AI-Powered .NET App Modernization: GitHub Copilot & Azure Migration Tools

Session Date: Microsoft Build 2025
Duration: ~45 minutes
Venue: Build 2025 Conference - BRK101
Speakers: Scott Hunter (VP of Product, Azure Developer), Chester Husk (Product Manager, .NET Tools)
Link: Microsoft Build 2025 Session BRK101

.NET App Modernization

Executive Summary

This session demonstrates how AI-powered tools are transforming .NET application modernization, featuring live demonstrations of GitHub Copilot-assisted upgrades and Azure migration capabilities. The speakers showcase the evolution from static analysis tools to intelligent, automated solutions that can perform complex code transformations with minimal developer intervention.

Key Topics Covered

🚀 1. The Imperative for .NET Upgrades

Core Concept: Regular .NET upgrades are essential for performance, security, compliance, and ecosystem compatibility.

Key Motivations:

  • Performance gains - Each release brings significant performance improvements
  • Security patches - Monthly servicing releases include critical security fixes
  • Tooling enhancements - New SDK capabilities and developer productivity features
  • Support lifecycle compliance - LTS vs STS model requirements
  • Ecosystem alignment - Community packages target newer frameworks

Current State:

  • Many organizations still run .NET Framework applications
  • Web Forms represent ~10% of legacy applications (hardest to migrate)
  • Framework targeting remains supported for gradual transitions

🔄 2. Upgrade vs. Modernization: Understanding the Spectrum

Upgrade (Point A → Point B):

  • Framework version migrations (.NET 6 → .NET 8 → .NET 9)
  • Dependency updates and vulnerability patches
  • Tooling and SDK transitions

Modernization (Architectural Transformation):

  • Decomposition into microservices
  • Migration to cloud-native patterns (Azure Functions, Container Apps)
  • Adoption of new deployment models
  • Integration with modern DevOps practices

Business Benefits:

  • Cost reduction through cloud provider alignment
  • Talent attraction and retention
  • Scalability and operational efficiency

🛠️ 3. Traditional Tools: .NET Upgrade Assistant & Azure Migrate

.NET Upgrade Assistant

Capabilities:

  • Analysis reporting - Comprehensive project assessment with story point estimates
  • Multiple upgrade strategies - In-place, side-by-side, incremental migration
  • NuGet Central Package Management - Automatic package consolidation
  • SDK-style project conversion - Modern project file transformation

Supported Project Types:

  • ASP.NET Web Applications
  • WPF and Windows Forms
  • Console Applications and Class Libraries
  • Azure Functions (with limitations)

Azure Migrate Application Code Assessment Tool

Purpose: Cloud readiness assessment and migration planning

Features:

  • Static code analysis for Azure compatibility
  • Detailed remediation reports with mandatory vs. optional fixes
  • Basic Copilot integration for guidance (limited to documentation lookup)

Limitations: Generates extensive task lists requiring manual developer intervention

🤖 4. AI-Powered Upgrade: GitHub Copilot for .NET Modernization

Core Innovation: Intelligent, context-aware upgrades that learn from developer interventions.

Key Features

  • Dependency-aware analysis - Understanding project relationships and package usage patterns
  • Automated execution - Beyond analysis to actual code transformation
  • Human-in-the-loop learning - Captures and reapplies developer fixes
  • Git integration - Checkpoint commits for each transformation step
  • Editable upgrade plans - Markdown-based plans that users can modify

Live Demonstration Highlights

Scenario: eShopOnWeb solution upgrade from .NET 6.0 → .NET 9.0

Process Flow:

  1. Interactive planning - Copilot generates customizable upgrade strategy
  2. Vulnerability detection - Automatic identification and resolution of security issues
  3. Automated execution - Project-by-project transformation with real-time progress
  4. Error handling - Intelligent recovery from compilation errors
  5. Learning integration - Pattern recognition for future similar issues

Results: ~2.5 minutes active upgrade time for 8 projects with 80%+ automation

🌐 5. AI-Assisted Modernization: Formula-Based Code Transformation

Concept: Pre-built and custom “formulas” for large-scale code pattern migrations.

Formula System Architecture

  • Pre-built formulas - Top 10 common migration patterns from AppCAT analysis
  • Custom formula creation - Learn from developer examples to generate reusable patterns
  • Prompt-based implementation - Editable transformation logic
  • Cross-project application - Bulk changes across entire codebases

Live Demo: AWS S3 → Azure Blob Storage Migration

Transformation scope:

  • Package references and imports
  • API method calls and signatures
  • Configuration settings (appsettings.json)
  • Connection string formats
  • Authentication mechanisms

Developer Experience:

  • Plan review and approval workflow
  • Real-time code transformation visualization
  • Automatic build verification
  • Style and convention preservation

📈 6. Real-World Impact and Adoption

Microsoft Internal Results

  • Teams and Xbox - Significant upgrade acceleration
  • Diverse development pressures - Different teams, different timelines
  • Reduced manual effort - Hours of work compressed to minutes

Partner Success Stories

  • Enterprise customers - 8-month migrations reduced to weeks
  • Legacy codebase modernization - Automated pattern migrations
  • Developer productivity gains - Focus shift to business logic vs. mechanical updates

🔮 7. Future Roadmap and Vision

Near-term Enhancements

  • Framework → Core migration support - Bridge the final gap in upgrade tooling
  • Visual Studio Code integration - Multi-editor support
  • Bulk/batch processing - Automated organization-wide upgrades
  • Enhanced formula marketplace - Shareable transformation patterns

Long-term Vision

  • Unified upgrade/modernization interface - Seamless workflow integration
  • SRE agent integration - Automated monitoring and upgrade triggering
  • Cross-language support - Python, C++, JavaScript formula system
  • Ecosystem integration - End-to-end DevOps automation

Technical Architecture Insights

AI Integration Points

  • Roslyn compiler integration - Deep code understanding for error detection
  • LLM prompt engineering - Context-aware transformation instructions
  • Pattern recognition - Learning from successful developer interventions
  • Validation frameworks - Automated testing and quality assurance

Developer Experience Design

  • Transparency - Visible plans, commits, and transformation steps
  • Control - User approval workflows and modification capabilities
  • Feedback loops - Continuous improvement from user interactions
  • Error recovery - Graceful handling of edge cases and failures

Session Highlights

“Any change is a breaking change for somebody, so we’re sorry. Also, use these tools to help you migrate.” - Chet Husk

“It’s amazing what Wi-Fi does for AI” - Scott Hunter (during live demo challenges)

“In that minute-and-a-half… it already saved Chet probably an hour or multiple hours of time to go manually update all those projects by hand.” - Scott Hunter

Practical Takeaways

Immediate Actions

  1. Install GitHub Copilot App Modernization extension - Available in public preview
  2. Assess current .NET Framework applications - Use existing tools for analysis
  3. Establish testing infrastructure - Better tests enable greater AI tool confidence
  4. Review upgrade strategies - Plan gradual vs. bulk migration approaches

Strategic Considerations

  1. AI tool adoption curve - Start with low-risk, high-impact scenarios
  2. Developer training - Team familiarity with AI-assisted workflows
  3. Quality assurance integration - PR validation and testing pipelines
  4. Feedback participation - Contribute to tool improvement through usage data

Community Engagement Opportunities

Immediate Feedback Channels

  • Visual Studio Marketplace - Extension reviews and feature requests
  • Microsoft Build sessions - Follow-up deep dives and labs
  • AI-assisted App Modernization booth - Direct team interaction

Upcoming Sessions

  • BRK131 - Deep dive into modernization technology (Timothy NG)
  • Dedicated labs - Hands-on experience with tools
  • SRE agent integration - Site Reliability Engineering automation

About the Speakers

Scott Hunter
VP of Product, Azure Developer
Microsoft
Leads Azure Developer Experience team including PaaS Services, Azure SDKs, and Developer Tools. Previously led .NET development.

Chester Husk
Product Manager, .NET Tools
Microsoft
Product Manager for .NET SDK, .NET CLI, MSBuild, and .NET Upgrades, focusing on developer productivity and tooling excellence.

This session represents a pivotal moment in .NET development tooling, demonstrating how AI can transform the traditionally manual and error-prone process of application modernization into an intelligent, automated workflow that scales across entire organizations.