Instrument Python Flask and FastAPI applications with Azure Monitor OpenTelemetry Distro for comprehensive observability. Learn automatic instrumentation, custom spans with tracers, custom metrics, logging integration, database tracking, and production configuration patterns.
Author: Chandan
Azure Monitor with OpenTelemetry Part 2: Setting Up OpenTelemetry in .NET Applications
.NET developers can instrument ASP.NET Core applications with OpenTelemetry and Azure Monitor in minutes. Learn automatic instrumentation, custom spans with Activity and ActivitySource, custom metrics implementation, and production configuration patterns for comprehensive observability.
Multi-Model Orchestration: Claude, GPT-4, and Gemini in Azure AI Foundry
Azure AI Foundry provides access to Claude, GPT-4, and Gemini models in a single platform. Multi-model orchestration allows you to leverage each model’s strengths, implement
Azure Monitor with OpenTelemetry Part 1: Understanding OpenTelemetry and Azure Monitor Integration
Understand the fundamentals of OpenTelemetry and why Azure Monitor adopted this vendor-neutral observability framework. Learn about the three pillars of observability, OpenTelemetry architecture, Azure Monitor Distro, and key differences from legacy Application Insights SDKs.
Cost Optimization Strategies for Azure AI Foundry Claude Deployments
Azure AI Foundry deployments of Claude can quickly become expensive at scale without proper cost management. Understanding the pricing model, implementing intelligent caching, choosing appropriate
OpenTelemetry for Node.js with Azure Monitor: Complete Implementation Guide
Learn how to implement OpenTelemetry instrumentation for Node.js applications with Azure Monitor. Complete guide covering Express and Fastify frameworks, automatic instrumentation, custom spans, custom metrics, production configuration, and migration from legacy Application Insights SDK.
Building Production RAG Systems with Azure AI Foundry and Claude
Production RAG systems transform Claude from a general-purpose assistant into a domain expert grounded in your enterprise data. Building reliable, scalable RAG architectures in Azure
Model Context Protocol Part 6: Production Deployment and Monitoring at Scale
Master production deployment of MCP servers with Kubernetes orchestration, CI/CD automation, OpenTelemetry monitoring, and performance optimization strategies for enterprise-scale AI integration.
Azure Event Grid vs Event Hubs vs Service Bus: Complete Technical Comparison
When building distributed systems on Azure, choosing the right messaging service can make the difference between a resilient, scalable architecture and one plagued with bottlenecks
Model Context Protocol Part 5: Integrating MCP Servers with Azure AI Foundry and Claude
Connect MCP servers to Azure AI Foundry and Claude with practical integration examples. Learn configuration, authentication, and cross-platform orchestration patterns for enterprise AI deployments.
