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npx mdskills install sickn33/azure-monitor-opentelemetry-exporter-pyComprehensive low-level OpenTelemetry exporter with clear examples for traces, metrics, and logs
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 pipelinesInstall via CLI
npx mdskills install sickn33/azure-monitor-opentelemetry-exporter-pyAzure Monitor Opentelemetry Exporter Py is a free, open-source AI agent skill. |
Install Azure Monitor Opentelemetry Exporter Py with a single command:
npx mdskills install sickn33/azure-monitor-opentelemetry-exporter-pyThis downloads the skill files into your project and your AI agent picks them up automatically.
Azure Monitor Opentelemetry Exporter Py works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.