Abstract
:The rise of cloud-native architectures has enabled the rapid development and deployment of scalable Software-as-a-Service applications. However, building multi-tenant systems that support extensive customization for individual tenants remains a challenge. This paper explores strategies to overcome these challenges in the context of developing an AI/ML-enhanced Enterprise Resource Planning (ERP) system for educational institutions. We propose a microservice-based architecture that decouples AI/ML models from the main application, dynamically generating UI components, forms, routes, and implementing flexible role-based access control (RBAC). This architecture allows tenant-specific customization without sacrificing the scalability, security, and maintainability of a cloud-native system. Real-world implementation details and strategies for sustainability are discussed, along with challenges faced.
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