Automate Spring Boot upgrades across hundreds of services with safe, scalable code transformations

Spring Boot is core to many modern Java services. But manual, repo-by-repo upgrades don’t hold up as systems grow.
Over time, versions drift, security fixes slip, and upgrades become harder to coordinate. What should be routine maintenance slowly turns into compounding technical debt.
A practical, hands-on training for teams on 2.x, 3.x, or planning for 4.x. Learn Spring Boot migration patterns, common pitfalls, and how to automate large-scale upgrades without slowing delivery.
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Ensures code changes are safe and accurate by understanding program intent—not just syntax—reducing the risk of subtle runtime issues.
Updates dependencies and build configurations automatically, keeping projects aligned without manual intervention or brittle scripts.
Coordinates changes across many repositories and teams, enabling consistent upgrades without manual sequencing or coordination overhead.
Maintains existing formatting and coding conventions so upgrades integrate cleanly with current codebases and review workflows.
Handles Java version upgrades and Jakarta namespace and API migrations automatically, reducing manual effort and upgrade risk.
Provides insight into upgrade progress, coverage, and risk across the entire application portfolio—not just individual repositories.
Applies security updates that align with supported Spring versions, helping teams stay secure without managing patches manually.

Understand which services are affected, what versions they’re running, and what changes are required before applying upgrades.
Apply the same validated Spring Boot upgrade recipes across all repositories to ensure consistency and reduce regression risk.
Roll out upgrades across hundreds or thousands of repositories with automated, reviewable PRs that fit existing developer workflows.
Track upgrade progress, adoption rates, and key milestones across teams using DevCenter dashboards—without spreadsheets or manual reporting.

Moderne's recipes cover:
Moderne applies validated recipes across the entire code estate, with impact analysis, coordinated PRs, and centralized progress tracking.
Moderne uses Lossless Semantic Trees to deliver deterministic, format-preserving transformations across hundreds or thousands of services.
Moderne coordinates Spring Boot migrations across teams and repositories, enabling controlled rollouts and portfolio-wide visibility.
Platforms using OpenRewrite recipes typically operate repo-by-repo with limited portfolio visibility and coordination.
AST- and regex-based tools automate basic changes but struggle with semantic accuracy and consistency at scale.
IDE-driven refactoring or AI assistants are helpful for individual developers but cannot coordinate, track, or govern enterprise-wide migrations.
For most teams, the most effective way to migrate from Spring Boot 2.x to 3.x is to automate the upgrade using semantic, repeatable code transformations rather than applying changes manually repository by repository. Spring Boot 3.x introduces significant framework and dependency updates, including the Jakarta EE namespace shift, that are difficult to apply consistently by hand at scale.
In large organizations, manual upgrades often break down due to inconsistent baselines, shared libraries, and varying levels of test coverage across services. Even small differences between repositories can introduce regressions when changes are applied manually.
Automated migration tools like OpenRewrite allow teams to encode Spring Boot 3.x upgrade logic as deterministic recipes, apply them consistently across services, and validate results through standard CI workflows.
For a deeper walkthrough of the technical changes and migration strategy, see our Spring Boot 3.x migration guide: https://www.moderne.ai/blog/speed-your-spring-boot-3-0-migration
Migrating to Spring Boot 4.x requires a forward-looking approach that accounts for ongoing framework evolution rather than treating upgrades as one-time events. Spring Boot 4.x builds on the architectural changes introduced in 3.x and continues to evolve dependencies, APIs, and runtime expectations.
Enterprises benefit from tools that support stepwise or multi-version upgrades, allowing teams to move incrementally while maintaining visibility across large application portfolios. This reduces risk compared to attempting large, one-off migrations that are difficult to test and coordinate.
Automation platforms like OpenRewrite enable teams to continuously apply and validate upgrade recipes as frameworks evolve, helping organizations stay current without disrupting delivery.
For a detailed breakdown of what changes in Spring Boot 4.x and how to plan an upgrade, see our Spring Boot 4.x migration guide: https://www.moderne.ai/blog/spring-boot-4x-migration-guide
At enterprise scale, Spring Boot migrations are no longer isolated framework updates—they become coordination challenges across teams, repositories, and shared libraries. Organizations with hundreds of services must balance centralized governance with team-level autonomy to avoid blocking delivery.
Successful enterprises typically coordinate upgrades centrally by defining standardized migration rules, while allowing individual teams to review and merge changes through familiar pull request workflows. This approach ensures consistency without forcing disruptive, top-down rewrites.
Automated code transformation platforms enable this model by applying the same upgrade logic across all repositories while preserving ownership and review processes.
A real-world example of this approach can be seen in this insurance industry case study, where automation significantly improved migration productivity at scale: https://www.moderne.ai/case-study/insurance-productivity-with-automated-code-migration
Yes—when automation is based on semantic code understanding rather than text-based search and replace. Safe automation requires tools that understand Java syntax, frameworks, and dependency relationships to ensure changes are applied correctly and consistently.
In real-world enterprise environments, Spring Boot applications often include custom frameworks, internal libraries, and non-standard patterns. Automation that lacks semantic awareness can introduce subtle bugs or incomplete changes.
Semantic, deterministic transformation engines like OpenRewrite analyze code structure directly, allowing migrations to be applied safely and validated through existing test suites and CI pipelines. This reduces regression risk while enabling upgrades to be rolled out confidently across large codebases.
OpenRewrite enables Spring Boot upgrades by providing a large library of pre-built, composable recipes that automate framework, dependency, and API changes using semantic analysis. These recipes encapsulate best practices for upgrading Spring Boot applications without relying on brittle text-based changes.
For Spring-specific upgrades, OpenRewrite includes recipes that handle dependency updates, configuration changes, deprecated API replacements, and framework alignment across services. Teams can apply these recipes consistently across many repositories to maintain a common baseline.
You can explore the full set of Spring-related OpenRewrite recipes here, including examples relevant to Spring Boot upgrades: https://docs.openrewrite.org/recipes/java/spring
Yes. Jakarta EE namespace migrations are a strong candidate for automation because they involve widespread, consistent API and package changes across Java codebases. Manually applying these changes is time-consuming and error-prone, especially in large applications with deep dependency graphs.
OpenRewrite provides dedicated Jakarta migration recipes that automatically update imports, dependencies, and affected APIs while preserving code correctness. These recipes understand the semantic structure of the code, ensuring changes are applied safely and completely.
For example, OpenRewrite’s Jakarta migration recipes can be used to automate large portions of the javax.* to jakarta.* transition. You can view these recipes here: https://docs.openrewrite.org/recipes/java/migrate/jakarta
The timeline for a Spring Boot migration with automation depends on portfolio size, testing strategy, and organizational readiness—but automation consistently compresses timelines from years to months, or even weeks for well-prepared teams.
Without automation, large enterprises often spend multiple years performing manual, repo-by-repo upgrades. In contrast, automated transformations allow teams to apply changes consistently across many services, validate results through CI, and iterate quickly.
A concrete example is Squarespace, where automation helped accelerate modernization efforts significantly—reducing the time required to move to newer Spring Boot versions compared to earlier, manual upgrades.
You can read more about this timeline in the Squarespace case study: https://www.moderne.ai/case-study/squarespace-simplifies-and-scales-code-modernization
At scale, Spring Boot upgrades tend to break in places that aren’t obvious from migration guides or small proof-of-concept projects. While individual applications may upgrade cleanly, large portfolios often surface hidden coupling between framework versions, shared libraries, and custom platform code.
Common failure points include dependency version conflicts, transitive dependency drift, and API changes introduced by framework upgrades—especially around Spring Security, configuration properties, and application context behavior. The Jakarta EE namespace shift in newer Spring Boot versions is another frequent source of breakage, requiring coordinated changes across imports, dependencies, and runtime expectations.
What makes these issues difficult at scale is that they rarely appear consistently across all services. Small differences between repositories—such as custom starters, legacy configurations, or test coverage gaps—can cause upgrades to fail in unpredictable ways. Automated, semantic code transformations help mitigate this by applying the same upgrade logic consistently and surfacing differences early through CI validation rather than during manual debugging.
Spring Boot migrations directly impact CI/CD pipelines because they often introduce widespread changes across application code, dependencies, and configuration. When upgrades are performed manually, teams frequently encounter broken builds, failing tests, and inconsistent results across environments—slowing down delivery and increasing rollback risk.
In enterprise environments, these issues are amplified by the number of repositories involved. A migration that appears successful in one service may fail in another due to subtle differences in build configuration, dependency resolution, or test assumptions. Without automation, CI pipelines can become bottlenecks rather than safeguards during large-scale upgrades.
Automated migration approaches integrate cleanly with CI/CD workflows by applying deterministic code changes, running tests immediately, and producing reviewable pull requests. This allows teams to validate Spring Boot upgrades incrementally, maintain confidence in pipeline results, and avoid long-lived upgrade branches. By treating upgrades as repeatable, testable changes, organizations can modernize without disrupting their existing delivery processes.
Yes—incremental rollouts are often the safest and most effective way to upgrade Spring Boot in large organizations. Rather than attempting a single, organization-wide upgrade, teams can migrate services in stages while maintaining visibility and control across the portfolio.
Incremental upgrades allow organizations to prioritize high-risk or high-impact services first, validate changes through CI, and address issues before expanding the rollout. This approach is especially important when dealing with framework changes that affect shared libraries or platform components, where early feedback can prevent widespread regressions.
Automation enables this model by ensuring that the same upgrade logic is applied consistently as services are migrated over time. Semantic code transformation tools make it possible to re-run upgrade recipes as frameworks evolve, allowing teams to move forward without losing track of what has already been modernized. This helps enterprises stay current with Spring Boot releases without disrupting ongoing development.