Minerva: A Portable Machine Learning Microservice Framework for Traditional Enterprise SaaS Applications

• URL: http://arxiv.org/abs/2005.00866v1
• Date: Sat, 2 May 2020 15:53:33 GMT
• Title: Minerva: A Portable Machine Learning Microservice Framework for Traditional Enterprise SaaS Applications
• Authors: Venkata Duvvuri
• Abstract summary: In traditional enterprise applications, redesign are an essential ingredient to deploy machine learning (ML) models successfully. Here, we propose a portable ML microservice framework Minerva as an efficient way to modularize and deploy intelligent in traditional legacy applications suite.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In traditional SaaS enterprise applications, microservices are an essential ingredient to deploy machine learning (ML) models successfully. In general, microservices result in efficiencies in software service design, development, and delivery. As they become ubiquitous in the redesign of monolithic software, with the addition of machine learning, the traditional applications are also becoming increasingly intelligent. Here, we propose a portable ML microservice framework Minerva (microservices container for applied ML) as an efficient way to modularize and deploy intelligent microservices in traditional legacy SaaS applications suite, especially in the enterprise domain. We identify and discuss the needs, challenges and architecture to incorporate ML microservices in such applications. Minervas design for optimal integration with legacy applications using microservices architecture leveraging lightweight infrastructure accelerates deploying ML models in such applications.

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