sickn33/antigravity-awesome-skills/azure-monitor-opentelemetry-exporter-py

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Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights.

Install

npx vskill@latest install sickn33/antigravity-awesome-skills/azure-monitor-opentelemetry-exporter-py

SKILL.md

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

When to Use

ScenarioUse
Quick setup, auto-instrumentationazure-monitor-opentelemetry (distro)
Custom OpenTelemetry pipelineazure-monitor-opentelemetry-exporter (this)
Fine-grained control over telemetryazure-monitor-opentelemetry-exporter (this)

Export and privacy boundary

Telemetry leaves the application for Azure and may also persist locally in offline storage. Review fields, endpoints, credentials, retention and cost; redact secrets and personal data before export. Reuse an existing provider instead of repeatedly resetting global providers, and flush/shut down providers during process termination. The independent snippets below are alternatives, not a single combined initialization script.

Trace Exporter

python
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

python
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

python
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:

python
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Connection string from environment
exporter = AzureMonitorTraceExporter()

Azure AD Authentication

python
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
exporter = AzureMonitorTraceExporter(
    credential=DefaultAzureCredential()
)

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.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

python
exporter = AzureMonitorTraceExporter(
    connection_string="...",
    disable_offline_storage=True  # Disable disk persistence; transport retry behavior is separate
)

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

ExporterTelemetry TypeApplication Insights Table
AzureMonitorTraceExporterTraces/Spansrequests, dependencies, exceptions
AzureMonitorMetricExporterMetricscustomMetrics, performanceCounters
AzureMonitorLogExporterLogstraces, customEvents

Configuration Options

ParameterDescriptionDefault
connection_stringApplication Insights connection stringFrom env var
credentialAzure credential for AAD authNone
disable_offline_storageDisable retry storageFalse
storage_directoryCustom storage pathTemp 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

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

See the full security report

Quality evaluation

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Source

Popularity

Repository stars
29,638
Repository forks
4,944
Repository npm downloads, 7 days
11,207
7-day trend score
73

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 1 Apr 2026, 6 months ago.

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