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azure-monitor-opentelemetry-exporter-py
Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights.
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Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights.
AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" request.
Diff a live page's accessibility violations against a baseline — by default compares uncommitted changes (stash-based), or pass --branch [<name>] to diff against a branch. Reports only new violations introduced, violations fixed, and pre-existing count. Use `scan` for a full audit with no diffing.
Use the Hugging Face Hub CLI (`hf`) to download, upload, and manage models, datasets, and Spaces.
Plan, orchestrate, and adversarially verify parallel AI coding agents with a dynamic multi-agent workflow engine.
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Generate AI images, videos, and music/audio from agents using the RunAPI CLI.
| name | azure-monitor-opentelemetry-exporter-py |
| description | Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights. |
| risk | unknown |
| source | community |
| date_added | 2026-02-27 |
Low-level exporter for sending OpenTelemetry traces, metrics, and logs to Application Insights.
pip install azure-monitor-opentelemetry-exporter
APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/
| 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) |
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!")
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"})
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")
Exporters read APPLICATIONINSIGHTS_CONNECTION_STRING automatically:
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Connection string from environment
exporter = AzureMonitorTraceExporter()
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential()
)
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))
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)
)
exporter = AzureMonitorTraceExporter(
connection_string="...",
disable_offline_storage=True # No retry on failure
)
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 | Telemetry Type | Application Insights Table |
|---|---|---|
AzureMonitorTraceExporter | Traces/Spans | requests, dependencies, exceptions |
AzureMonitorMetricExporter | Metrics | customMetrics, performanceCounters |
AzureMonitorLogExporter | Logs | traces, customEvents |
| 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 |
azure-monitor-opentelemetry) unless you need custom pipelines