `storage_directory` | Custom storage path | Temp directory |
## Best Practices
1. **Pick sync OR async and stay consistent.** Do not mix `azure.xxx` sync clients with `azure.xxx.aio` async clients in the same call path. Choose one mode per module.
2. **Flush and shut down providers at process exit.** Call the shutdown/flush APIs (e.g. `tracer_provider.shutdown()`, `meter_provider.shutdown()`, `logger_provider.shutdown()`) at process exit to flush telemetry before the process terminates.
3. **Use BatchSpanProcessor** for production (not SimpleSpanProcessor)
4. **Use ApplicationInsightsSampler** for consistent sampling across services
5. **Enable offline storage** for reliability in production
6. **Use Microsoft Entra authentication** instead of instrumentation keys
7. **Set export intervals** appropriate for your workload
8. **Use the distro** (`azure-monitor-opentelemetry`) unless you need custom pipelines
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