Microservice-Driven Modular Low-Code Platform for Accelerating SME Digital Transformation

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Abstract

To overcome the difficulties encountered by the SMEs during their digital transformation such as insufficient development resources and complicated system integration, this article introduces a microservice-oriented modular low code platform (MDMLCP) to facilitate the rapid devolution and smart evolution of SMEs' digital infrastructure. Specifically, the proposed model embeds new the multi-tenant secure software development lifecycle to guarantee security and privacy between different organizations via data isolation and access control. Meanwhile, the platform adds AI-supported module development functions and integrates the AutoML tool chain, enabling users from small and medium-sized enterprise to develop intelligent applications, such as sales forecasting, inventory optimization and customer portraits, with no IT experience required. Moreover, MDMLCP offers handy digital service templates CRM, ERP and supply chain management systems, enabling the templatized customization of a tailored-for-user business system fast through visual drag and drop and smart connectors. Compared with prior low-code platforms, the MDMLCP creatively presents a meta-component orchestration engine that combines static template reuse and dynamically synthesized AI components to realize intelligent-inspired combination on the component level and the secure collaboration at service level, and is responsible for unified schedule as well as controls over a cloud microservice cluster. The experimental results indicate that MDMLCP can not only raise the system deployment efficiency by 40% and promote the service stability by 35% on average under realistic DSME.

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APA

Fang, Z. (2025). Microservice-Driven Modular Low-Code Platform for Accelerating SME Digital Transformation. In Proceedings of 2025 International Conference on Economic Management and Big Data Application, ICEMBDA 2025 (pp. 894–898). Association for Computing Machinery, Inc. https://doi.org/10.1145/3770177.3770324

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