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 how to build a multi-cloud strategy for .NET apps across AWS, Azure, and GCP with C# code examples. Start deploying cloud-agnostic apps today. Why a Multi-Cloud Strategy Matters for .NET Developers in 2026 A multi-cloud strategy — running your applications across AWS, Azure, and Google Cloud Platform (GCP) at the same time — has moved from a "nice to have" buzzword to a board-level requirement. Surveys consistently show that over 85% of enterprises now use more than one cloud provider, and .NET teams are right in the middle of that shift. Whether it's regulatory pressure in the UK and EU, avoiding vendor lock-in in the US market, or cost arbitrage between regions in India and Australia, the ability to run the same .NET application on multiple clouds is a genuine competitive advantage. The good news: modern .NET (8, 9, and 10) is arguably the best-positioned enterprise stack for multi-cloud. It's cross-platform, container-first, and has first-class SDKs ...