Domain Driven Design: Concepts and Practices

• An understanding of object-oriented programming and design patterns
• Experience with C# and .NET Core
• Basic knowledge of databases and SQL

Audience

• Developers
• Architects
• Analysts

Domain Driven Design (DDD) is a software development approach that focuses on the domain and the business logic, rather than the technical details. DDD helps to create software that is more maintainable, testable, and aligned with the business needs and goals.

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers, architects, and analysts who wish to learn and apply DDD concepts and practices to their software projects.

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

• Grasp core DDD concepts (bounded contexts, entities, etc.) and their application in software projects.
• Apply strategic DDD to define and design the domain model, identify subdomains, and establish boundaries.
• Implement tactical DDD using patterns such as CQRS, factories, and event sourcing.
• Refactor and modernize legacy systems effectively with DDD techniques.
• Design and implement product, domain, and team-oriented architectures.
• Utilize data mesh to create a domain-oriented data platform supporting data discovery and governance.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

• What is Domain Driven Design (DDD) and its benefits?
• DDD vs other approaches
• Overview of DDD concepts and project structure

Tactical Domain-Driven Design

• Elements of a domain model
• Implementing entities, value objects, aggregates, repositories, and domain services
• Using factories, specifications, CQRS, and event sourcing

Strategic Domain-Driven Design

• Context map patterns
• Designing the domain model with event storming and domain storytelling
• Identifying and classifying subdomains
• Establishing boundaries and relationships with patterns like bounded contexts

DDD & Legacy Workshop

• Challenges and opportunities of legacy systems
• Analyzing and understanding legacy systems with tools like NDepend
• Refactoring and modernizing legacy systems using techniques such as strangler pattern

Product, Domain & Team-oriented Architecture

• Benefits and challenges of product, domain, and team-oriented architecture
• Designing and implementing such architectures with patterns like microservices
• Organizing and collaborating with teams
• Ensuring quality and consistency with automated testing and continuous integration

Data Mesh – Domain-Oriented Data

• Problems with traditional data platforms
• Introduction to data mesh
• Implementing a domain-oriented data platform supporting data discovery, access, and governance
• Technologies like Apache Kafka, Apache Spark, and GraphQL in data mesh

Summary and Next Steps