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AI-Assisted Microservices with Spring Cloud

Description

This advanced course teaches developers how to build, integrate, and manage microservices using Spring Boot and Spring Cloud. Participants will gain hands-on experience in creating resilient, scalable services fit for modern cloud-native applications.

 

🕒 Duration: 38 hours

👥 Target Audience:

  • Roles: Backend Developers, Software Engineers, DevOps Engineers
  • Seniority: Mid- to senior-level professionals building cloud-native or enterprise applications
Webinar Content
Module 1: Introduction to Microservices
  • History flashback; The evolution of software design & architecture
  • Monolithic Applications
  • Service Oriented Architecture (SOA)
  • Microservices design considerations
  • CQRS
  • Saga Pattern
  • Overview of key architectural components covering needs such as Distributed/versioned Configuration, Service registration and discovery, Routing, Service-to-service calls, Load balancing.
Module 2: Project setup, design
& implementation
  • A Journey from Monolithic Applications to Microservices
  • Demonstration project source code go through
  • Go through project structure and internal architecture

 

  • AI showcase: explore and explain the monolith project structure and architectural layers
  • Revisit project structure to facilitate the transition to microservices, resolve dependencies, setup build mechanism
  • Refactor source code and how to preserve existing architectural layers (Controller, Service, Repository)

 

  • AI showcase: demonstrate scaffolding a new microservice module and reviewing the refactored layer structure
Module 3: Spring Cloud
  • Service Discovery using Eureka
  • Rest Clients using Feign
  • Client-side Load Balancing

 

  • ΑΙ showcase: generate a Feign client interface and Eureka configuration from scratch
  • Gateway (Load Balancing, Predicates, Filters etc)

 

  • ΑΙ showcase: set up gateway route and filter configurations live
  • Centralized Configuration using Config Server serving multiple environments (e.g. Development, QA, Production)

 

  • ΑΙ showcase: scaffold environment-specific config files for all three environments
  • Distributed Tracing using Sleuth and Zipkin

 

  • ΑΙ showcase: instrument a service with tracing and interpret the output
  • Fault Tolerance and Circuit Breaker with Resilience4j

 

  • ΑΙ showcase: generate a circuit breaker pattern with fallback handler

 

Learning Objectives:

After attending this webinar participants will be able to:

  • Design and build scalable microservices using Spring Boot.
  • Implement service discovery, load balancing, and fault tolerance with Spring Cloud.
  • Use API gateways, configuration servers, and centralized logging for microservice management.
  • Apply communication patterns such as REST and asynchronous messaging (e.g., RabbitMQ/Kafka).
  • Deploy and monitor microservices in distributed environments using industry best practices.
Prerequisite Knowledge
  • Strong Java programming skills
  • Working knowledge of Spring Boot
  • Basic understanding of REST APIs and distributed systems
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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