AI-Native Microservices Architecture with .NET & Containers
Certificate of Completion by Code.Hub
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.
By the end of this module, 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
- Roles: .NET Developer, Backend Developer, Software Engineer, ΑI Engineer
- Seniority: Mid
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
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
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
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
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
Monitoring & Logging
Centralized logging
Tracing distributed systems
Observability tools
AI Practice: Generate logging strategy using AI
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
- Roles: .NET Developer, Backend Developer, Software Engineer, ΑI Engineer
- Seniority: Mid
- Experience with C#, ASP.NET Core, and basic microservices or Web API concepts
- Familiarity with Docker fundamentals and general software architecture principles
Sessions can be delivered via the following formats:
- Live Online – Interactive virtual sessions via video conferencing
- On-Site – At your organization’s premises
- In-Person – At Code.Hub’s training center
- Hybrid – A combination of online and in-person sessions
Interested for
