Learn Azure AI Search with C# — index data, run vector and hybrid queries, and add RAG to your .NET app. Start building intelligent search today. If your application's search box still runs a LIKE '%term%' query against SQL Server, your users are quietly suffering. They type "cheap laptop for uni" and get zero results because your catalogue says "affordable notebook for students." Azure AI Search with C# fixes exactly this problem: it combines classic keyword search, vector embeddings, and semantic reranking into a single managed service that you can drive from .NET with a few dozen lines of code. In this tutorial you'll build a working search index from scratch, run keyword, vector, and hybrid queries, and finish with a Retrieval Augmented Generation (RAG) pattern that grounds an LLM in your own data. This guide targets .NET 9 and the Azure.Search.Documents v11 SDK. Every snippet is runnable. We'll explain why each design choice matter...
Learn ASP.NET Core output caching with real C# examples. Speed up API responses dramatically with policies, cache invalidation & Redis. Start caching today! If your API is hitting the database on every single request for data that barely changes, you are burning CPU, database connections, and money for nothing. ASP.NET Core output caching is one of the highest-impact, lowest-effort performance wins available in modern .NET: with a few lines of code, you can serve repeat requests in microseconds instead of milliseconds — often cutting response times by 90% or more and slashing database load dramatically. Output caching was introduced in .NET 7 as a first-class middleware and has matured significantly through .NET 8 and .NET 9, gaining built-in Redis support, tag-based invalidation, and clean integration with Minimal APIs and MVC controllers. In this tutorial, you will learn how output caching works, how it differs from response caching (a distinction that confuses even senior d...