azure-monitor-opentelemetry-exporter-py

name	azure-monitor-opentelemetry-exporter-py
description	Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights. Triggers: "azure-monitor-opentelemetry-exporter", "AzureMonitorTraceExporter", "AzureMonitorMetricExporter", "AzureMonitorLogExporter".

Azure Monitor OpenTelemetry Exporter for Python

Low-level exporter for sending OpenTelemetry traces, metrics, and logs to Application Insights.

Installation

pip install azure-monitor-opentelemetry-exporter

Environment Variables

APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/

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

from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter

# Create exporter
exporter = AzureMonitorTraceExporter(
    connection_string="InstrumentationKey=xxx;..."
)

# 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

from opentelemetry import metrics
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter

# Create exporter
exporter = AzureMonitorMetricExporter(
    connection_string="InstrumentationKey=xxx;..."
)

# 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

import logging
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

# Create exporter
exporter = AzureMonitorLogExporter(
    connection_string="InstrumentationKey=xxx;..."
)

# 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:

from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter

# Connection string from environment
exporter = AzureMonitorTraceExporter()

Azure AD Authentication

from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter

exporter = AzureMonitorTraceExporter(
    credential=DefaultAzureCredential()
)

Sampling

Use ApplicationInsightsSampler for consistent sampling:

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:

from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter

exporter = AzureMonitorTraceExporter(
    connection_string="...",
    storage_directory="/path/to/storage",  # Custom storage path
    disable_offline_storage=False  # Enable retry (default)
)

Disable Offline Storage

exporter = AzureMonitorTraceExporter(
    connection_string="...",
    disable_offline_storage=True  # No retry on failure
)

Sovereign 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
)

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. Use BatchSpanProcessor for production (not SimpleSpanProcessor)
2. Use ApplicationInsightsSampler for consistent sampling across services
3. Enable offline storage for reliability in production
4. Use AAD authentication instead of instrumentation keys
5. Set export intervals appropriate for your workload
6. Use the distro (azure-monitor-opentelemetry) unless you need custom pipelines