Event 1

Summary Report: “GenAI-powered App-DB Modernization workshop”

Event Objectives

  • Share best practices in modern application design
  • Introduce Domain-Driven Design (DDD) and event-driven architecture
  • Provide guidance on selecting the right compute services
  • Present AI tools to support the development lifecycle

Speakers

  • Jignesh Shah – Director, Open Source Databases
  • Erica Liu – Sr. GTM Specialist, AppMod
  • Fabrianne Effendi – Assc. Specialist SA, Serverless Amazon Web Services

Key Highlights

Identifying the drawbacks of legacy application architecture

  • Long product release cycles → Lost revenue/missed opportunities
  • Inefficient operations → Reduced productivity, higher costs
  • Non-compliance with security regulations → Security breaches, loss of reputation

Transitioning to modern application architecture – Microservices

Migrating to a modular system — each function is an independent service communicating via events, built on three core pillars:

  • Queue Management: Handle asynchronous tasks
  • Caching Strategy: Optimize performance
  • Message Handling: Flexible inter-service communication

Domain-Driven Design (DDD)

  • Four-step method: Identify domain events → arrange timeline → identify actors → define bounded contexts
  • Bookstore case study: Demonstrates real-world DDD application
  • Context mapping: 7 patterns for integrating bounded contexts

Event-Driven Architecture

  • 3 integration patterns: Publish/Subscribe, Point-to-point, Streaming
  • Benefits: Loose coupling, scalability, resilience
  • Sync vs async comparison: Understanding the trade-offs

Compute Evolution

  • Shared Responsibility Model: EC2 → ECS → Fargate → Lambda
  • Serverless benefits: No server management, auto-scaling, pay-for-value
  • Functions vs Containers: Criteria for appropriate choice

Amazon Q Developer

  • SDLC automation: From planning to maintenance
  • Code transformation: Java upgrade, .NET modernization
  • AWS Transform agents: VMware, Mainframe, .NET migration

Key Takeaways

Design Mindset

  • Business-first approach: Always start from the business domain, not the technology
  • Ubiquitous language: Importance of a shared vocabulary between business and tech teams
  • Bounded contexts: Identifying and managing complexity in large systems

Technical Architecture

  • Event storming technique: Practical method for modeling business processes
  • Use event-driven communication instead of synchronous calls
  • Integration patterns: When to use sync, async, pub/sub, streaming
  • Compute spectrum: Criteria for choosing between VM, containers, and serverless

Modernization Strategy

  • Phased approach: No rushing — follow a clear roadmap
  • 7Rs framework: Multiple modernization paths depending on the application
  • ROI measurement: Cost reduction + business agility

Applying to Work

  • Apply DDD to current projects: Event storming sessions with business teams
  • Refactor microservices: Use bounded contexts to define service boundaries
  • Implement event-driven patterns: Replace some sync calls with async messaging
  • Adopt serverless: Pilot AWS Lambda for suitable use cases
  • Try Amazon Q Developer: Integrate into the dev workflow to boost productivity

Event Experience

Attending the “GenAI-powered App-DB Modernization” workshop was extremely valuable, giving me a comprehensive view of modernizing applications and databases using advanced methods and tools. Key experiences included:

Learning from highly skilled speakers

  • Experts from AWS and major tech organizations shared best practices in modern application design.
  • Through real-world case studies, I gained a deeper understanding of applying DDD and Event-Driven Architecture to large projects.

Hands-on technical exposure

  • Participating in event storming sessions helped me visualize how to model business processes into domain events.
  • Learned how to split microservices and define bounded contexts to manage large-system complexity.
  • Understood trade-offs between synchronous and asynchronous communication and integration patterns like pub/sub, point-to-point, streaming.

Leveraging modern tools

  • Explored Amazon Q Developer, an AI tool for SDLC support from planning to maintenance.
  • Learned to automate code transformation and pilot serverless with AWS Lambda to improve productivity.

Networking and discussions

  • The workshop offered opportunities to exchange ideas with experts, peers, and business teams, enhancing the ubiquitous language between business and tech.
  • Real-world examples reinforced the importance of the business-first approach rather than focusing solely on technology.

Lessons learned

  • Applying DDD and event-driven patterns reduces coupling while improving scalability and resilience.
  • Modernization requires a phased approach with ROI measurement; rushing the process can be risky.
  • AI tools like Amazon Q Developer can significantly boost productivity when integrated into the current workflow.