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# GitHub Copilot Modernize 101: Microsoft's 9-part series on AI-assisted Java modernization

**[Collections](https://daily.dev/sources/collections)** · 3 min read · 1 upvotes · 0 comments

## Summary

Microsoft has released a 9-part video series, GitHub Copilot Modernize 101, covering AI-assisted modernization of legacy Java applications. The series walks through the full lifecycle: assessment using tools like Dr. Migrate and CAST, framework upgrades (Spring Boot 1.5.9/Java 8 to Spring Boot 3.5.3/Java 25 using OpenRewrite), database migration from Oracle to PostgreSQL, containerization with Docker, and deployment to Azure Container Apps. A real-world case study shows a Java 5/Struts 1.3 monolith migrated in ~2 days instead of the typical 14 weeks. The key principle is developer-controlled modernization — Copilot handles repetitive mechanical work while developers review and approve every significant change.

## Content

Microsoft has released a 9-part video series called *GitHub Copilot Modernize 101* on the Microsoft Developer Channel. It covers the full lifecycle of modernizing legacy Java applications — assessment, framework upgrades, database migration, containerization, and CI/CD — using GitHub Copilot's agentic capabilities inside existing developer IDEs like IntelliJ.

## Why modernization matters right now

The framing throughout the series is practical: 94% of executives say AI is critical to their business, but only 28% have moved AI pilots into production. The bottleneck is usually the underlying codebase. You can't bolt AI onto a Java 1.5 Struts monolith. Modernization isn't a nice-to-have — it's the prerequisite.

The series argues that modernization should be a continuous, repeatable process rather than a one-time big-bang rewrite. GitHub Copilot's agentic workflow makes that practical by automating the mechanical parts while keeping developers in control of every decision.

## What the series covers

**Assessment** — The workflow starts with portfolio-level tools (Dr. Migrate, CAST, Azure Migrate) to identify what needs upgrading, then surfaces findings as GitHub Issues that feed directly into the agent's task list.

**Framework upgrades** — The core demo upgrades a Spring Boot 1.5.9 / Java 8 application all the way to Spring Boot 3.5.3 and Java 25. The agent uses OpenRewrite under the hood and works through multiple milestones (Java 21 → 25, Spring Boot 3.3 → 3.4 → 3.5), running CVE checks and all 96 tests at each step. Minor Mockito 5.x compatibility issues get resolved automatically. The full upgrade takes roughly 20 minutes.

**Customizing tasks** — Copilot generates a task list as a first draft, not a final decision. Developers can edit it: add constraints, exclude specific upgrades, or break changes into smaller reviewable steps. In one demo, excluding Java and Spring version bumps resulted in zero file changes — the intended outcome. Copilot still surfaced a pre-existing Mockito test failure and flagged known CVEs it couldn't fix within the given constraints, explaining why. The principle here is explicit: modernization means developer-controlled changes, not silent automatic rewrites.

**Database migration** — A separate walkthrough covers migrating a Spring Boot app from Oracle to PostgreSQL on Azure, using a JetBrains plugin for database migration tasks. The agent handles dependency updates, readme fixes, and schema migration steps, with the developer reviewing each change.

**Containerization and deployment** — The series ends with Docker containerization and deployment to Azure Container Apps, plus scaling the workflow via CLI and parallel cloud coding agents for larger portfolios.

## A real migration: Java 5 / Struts 1.3 to Java 21 and Spring Boot

One contributor shared their experience migrating an actual legacy Java 5 / Struts 1.3 monolith — the kind of codebase that would normally take around 14 weeks to modernize manually. With AI assistance, it took about 2 days.

A few things made the difference:

- **A detailed migration plan upfront.** The agent works better with explicit steps than with vague goals.
- **Custom verification skills.** AI makes mistakes. Building checks that catch them early saves time later.
- **Custom instructions.** Guiding the agent through migration steps — rather than letting it improvise — produced more predictable results.

This isn't a story about AI doing everything. It's about AI handling the repetitive mechanical work (dependency updates, CVE fixes, configuration migration) while the developer stays in the loop on decisions that matter.

## Where to find it

The full 9-part *GitHub Copilot Modernize 101* series is on the [Microsoft Developer Channel](https://www.youtube.com/@MicrosoftDeveloper). The workflow runs inside IntelliJ via the GitHub Copilot App Modernization extension, with CLI support for scaling across larger portfolios.

---

Tags: [#github](https://daily.dev/tags/github), [#java](https://daily.dev/tags/java), [#azure](https://daily.dev/tags/azure), [#spring](https://daily.dev/tags/spring)

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