Microservice Architecture

Overview:

Introduction:

Microservice Architecture is a modern approach to designing scalable and independent services within complex applications. This training program introduces participants to the core concepts, design patterns, and tools essential for building and managing microservices effectively.

Program Objectives:

By the end of this program, participants will be able to:

• Understand the core principles and advantages of microservice architecture.

• Design and develop microservices using proven design patterns.

• Implement reliable inter-service communication and data handling techniques.

• Monitor, troubleshoot, and optimize microservice applications.

• Apply best practices for deployment, scaling, and production management.

Targeted Audience:

• Software architects and system designers.

• Backend and full-stack developers.

• DevOps and site reliability engineers (SREs).

• IT professionals involved in cloud-native or distributed system development.

Program Outline:

Unit 1:

Introduction to Microservice Architecture:

• Definition and principles of microservice architecture.

• Benefits and common challenges of adopting microservices.

• Comparison of monolithic and microservice architectures.

• Key components of microservice-based systems.

• Real-world applications and case studies.

Unit 2:

Designing Microservices:

• Applying domain-driven design to microservices.

• Identifying service boundaries and responsibilities.

• Designing RESTful and RPC APIs.

• Communication patterns (REST, gRPC, messaging).

• Data handling strategies: Database-per-service, CQRS, event sourcing.

Unit 3:

Developing Microservices:

• Selecting suitable technology stacks and frameworks.

• Building services using tools like Spring Boot, Node.js.

• Service discovery and client-side load balancing.

• Implementing authentication and authorization.

• Writing unit and integration tests for microservices.

Unit 4:

Deploying and Managing Microservices:

• Containerization using Docker.

• Kubernetes for orchestration and scaling.

• CI/CD pipelines for automated deployment.

• Using service mesh tools like Istio or Linkerd.

• Monitoring and logging with Prometheus, ELK, and Grafana.

Unit 5:

Optimization and Best Practices:

• Performance tuning and resource optimization.

• Implementing resiliency: Circuit breakers, retries, timeouts.

• Scaling services horizontally and vertically.

• Managing transactions and data consistency.

• Trends: Serverless microservices, API gateways, and observability.