Accelerate Modernization at Scale: From Legacy to Cloud-Native with AI

Session Date: Microsoft Build 2025
Duration: ~45 minutes
Venue: Build 2025 Conference - BRK199
Speakers: Mohammad Nofal (Global Black Belt Lead, Microsoft), Anoop Iyer (Director, Business Strategy, Microsoft), Michael Yen-Chi Ho (Senior Product Manager, Microsoft), Bryce Hunt (Founding GTM Engineer, Cognition AI), Tinius Alexander Lystad (CTO, Visma AS)
Link: [Microsoft Build 2025 Session BRK199]

App Modernization at Scale

Executive Summary

This session demonstrates how organizations can transform legacy systems into agile, cloud-native solutions at enterprise scale using AI-powered tools. The presentation showcases end-to-end modernization workflows using GitHub Copilot, Devin AI agent, and Azure’s comprehensive modernization guidance, featuring real-world case studies and live demonstrations of automated code transformation.

Key Topics Covered

?? 1. The AI-Driven Modernization Imperative

Core Concept: Every application will be reinvented with AI, making modernization essential for AI adoption at scale.

Key Motivations:

  • Performance improvements through modern frameworks and PaaS services
  • Security enhancements via latest patches and reduced attack surfaces
  • Feature accessibility - newer frameworks unlock modern capabilities
  • Operational efficiency through automated infrastructure management
  • Cost optimization via cloud-native architectures

AI-Powered Development Lifecycle:

  • Inner loop: Developer + IDE with GitHub Copilot integration
  • Outer loop: Software Engineering Agent for broader automation
  • Third loop: SRE Agent for observability and operational excellence

?? 2. Cloud-Native Architecture Pillars

Four Foundational Pillars

1. Containers

  • Build once, manage and scale anywhere
  • Backbone of microservices architectures
  • Platform-agnostic deployment models

2. Serverless Computing

  • Infrastructure abstraction for developer focus on business logic
  • Automatic provisioning, scaling, and cost optimization
  • Event-driven architecture enablement

3. Data Ecosystem Intelligence

  • Comprehensive connectivity to analytics and intelligence services
  • Multi-database support (SQL Server, MySQL, PostgreSQL, Cosmos DB)
  • Real-time data processing capabilities

4. API-First Development

  • Accelerated application connectivity and data sharing
  • Ecosystem integration and monetization opportunities
  • Developer productivity through standardized interfaces

?? 3. Application Modernization Framework

Comprehensive Modernization Guidance

Microsoft’s new App Modernization Guidance provides step-by-step transformation methodology for the AI era.

Modernization Categories

Code & Language Platform Modernization:

  • Framework upgrades (Java 8 ? Java 21, .NET Framework ? .NET 8)
  • Dependency management (NuGet packages, Maven dependencies)
  • Code refactoring for cloud compatibility
  • Configuration externalization (local files ? Azure Blob Storage)

Replatforming to Azure:

  • Containerization and deployment to AKS/Container Apps
  • Database migration (on-premises ? managed cloud services)
  • Cross-cloud migration (AWS ? Azure PaaS)

Refactor & Rearchitect:

  • Monolith decomposition into microservices
  • Event-driven architecture adoption
  • API-first design implementation

Process Modernization:

  • DevOps transformation with modern tooling
  • Security modernization via zero-trust architecture

?? 4. AI-Powered Modernization Tools

GitHub Copilot App Modernization Extension

Capabilities:

  • Automated assessment using integrated AppCAT tool
  • Framework upgrades with OpenRewrite integration
  • Custom formula creation for repeatable transformations
  • End-to-end deployment to Azure services

Live Demo Results (Java Application - Airsonic):

  • Assessment time: 3-5 minutes (previously days of manual analysis)
  • Framework upgrade: Java 8 ? Java 21 with automated dependency resolution
  • Code transformation: Logging, authentication, and configuration modernization
  • Deployment: Automated Bicep file generation and Azure Container Apps deployment

Cognition Devin AI Agent

Agent Architecture:

  • Cloud-based execution in isolated virtual environments
  • Parallel processing multiple tasks simultaneously
  • End-to-end automation from analysis to PR creation
  • Integration with Microsoft .NET Upgrade Assistant

Productivity Gains:

  • 6X to 12X improvement for repetitive migration tasks
  • Autonomous workflow from requirements to deployed code
  • Error handling and recovery without human intervention
  • Collaborative feedback loop via GitHub integration

?? 5. Enterprise Case Study: Visma’s Modernization at Scale

Organization Context

  • 190 software companies across Europe and Latin America
  • 400+ SaaS products serving SMBs and public sector
  • Strategic AI adoption across entire development organization

Modernization Process

1. Data-Driven Selection:

  • Portfolio analysis identifying legacy technology stacks
  • Business strategy alignment for modernization candidates
  • Cost-benefit analysis using older frameworks and expensive databases

2. Three-Day Workshop Methodology:

  • Collaborative planning with development teams
  • Tool selection and process definition
  • Vertical slice modernization proof-of-concept
  • Knowledge transfer and team enablement

3. Autonomous Execution:

  • Development teams take full ownership post-workshop
  • Code and infrastructure modernization in parallel
  • Database technology migrations and cloud adoption

Flex HRM Case Study Results

Technical Transformation:

  • 3 million lines of code modernized from .NET Framework ? .NET 8
  • 30 developers achieving 100% AI tool adoption
  • Azure App Service deployment with Linux hosting
  • 40% reduction in migration effort through AI assistance

Business Impact:

  • �600,000 annual savings in hosting and licensing costs
  • Significant performance improvements over legacy system
  • Enhanced developer engagement and job satisfaction
  • Accelerated feature development capability

Future Roadmap:

  • PostgreSQL migration for further cost optimization
  • Mobile application modernization
  • Microservices architecture decomposition
  • AI agent integration for automated issue resolution

?? 6. AI Tool Integration Ecosystem

Developer Experience Spectrum

Level 1: Real-Time Assistance

  • GitHub Copilot autocomplete and suggestions
  • 20-40% productivity improvements
  • Synchronous workflow enhancement

Level 2: IDE-Embedded AI

  • Contextual code analysis and recommendations
  • File-level understanding and transformation
  • Interactive development companion

Level 3: End-to-End Autonomy

  • Task delegation to AI agents (Devin)
  • Complete workflow automation from PRD to deployment
  • Asynchronous, parallel task execution

Technical Implementation Architecture

Microsoft.Extensions.AI Integration:

  • Unified approach to AI service consumption
  • Custom formula development for organization-specific patterns
  • Integration with existing Visual Studio and VS Code workflows

Multi-Platform Support:

  • Java modernization with OpenRewrite integration
  • .NET modernization with built-in upgrade tooling
  • Database schema migration capabilities (upcoming)
  • Cross-platform deployment automation

?? 7. Measurable Business Outcomes

Productivity Metrics

  • Weeks/months ? hours/days for framework upgrades
  • Manual code analysis eliminated through automated assessment
  • Parallel processing enabling simultaneous modernization efforts
  • Standardized approaches reducing learning curves for teams

Cost Optimization Results

  • 20-50% hosting cost reductions through cloud-native architectures
  • Eliminated licensing costs via open-source alternatives
  • Operational burden reduction through managed services adoption
  • Developer time reallocation to high-value business logic

Risk Mitigation

  • Automated testing integration throughout modernization process
  • Transparent change tracking with git-based workflows
  • Rollback capabilities via checkpoint commits
  • Validation frameworks ensuring functional equivalence

?? 8. Strategic Implementation Roadmap

Phase 1: Discovery & Assessment

  • Estate discovery using Azure Migrate and Dr. Migrate tools
  • Criticality matrix development based on business value, urgency, and complexity
  • Modernization wave planning with strategic prioritization

Phase 2: Proof of Concept

  • Three-day workshop methodology for team enablement
  • Vertical slice modernization to validate approach
  • Tool evaluation and process refinement

Phase 3: Factory Model Implementation

  • Infrastructure as Code standardization
  • DevOps modernization with automated pipelines
  • Cloud-native technology adoption at scale

Phase 4: Continuous Optimization

  • Monitoring and observability integration
  • Performance optimization based on insights
  • Cost management and right-sizing
  • Security and compliance automation

Technical Deep Dive Insights

AI-Assisted Code Transformation Process

Assessment Phase:

  • Automated dependency analysis and vulnerability scanning
  • Framework compatibility evaluation
  • Migration complexity scoring
  • Resource requirement estimation

Transformation Phase:

  • Formula-based pattern application
  • Build validation and error resolution
  • Automated testing execution
  • Configuration externalization

Deployment Phase:

  • Infrastructure as Code generation
  • Azure service provisioning
  • Monitoring and observability setup
  • Performance validation

Integration with Microsoft Ecosystem

Azure Platform Services:

  • App Service, Container Apps, AKS integration
  • Managed database service connectivity
  • API Management for service exposure
  • Azure Functions for event-driven workloads

Development Toolchain:

  • Visual Studio family (50 million professional developers)
  • GitHub integration for source control and CI/CD
  • Azure DevOps for enterprise development workflows
  • Defender for DevOps security integration

Session Highlights

“Every app will be reinvented with AI, and new apps will be built with the aid of generative AI. The key word is ‘every’ - because every means scale.” - Mohammad Nofal

“If it’s painful to move, then it’s probably painful to keep.” - Mohammad Nofal

“We’re seeing 6X to 12X improvements for highly repetitive, tedious, manual migration work through AI agents.” - Bryce Hunt

“We see 30% to 75% reduction in human effort for code modernization, with 20% to 50% cost savings in hosting and licenses.” - Tinius Alexander Lystad

Practical Implementation Guidelines

Immediate Actions

  1. Install GitHub Copilot App Modernization extension for VS Code
  2. Assess current application portfolio using Azure Migrate tools
  3. Identify modernization candidates based on business value and technical complexity
  4. Experiment with Devin AI agent for proof-of-concept modernization

Strategic Planning

  1. Develop modernization waves based on criticality matrix
  2. Implement workshop methodology for team enablement and knowledge transfer
  3. Establish factory model with Infrastructure as Code and automated pipelines
  4. Create feedback loops for continuous improvement and optimization

Success Factors

  1. Developer upskilling investment to maximize AI tool effectiveness
  2. Executive sponsorship for large-scale transformation initiatives
  3. Pilot project validation before enterprise-wide rollout
  4. Cultural change management supporting AI-assisted development workflows

Resources and Next Steps

Getting Started Resources

  • App Modernization Guidance: Comprehensive framework documentation
  • GitHub Copilot Extensions: VS Code marketplace installation
  • Azure Migrate Tools: Application estate discovery and assessment
  • Devin AI Platform: Agent-based modernization capabilities

Support Channels

  • Microsoft Account Team: Large-scale project consultation
  • Partner Ecosystem: Implementation support and services
  • Community Forums: Developer experience sharing and best practices
  • Documentation Hub: Technical implementation guides and tutorials

About the Speakers

Mohammad Nofal
Global Black Belt Lead - Application Innovation (EMEA)
Microsoft
Leads teams helping customers modernize application estates and innovate on Azure.

Anoop Iyer
Director, Business Strategy
Microsoft
Leads strategy architects in Global Customer Success focused on AI-powered application transformation.

Michael Yen-Chi Ho
Senior Product Manager
Microsoft
Oversees Azure Developer Platform services and AI-assisted migration tooling strategy.

Bryce Hunt
Founding GTM Engineer
Cognition AI
Leads technical deployments with enterprise partners and agent-based development workflows.

Tinius Alexander Lystad
Chief Technology Officer
Visma AS
Leads software development modernization and AI transformation across 190 software companies.

This session represents a comprehensive roadmap for organizations seeking to accelerate their modernization journey through AI-powered tools and methodologies, demonstrating how legacy systems can be transformed into cloud-native solutions at enterprise scale.