For large-scale legacy system retrofits, Kiro has been working withContextual reconstruction + incremental updatesStrategies provide specialized support:
- Architecture analysis phase::
- Scanning the code base to generate dependency graph.svg
- Automatic identification of technical debt (marking outdated dependency libraries / deprecated API calls)
- Retrofit implementation phase::
- pass (a bill or inspection etc)
steering.jsonConfiguration file constrains the direction of the transformation (e.g., "must maintain backward compatibility of APIs") - Generate comparison branches for selected functional scopes using a modular replacement strategy
- Automatic retention of original business logic annotations (labeled LEGACY_LOGIC)
- pass (a bill or inspection etc)
- validation phase::
- Automated generation of interface contract tests (Postman collection)
- Memory/CPU metrics report comparing old and new versions
Typical example: When migrating Spring Boot 2.x to 3.x for a financial system, Kiro completed it in 3 weeks:
1) Automatic update of 78% compatibility code
2) Flag 22% for breaking changes that require manual review
3) Generate complete documentation of the rollback scenario
This treatment significantly reduces the perceived load and risk of retrofitting legacy systems.
This answer comes from the articleKiro: an AI programming tool that quickly turns requirements into codeThe
May not be reproduced without permission:AI productivity tools " How does Kiro handle retrofitting upgrades to large legacy code bases?
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