How do I set the Cloud Role Name for the Application Map?

You can set the Cloud Role Name by passing a Resource object with the SERVICE_NAME attribute to the configuration function during setup.

Can I use Azure Active Directory for authentication?

Absolutely. The skill provides configuration patterns for using DefaultAzureCredential for secure AAD-based telemetry ingestion.

Does this skill support FastAPI and Django?

Yes, it includes auto-instrumentation for FastAPI, Django, Flask, and many other common Python libraries and database drivers.

Does it support real-time monitoring?

Yes, there is a specific configuration option to enable the Live Metrics stream for real-time performance monitoring in the Azure Portal.

Azure Monitor OpenTelemetry for Python

Name: Azure Monitor OpenTelemetry for Python
Author: MoonAxis

byMoonAxis

•

分析与监控

Configures Azure Application Insights with one-line OpenTelemetry auto-instrumentation for Python applications.

This skill streamlines the observability of Python applications on Azure by implementing the Azure Monitor OpenTelemetry Distro. It enables developers to quickly set up distributed tracing, metrics, and logging for popular frameworks like FastAPI, Django, and Flask without complex manual configuration. By integrating best practices such as Azure AD authentication, sampling, and Cloud Role Name identification, it ensures your cloud-native applications are production-ready and fully visible within the Azure Monitor ecosystem.

主要功能

01Integrated support for custom distributed tracing, metrics, and structured logging

02Advanced configuration for sampling ratios, Cloud Role Names, and Live Metrics

03One-line setup for Application Insights using configure_azure_monitor()

042 GitHub stars

05Built-in Azure Active Directory (AAD) authentication support for secure telemetry ingestion

06Auto-instrumentation for major libraries like Flask, Django, FastAPI, and Requests

使用场景

01Migrating legacy Application Insights SDKs to the modern OpenTelemetry standard

02Adding full-stack observability to a Python web service deployed on Azure

03Implementing distributed tracing across a microservices architecture on Azure

What are Skills?·How to Install

Install with 🐟 Skill.Fish

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

For use in Claude.ai and ChatGPT

主要功能

01Integrated support for custom distributed tracing, metrics, and structured logging

02Advanced configuration for sampling ratios, Cloud Role Names, and Live Metrics

03One-line setup for Application Insights using configure_azure_monitor()

042 GitHub stars

05Built-in Azure Active Directory (AAD) authentication support for secure telemetry ingestion

06Auto-instrumentation for major libraries like Flask, Django, FastAPI, and Requests

使用场景

01Migrating legacy Application Insights SDKs to the modern OpenTelemetry standard

02Adding full-stack observability to a Python web service deployed on Azure

03Implementing distributed tracing across a microservices architecture on Azure

What are Skills?·How to Install

Install with 🐟 Skill.Fish

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

For use in Claude.ai and ChatGPT