.NET on AWS Blog

Introduction Imagine you want to create intelligent text summarization tools without managing infrastructure. How can you efficiently build AI-powered solutions that can transform lengthy documents into concise summaries? Amazon Bedrock, a fully managed service from AWS, addresses this challenge by optimizing text summarization through its Converse API. The Converse API provides a standardized interface for […]

Generative AI is taking chatbots to the next level by empowering them to engage in human-like dialogues. These advanced conversational agents understand and respond to complex queries, provide personalized assistance, and even generate creative content. This blog post shows how to build a context-aware chatbot using Amazon Bedrock and LangChain in a .NET environment. The choice […]

Introduction This blog series explores how to port different kinds of .NET Framework projects to cross-platform .NET with Amazon Q Developer .NET transformation, currently in public preview. Modernizing a Windows-based .NET Framework solution to run on Linux can reduce operational costs by up to 40%. Part 1 covered porting of class library projects. Here in […]

Ulili Nhaga contributed to this article. When building applications, ensuring proper security and access control is crucial. One way to achieve this is by implementing a Role-Based Access Control (RBAC) authorization system. This blog post will discuss implementing RBAC for .NET applications using Amazon Cognito with OpenID Connect (OIDC). We will guide you on how […]

Amazon Q Developer is a generative AI-powered assistant that automates software documentation by analyzing codebases, creating and updating README files, generating visual diagrams, and providing detailed technical documentation, helping development teams maintain current documentation without sacrificing development velocity.

Introduction Large language models (LLMs) are driving the rapid growth of semantic search applications. Semantic search understands both user intent and content context, rather than just matching keywords. LLMs enhance this capability through their advanced language processing abilities. These AI models can process multiple content formats, including text, images, audio, and video. The users receive […]

Razvan Pat contributed to this article. Introduction As .NET developers, we often find ourselves at a crossroads when venturing into the world of machine learning and AI. While Python dominates this space, what if you could leverage your C# skills in a powerful machine learning (ML) environment? That’s exactly what we’re exploring today: how to […]

Introduction In the .NET world, the modernization process for .NET Framework applications can be complex, presenting significant challenges for enterprise software development teams. Organizations with extensive .NET Framework codebases face critical decisions about migrating traditional applications to modern .NET and Linux, including careful analysis of dependencies and how to handle compatibility constraints. Existing libraries may […]

Observability has become a crucial aspect of modern software development, enabling developers to gain insights into the behavior and performance of their applications. The OpenTelemetry project, a Cloud Native Computing Foundation (CNCF) hosted project, has emerged as a powerful solution for generating, collecting, and exporting telemetry data, providing a vendor-neutral and standardized approach to observability. […]

Introduction When interacting with a large language model (LLM), its knowledge comes from data used during its training, which is often mostly from public sources. As a result, the model’s knowledge may not fully reflect the most current information. This leads to three main issues: outdated information, no access to internal company data, and potential […]