Richard_Healy shares an in-depth look at how GitHub Copilot, agentic AI, and Azure are revolutionizing application modernisation, empowering teams to refactor legacy systems, accelerate cloud adoption, and boost developer productivity.

Unlocking Application Modernisation with GitHub Copilot

Introduction

Modernising legacy applications has historically been a complex, risky undertaking. Richard_Healy explores how the emergence of GitHub Copilot and agentic AI has shifted the landscape, enabling developers and organisations to reimagine what’s possible for application transformation and cloud adoption.

The Modernisation Challenge – Past vs. Present

Past hurdles: Outdated programming languages (COBOL, VB6), technical debt, missing documentation, high risk of business disruption.
AI shifts the game: Tools like GitHub Copilot act as AI pair programmers, offering instant code comprehension, automated refactoring, and the ability to translate or update code across languages and frameworks. Developers can now tackle upgrades, reduce technical debt, and modernise with more confidence and speed.

Modernisation Opportunities Unlocked by Copilot

1. AI-Assisted Legacy Code Refactoring and Upgrades

Code Understanding: Copilot explains complex legacy code and assists with upgrades.
Automated Refactoring: Proposes modern replacements and can perform bulk changes (e.g., updating frameworks from .NET Framework 4.x to .NET 6).
Technical Debt Reduction: Enforces best practices, flags vulnerabilities, and streamlines formerly risky upgrades.

2. Accelerating Cloud Migration and Azure Modernisation

Azure Migration Planning: Assesses app readiness and recommends target Azure services (Azure SQL, Azure Blob Storage, Azure Functions).
Automated Cloud Transformations: Handles tasks like replacing storage or identity features with Azure-native solutions, using Azure AD (Entra ID), Key Vault, App Configuration.
Validation & Deployment: Generates unit tests, Infrastructure-as-Code (ARM, Bicep, Terraform), and CI/CD pipelines for seamless Azure deployment.
Complex Integrations: Translates workflows from platforms like Apigee/MuleSoft to Azure API Management or Logic Apps; helps move workloads from AWS/GCP to Azure.

3. Boosting Developer Productivity and DevOps

Unit Test Generation: Instantly generates test cases for legacy code (enabling TDD).
DevOps Automation: Autocompletes YAML for CI/CD, creates Dockerfiles, Kubernetes manifests, reduces boilerplate.
BDD Support: Interprets human-readable scenarios into step definitions and code.
Consistency and Quality: Encourages best practices, reduces bugs, and supports rigorous code reviews with high-quality suggestions.

Business Impact

Faster Time-to-Market: Accelerates upgrades and new feature delivery.
Cost Savings: Automation lowers developer effort and operational costs.
Increased Reliability: AI-driven testing and refactoring improve system robustness.
Agility: Modernised platforms are more adaptable for future requirements.
Employee Satisfaction: Developers focus on high-value, creative work as AI handles repetitive tasks.

Next Steps

Experiment with Copilot: Try it on a sample project for code explanation or test generation.
Pilot a Migration: Select a legacy service or module, assess Copilot’s impact, and build confidence with early wins.
Prepare Your Organisation: Address licensing, security, training, and roll-out strategies to maximise value.

Resources

Modernisation is a journey. Tools like GitHub Copilot and Azure are the new compass, helping organisations unlock the full potential of their applications and teams.

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