Azure AI Search is powered by three core components: Index, Data Sources, and Indexers. The Index is the heart of search, storing structured fields for fast retrieval. Data Sources supply the raw content, while Indexers act as the pipeline, moving and enriching data into the index. Together, they form the foundation of a scalable, AI-driven search system that powers everything from enterprise knowledge bases to intelligent chatbots.
Azure AI Search – Introduction
Discover how Azure AI Search revolutionizes information discovery with AI-powered indexing, semantic search, and integration with Azure Cognitive Services. From e-commerce optimization to enterprise knowledge management, this guide explores features, benefits, use cases, and setup steps—perfect for businesses looking to harness the future of intelligent search.
Configure MCP Servers on VSCode, Cursor & Claude Desktop
Unlock the full potential of your AI tools by connecting them to external data and custom functionalities. This guide provides clear, step-by-step instructions for configuring Model Context Protocol (MCP) servers in three popular environments: Visual Studio Code, the AI-first editor Cursor, and the Claude Desktop app. Learn how to use the mcp.json file to seamlessly integrate powerful tools directly into your workflow, supercharging your productivity and extending the capabilities of your favorite AI assistants.
Unlocking the Power of LLMs: An Intro On the Model Context Protocol (MCP)
Discover the Model Context Protocol (MCP), a groundbreaking open standard designed to revolutionize how Large Language Models (LLMs) connect with the world. This article provides a comprehensive overview of MCP, explaining how it acts as a universal translator between AI and external data sources and tools. We delve into the critical need for a standardized protocol, explore its client-server architecture and core components, and showcase the significant advantages it brings to LLMs—from accessing real-time information to enabling complex, agent-like workflows.
🚀 Building Resilient Azure Functions: Mastering Microsoft Graph API Calls with Python
Calling Microsoft Graph API from Python Azure Functions? Don't let network glitches or API throttling derail your critical operations. This article provides a deep dive into building resilient serverless applications by implementing a robust, centralized retry mechanism in Python. Discover how to effectively handle transient errors, manage API rate limits gracefully, and make your Microsoft Graph API interactions truly production-ready with practical code examples and best practices for session management and authentication.
Robust Authentication with Microsoft Graph API (Using MSAL and Service Principals)
Unlock robust and efficient Microsoft Graph API authentication in your Python applications using MSAL and Service Principals. Learn best practices for the Client Credentials Flow, including secure secret management, efficient token caching by reusing ConfidentialClientApplication, and comprehensive error handling. Elevate the performance and reliability of your services, like Azure Functions, when interacting with Microsoft 365 data.
Improving Python Azure Function Performance: Handling Large SharePoint Lists with Throttling, Caching, and Batch Requests
Handling lots of SharePoint Items in Azure Functions with Ease. Learn how to supercharge your Azure Functions with Graph API batching, throttling retry logic, in-memory caching, and optimized pagination to efficiently process massive SharePoint Online lists. Ideal for enterprise-scale data automation and integrations.
🔐 Secure Python Azure Function Using Azure Key Vault and Managed Identity
In this enhanced article, we take the foundation of building a secure Azure Function in Python that accesses SharePoint Online via Microsoft Graph API and elevate it using Azure Key Vault with Managed Identity. We demonstrate how to securely store and retrieve secrets like client IDs and secrets using environment-independent authentication, avoiding hardcoding sensitive information. The guide includes detailed steps for deploying to Azure, RBAC-based Key Vault access.
Build a Python Azure Function to Connect with SharePoint Online via Microsoft Graph API
This guide walks you through creating, deploying, and securely managing a Python Azure Function that connects to SharePoint Online using the Microsoft Graph API. Learn how to register an app, configure permissions, install Azure Function Core Tools, manage Python versions, package dependencies, and deploy using ZIP to keep your source code hidden from the Azure Portal. Ideal for production-grade SharePoint integrations in a secure and scalable way.
Elevated Permission in SPFx Webpart Using Power Automate
This article explores an alternative approach to impersonation or elevated permissions. While Azure Functions offer flexibility, they require coding expertise and an Azure subscription, making them resource-intensive. A simpler solution is Power Automate, which is easy to create and maintain without coding or deployment, though it requires premium triggers for impersonation.
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