Azure Copilot and GitHub Copilot work together to reimagine how you modernize applications end to end. Instead of treating planning, coding, deployment, and optimization as separate steps, they connect these activities into a single, AI-assisted experience.

At a high level:

• GitHub Copilot helps developers inside the IDE with AI-assisted coding, refactoring, and understanding legacy code.
• Azure Copilot helps you design, configure, and operate modern cloud architectures on Azure, guiding decisions like which services to use and how to migrate workloads.

Together, they support a more connected modernization journey—from analyzing existing apps to implementing changes and running them in Azure—using AI at each step to reduce manual effort and speed up delivery.

The connected experience is designed to reshape the day-to-day work of teams modernizing applications by linking planning, development, and cloud operations.

Practically, this can help you:

• Understand existing applications faster – AI can summarize code, highlight dependencies, and suggest modernization paths.
• Accelerate code changes – GitHub Copilot can propose updated patterns, new APIs, and refactoring options directly in your editor.
• Align code with cloud architecture – Azure Copilot can suggest Azure services, deployment models, and configuration options that match your modernization goals.
• Reduce context switching – Because the experience is connected, insights from Azure (like recommended services) can inform what you do in GitHub, and vice versa.

Instead of separate tools and handoffs, you get a more continuous flow, which can help teams deliver modernization work more predictably and with clearer guidance from AI at each stage.

Azure Copilot and GitHub Copilot are built to support a range of end-to-end modernization scenarios, especially when you are moving or evolving applications on Microsoft Azure.

Typical scenarios include:

• Refactoring legacy apps – Analyzing existing codebases, suggesting modern patterns, and helping rewrite components for cloud-native architectures.
• Replatforming to Azure – Guiding you on which Azure services to use, how to structure deployments, and how to adjust code to run effectively on those services.
• Incremental modernization – Supporting step-by-step changes (for example, breaking out services over time) while keeping the overall journey connected and AI-assisted.

Because the experience is designed as a connected, AI-assisted workflow, you can move from assessment to implementation and operations with fewer gaps between tools and teams.