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.NET Aspire and GenAI Develop Distributed Architectures
Rating: 4.5 out of 5(356 ratings)
2,253 students

.NET Aspire and GenAI Develop Distributed Architectures

Develop AI-Powered Distributed Architecture w/ PostgreSQL, Redis, RabbitMQ, Keycloak, Ollama, VectorDB using .NET Aspire
Created byMehmet Ozkaya
Last updated 5/2026
English

What you'll learn

  • Develop AI-Powered Distributed Architectures using .NET Aspire and GenAI
  • Cloud-Native Distributed Architectures
  • .NET Aspire Framework for Cloud-Native Distributed App Development
  • Building EShop Distributed Microservices Architecture with .NET Aspire
  • Messaging and Event-Driven Patterns with RabbitMQ
  • Develop Catalog Microservice with PostgreSQL orchestrate in .NET Aspire
  • Develop Basket Microservice with Redis orchestrate in .NET Aspire
  • Sync Communications between Catalog-Basket w/ .NET Aspire Service Discovery
  • Async Communications w/ RabbitMQ & MassTransit orchestrate .NET Aspire
  • Secure Basket with Keycloak Authentication orchestrate .NET Aspire
  • Develop Client Blazor Web Application
  • Azure Container Apps
  • Deploy EShop Aspire project to Azure Container Apps
  • .NET GenAI with Microsoft Extensions AI and Semantic Kernel

Course content

15 sections115 lectures7h 5m total length
  • Introduction6:57

    Build AI powered distributed architectures with dotnet aspire to create catalog and basket microservices, integrate PostgreSQL, Redis, RabbitMQ, Keycloak, and Semantic Kernel, and deploy to Azure Container Apps.

  • Prerequisites, Source Code and Course Slides2:28

    Review prerequisites and set up dotnet nine with Visual Studio 2022, ASP.Net web development, and the dotnet aspire workload. Install Docker Desktop; access GitHub source and lecture resources slides.

  • Course Project: EShop Microservices with AI-Powered Capabilities using LLMs2:27

    Set up and run the eShop microservices project, activating Postgres, Redis output caching, a distributed cache, RabbitMQ, and Keycloak, with catalog and basket services and a Blazor client.

Requirements

  • Basics of C# and Programming

Description

In this course, we are designing and implementing cloud-native distributed architectures using the .NET Aspire framework, while integrating Generative AI capabilities (GenAI) through Microsoft-Extensions-AI and Semantic Kernel.

From microservices fundamentals to Advanced AI-driven features, you’ll gain hands-on experience architecting an E-Shop system where Catalog and Basket microservices work in tandem using PostgreSQL, Redis and RabbitMQ for messaging.

You’ll also discover how to incorporate intelligent features such as Q&A chatbots and semantic product search, powered by Ollama’s Llama/Phi models and RAG (Retrieval-Augmented Generation) flows.

Throughout the course, you’ll learn:

Cloud-Native Distributed Architecture Essentials

  • Dive into microservices architecture, containerization, and the Twelve-Factor App methodology.

  • Learn best practices for resiliency, scalability, and DevOps workflows.

.NET Aspire Framework for Cloud-Native Development

  • Understand how .NET Aspire simplifies building distributed services.

  • Set up new projects, manage configurations, and apply cross-cutting concerns like logging and observability.

Catalog Microservice with PostgreSQL and RabbitMQ:

  • Store and manage product data in PostgreSQL.

  • Publish integration events (e.g., ProductPriceChanged) to RabbitMQ.

Basket Microservice with Redis:

  • Maintain fast, session-based data using Redis.

  • Syncs with the Catalog service when adding items to the basket.

  • Consume integration events from RabbitMQ to keep basket prices in sync.

  • Secure basket endpoints with Keycloak using JWT Bearer token.

Messaging and Event-Driven Patterns with RabbitMQ

  • Explore publish/subscribe patterns, exchanges, routing keys, and best practices for handling retries.

  • Implement robust error handling and ensure reliable event-driven communication across microservices.

Deployment, Security, and Observability

  • Containerize microservices and deploy them to Azure Container Apps using the azd up and azd down commands.

  • Follow .NET Aspire’s project structure for streamlined CI/CD workflows.

Introduction to .NET GenAI with Semantic Kernel

  • Discover the foundations of Generative AI and large language models (LLMs).

  • Integrate Microsoft-Extensions-AI and Semantic Kernel to power advanced AI functionalities.

Ollama, Llama, and Phi Models Setup

Install and configure Ollama locally or via containers.

Run Llama or Phi models for inference directly within your .NET microservices.

GenAI Use Cases in E-Shop

Customer Support Q&A Chatbot:

  • Leverage semantic kernel and prompt engineering for context-aware Q&A.

  • Integrate Ollama to deliver real-time responses to users’ questions.

Product Semantic Search with Vector Store (RAG Flow):

  • Generate embeddings for product data using Ollama’s All-MiniLM model.

  • Use a vector database to retrieve, rank, and deliver personalized product recommendations.

By the end of this course, you’ll have built a fully functional, AI-powered E-Shop platform that demonstrates the power of event-driven microservices coupled with .NET Aspire and GenAI

Who this course is for:

  • All Levels of .NET Developers who is curious about .NET Aspire and GenAI