How do I configure sampling with this skill?

It includes implementation details for the ApplicationInsightsSampler to maintain consistent sampling ratios across distributed Python services.

Can it handle intermittent network issues?

Yes, the skill provides patterns for configuring offline storage and retry mechanisms to ensure telemetry data is preserved during connection outages.

When should I use this exporter instead of the Azure Monitor distro?

Use this exporter when you need low-level control over the OpenTelemetry pipeline, such as custom span processors or complex sampling logic, whereas the distro is better for quick, automatic setup.

Does this skill support Azure AD authentication?

Yes, it includes guidance on using DefaultAzureCredential for secure, keyless authentication to Application Insights via Entra ID.

Azure Monitor OpenTelemetry Python Exporter

Name: Azure Monitor OpenTelemetry Python Exporter
Author: MoonAxis

byMoonAxis

•

Analytics & Monitoring

Exports Python OpenTelemetry traces, metrics, and logs to Azure Application Insights with fine-grained control.

This skill equips Claude with the specialized knowledge required to implement the low-level azure-monitor-opentelemetry-exporter library in Python applications. It is specifically designed for developers who need more control than the standard Azure Monitor distro provides, offering implementation patterns for custom telemetry pipelines, advanced sampling, and complex authentication scenarios. By using this skill, users can ensure their cloud-native Azure applications maintain high observability through precise Trace, Metric, and Log exporting to Application Insights.

Key Features

01Azure AD (Entra ID) and Managed Identity authentication

02Support for Sovereign Clouds and custom sampling ratios

03Advanced Trace, Metric, and Log exporting to Application Insights

04Low-level OpenTelemetry pipeline configuration for Python

05Configurable offline storage for high-reliability telemetry

062 GitHub stars

Use Cases

01Implementing robust observability in environments with intermittent connectivity using offline storage

02Configuring secure, identity-based monitoring for Azure-hosted Python services

03Building custom telemetry pipelines that require specific span processors or exporters

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add moonaxis/azure-stack azure-monitor-opentelemetry-exporter-py

For use in Claude.ai and ChatGPT

Key Features

01Azure AD (Entra ID) and Managed Identity authentication

02Support for Sovereign Clouds and custom sampling ratios

03Advanced Trace, Metric, and Log exporting to Application Insights

04Low-level OpenTelemetry pipeline configuration for Python

05Configurable offline storage for high-reliability telemetry

062 GitHub stars

Use Cases

01Implementing robust observability in environments with intermittent connectivity using offline storage

02Configuring secure, identity-based monitoring for Azure-hosted Python services

03Building custom telemetry pipelines that require specific span processors or exporters

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add moonaxis/azure-stack azure-monitor-opentelemetry-exporter-py

For use in Claude.ai and ChatGPT