In a typical case of Java monolithic application migration to Kubernetes microservices, Gemini-Flow schedules 50 intelligences to work together: analyzing intelligences to parse the old system structure, architecting intelligences to design the service splitting scheme, and finally deploying intelligences to generate Helm diagrams and CI/CD configurations. The system automates code refactoring, test case generation, and performance optimization, reducing average deployment time by 67% compared to manual migration. outputs include a complete microservices codebase, containerized configurations, and monitoring dashboards.
This answer comes from the articleGemini-Flow: AI Code Development and System Optimization Tool for Multi-Intelligence CollaborationThe
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