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AI-Native Microservices Architecture with .NET & Containers

Description

This course focuses on designing and implementing AI-native microservices architectures using .NET and container technologies. Participants will learn how to build distributed systems where AI capabilities are first-class components, integrated into services for intelligent decision-making and automation. The course covers microservices principles, containerization with Docker, orchestration patterns, and communication strategies across services. It also explores how to embed LLM-powered features such as reasoning, RAG, and tool invocation within microservices. Hands-on labs demonstrate how to design scalable, resilient systems using ASP.NET Core, messaging systems, and container platforms. Emphasis is placed on observability, security, and performance in AI-enabled distributed environments. By the end of the training, participants will be able to architect and deploy production-ready AI-native microservices systems.

 

🕒 Duration: 24 hours

👥 Target Audience:

  • Roles: .NET Developer, Backend Developer, Software Engineer, ΑI Engineer

 

  • Seniority: Mid
Webinar Content

 

Module 1: Foundations of AI-Native Architecture
 Introduction to Microservices
&
AI-Native Systems
  • Microservices principles and benefits
  • Monolith vs microservices
  • What makes a system “AI-native”

 

  • AI Practice: Use AI to decompose a monolith into microservices
ASP.NET Core Microservices Setup
  • Creating microservices with ASP.NET Core
  • Project structure and APIs
  • Service boundaries

 

  • AI Practice: Generate microservice scaffolding using Copilot
Module 2: Containerization
 Docker Fundamentals
  • Containers vs VMs
  • Docker images and containers
  • Dockerfiles for .NET apps

 

  • AI Practice: Generate Dockerfile for a .NET microservice
Docker Compose for Multi-Service Systems
  • Defining multi-container systems
  • Networking and volumes
  • Service dependencies

 

  • AI Practice: Create docker-compose setup with multiple services
Module 3: Communication Patterns
 Synchronous Communication
  • REST APIs between services
  • API gateways
  • Service discovery basics

 

  • AI Practice: Design API contracts using AI
Asynchronous Communication
  • Messaging patterns
  • Event-driven architecture
  • Intro to RabbitMQ or Kafka

 

  • AI Practice: Generate event schema and messaging flow
Module 4: AI Integration
 Integrating LLMs into Microservices
  • Calling AI services from APIs
  • Prompt orchestration
  • Stateless vs stateful AI services

 

  • AI Practice: Build AI-enabled microservice endpoint
RAG in Microservices
  • Retrieval pipelines per service
  • Vector DB integration
  • Context-aware services

 

  • AI Practice: Implement simple RAG microservice
Module 5: Advanced Patterns
 Multi-Service AI Workflows
  • Orchestration across services
  • Chaining AI tasks
  • Introduction to agents

 

  • AI Practice: Design multi-step workflow with AI orchestration
Resilience & Fault Tolerance
  • Retry, circuit breakers
  • Handling AI failures
  • Distributed system challenges

 

  • AI Practice: Add resilience patterns to services
Module 6: Observability & Security Monitoring & Logging
  • Centralized logging
  • Tracing distributed systems
  • Observability tools

 

  • AI Practice: Generate logging strategy using AI
Module 7: Deployment & Capstone Deployment & End-to-End System
  • Deploying to cloud (Azure/Kubernetes basics)
  • End-to-end system integration
  • Final project

 

  • AI Practice: Build and deploy AI-native microservices system
Learning Objectives:

After attending this webinar participants will be able to:

  • Design and implement AI-native microservices using ASP.NET Core and containerization
  • Integrate LLM capabilities into microservices for intelligent workflows and automation
  • Build distributed systems with messaging, service communication, and orchestration patterns
  • Apply observability, resilience, and security practices in containerized environments
  • Deploy and manage scalable microservices architectures using Docker and cloud platforms
Prerequisite Knowledge
  • Experience with C#, ASP.NET Core, and basic microservices or Web API concepts
  • Familiarity with Docker fundamentals and general software architecture principles

 

Tags:

Date

28 May 2026, 16:00-19:00

Cost

Free

Labels

AI-Native
Category

Organizer

Code.Hub
Email
[email protected]

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