.NET Aspire and GenAI Develop Distributed Architectures 2025

Build Scalable Cloud-Native Applications with .NET Aspire and Generative AI

This comprehensive course guides you through the design and implementation of robust, cloud-native distributed architectures using the powerful .NET Aspire framework. You'll gain practical experience integrating cutting-edge Generative AI (GenAI) capabilities with Microsoft-Extensions-AI and Semantic Kernel, transforming your applications with intelligent features.

Key Concepts & Technologies:

• Microservices Architecture: Master the fundamentals of microservices, including containerization and the Twelve-Factor App methodology. Learn best practices for building resilient, scalable, and maintainable systems with effective DevOps workflows.
• .NET Aspire Framework: Discover how .NET Aspire simplifies the development of distributed services. You'll learn to set up new projects, manage configurations, and implement crucial cross-cutting concerns like logging and observability.
• Event-Driven Architecture with RabbitMQ: Explore messaging and event-driven patterns using RabbitMQ. Understand publish/subscribe, exchanges, routing keys, and implement reliable event communication with robust error handling.
• PostgreSQL & Redis Integration: Learn to effectively use PostgreSQL for persistent data storage and Redis for fast, session-based data management. See how these technologies work together in a distributed environment.
• Security with Keycloak & JWT: Secure your application endpoints using Keycloak and JWT Bearer tokens for authentication and authorization.
• Containerization & Deployment: Containerize your microservices and deploy them to Azure Container Apps using command-line tools. Follow .NET Aspire’s project structure for streamlined CI/CD pipelines.
• Generative AI (GenAI) with Semantic Kernel: Delve into the foundations of Generative AI and Large Language Models (LLMs). Integrate Microsoft-Extensions-AI and Semantic Kernel to unlock advanced AI functionalities.

Hands-on Projects & AI Use Cases:

• E-Shop System: Architect and build a complete E-Shop system featuring interconnected Catalog and Basket microservices.
• Catalog Microservice (PostgreSQL & RabbitMQ): Store and manage product data in PostgreSQL. Publish integration events (e.g., ProductPriceChanged) to RabbitMQ for real-time updates.
• Basket Microservice (Redis): Maintain fast, session-based data using Redis. Synchronize with the Catalog service when adding items to the basket. Consume events from RabbitMQ to keep basket prices consistent.
• Customer Support Q&A Chatbot: Build a context-aware Q&A chatbot using Semantic Kernel and prompt engineering. Integrate Ollama for real-time responses.
• Product Semantic Search with RAG: Implement semantic product search using a vector store and Retrieval-Augmented Generation (RAG) flows. Generate embeddings for product data using Ollama’s All-MiniLM model and retrieve personalized product recommendations.

Generative AI Implementation:

• Ollama, Llama, and Phi Models: Learn to install and configure Ollama locally or via containers. Run Llama or Phi models directly within your .NET microservices for inference.

By the end of this course, you'll be able to:

• Build a fully functional, AI-powered E-Shop platform demonstrating the power of event-driven microservices, .NET Aspire, and Generative AI.
• Design and implement scalable, resilient, and secure cloud-native applications.
• Leverage GenAI to enhance customer experiences and improve business processes.