.NET Aspire and GenAI Develop Distributed Architectures 2025

Develop AI-Powered Distributed Architecture w/ PostgreSQL, Redis, RabbitMQ, Keycloak, Ollama, VectorDB using .NET Aspire

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