Are you ready to learn about building your very own AI apps in Azure? Participate in the Microsoft Developers AI Learning Hackathon and discover how to build your own custom AI copilot using Azure Cosmos DB for MongoDB and the Azure OpenAI API.
Welcome to Part 9 of our Azure Cosmos DB Design Patterns series, focusing on Schema Versioning. This edition is particularly useful for those new to NoSQL databases or looking to understand Azure Cosmos DB’s unique capabilities. Here, we will explore how schema versioning can help manage and evolve your database schema efficiently,
Abandoning the background work if we know that it is pointless.
Literally, I just said that! I have three daughters, and it’s amazing how they ask me the same questions over and over. I don’t mind answering them, but I sure wish they would either remember my answer or, at least, write it down.
With our recent 1.19 release, performance was our biggest focus for the C++ Extension in Visual Studio Code. This included features like progressive population of IntelliSense results and faster symbol searching. With these enhancements, you can begin writing C++ code when opening a file quicker than ever before.
Join us on April 30th for a full day of online training and discover the latest services and features in Azure designed specifically for .NET developers.
In a previous article I already mentioned how vectors can be easily stored in Azure SQL already and how to calculate dot product and cosine distance using just T-SQL. In this article I will show how to improve the performance in vector search by using a technique that has many name but is really based on something very well know already: KMeans Clustering.
As we approach a stable v1.0 version of the Python Semantic Kernel SDK, we analysed the methods used to add plugins and functions to the kernel. We realised that the variety of available methods might confuse developers. For instance, when should one use import_plugin_from_object() versus import_native_plugin_from_directory()?
