Evolutionary Paths. Software Architecture for developers

TRAINING DESCRIPTION

This training explores how to evolve software systems and architectures iteratively, introducing complexity only when necessary. Participants will gain insight into the Natural Course of Refactoring and the Natural Course of Architecture Design as guiding principles for creating maintainable, scalable systems. The training includes practical examples and evolutionary paths to help participants transition from simple flat architectures to complex distributed systems.

Key topics include architectural drivers, application design, data access strategies, integration patterns, SecOps practices, and data processing techniques. The program emphasizes real-world applicability and balancing simplicity with long-term scalability.

Enroll Now, Warsaw, 16.05.2025 Order dedicated training

BASIC PROGRAM

  • Module 1: Evolutionary Software Engineering
  • Module 2: Natural Course of Refactoring
  • Module 3: Natural Course of Architecture Design
  • Module 4: Evolutionary Paths for Architecture Development
  • Module 5: Applying Evolutionary Paths in Real-Life Projects
  • Module 6: Evolution Paths

DETAILED PROGRAM

Module 1: Evolutionary Software Engineering

  • Challenges in Software Architecture Design:

    • Common pitfalls in architectural decision-making
    • Overengineering vs. simplicity in early-stage projects
    • Trade-offs of avoiding complex architectures initially

  • Defensive Architecture and Complexity:

    • Risks of upfront architectural decisions
    • Examples of unnecessary complexity slowing down projects

  • Evolutionary Approach:

    • Starting with simple solutions and evolving them iteratively
    • Balancing domain-driven simplicity with scalability and flexibility

Module 2: Natural Course of Refactoring

  • Refactoring Strategies:

    • Moving from simple solutions to evolved architectures
    • Using heuristics to decide when to apply design patterns
    • Emphasizing simplicity at the beginning of feature development

  • Practical Refactoring Examples:

    • Quadratic equation solution: from simple to modular
    • Library system: implementing iterative refactoring techniques

Module 3: Natural Course of Architecture Design

  • Guidelines for Architectural Evolution:

    • Evolution as a guideline rather than a strict pattern
    • Transitioning from monolithic to distributed systems

  • Phases of Architectural Evolution:

    • Starting with flat architectures
    • Gradually introducing layers, modules, and distribution

Module 4: Evolutionary Paths for Architecture Development

  • Starting Point: Flat Architecture

    • Transformation
    • Design
    • Testing
    • Introducing changes
    • Scalability
    • Deployment

  • Introducing Layers

    • Transformation
    • Design
    • Testing
    • Introducing changes
    • Scalability
    • Deployment

  • Modularizing the System

    • Transformation
    • Design
    • Testing
    • Introducing changes
    • Scalability
    • Deployment

  • Towards Simpler Distribution

    • Transformation
    • Design
    • Testing
    • Introducing changes
    • Scalability
    • Deployment

  • Towards More Complex but the Most Powerful Distribution

    • Transformation
    • Design
    • Testing
    • Introducing changes
    • Scalability
    • Deployment

Module 5: Applying Evolutionary Paths in Real-Life Projects

  • Integrating with Other Systems:

    • Managing external dependencies during evolution
    • Adapting evolutionary paths to integration needs

  • Mixing Phases:

    • Combining evolutionary stages for specific project goals
    • Balancing immediate needs with long-term scalability

Module 6: Evolution Paths

  • Architectural Drivers:

    • Project types
    • Problem types

  • Application:

    • Domain model
    • Application logic
    • Processes and state machines
    • Transactions

  • Data Access:

    • Persistence strategies
    • Storage solutions
    • Read optimization techniques
    • Search-oriented architectures

  • Integration:

    • Integration patterns and transfer models
    • Events and event-driven architecture
    • Building resilience into integrations

  • SecOps:

    • CI/CD pipelines
    • Containerization strategies
    • Monitoring practices
    • Tracing and debugging tools
    • Security considerations

  • Data Processing:

    • Data transformation techniques
    • Handling and optimizing data processing workflows