Servitization of Customized 3D Assets and Performance Comparison of Services and Microservices Implementations

3D models (or assets) that are present in many of modern software applications are first modeled by graphic designers using dedicated computer graphic tools and then integrated into such software applications or apps by software developers. This simple workflow/procedure requires developers to have a basic grounding in computer graphics, since 3D engines, libraries and third-party software are needed for this kind of integrations. Oftentimes, 3D designers are also required to customize or produce versions of a 3D model and thus, they must re-model all the assets before they are returned back to the developers for integration into the applications. This procedure also occurs whenever a modification or customization is requested. One possible significant improvement to this traditional, poorly automated workflow is to use services-oriented technology and features servitization to carry out the customization of 3D assets on-demand. In this article, we introduce
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S3D, an open-source microservices-based platform designed to support features relating to the customization of 3D models.
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S3D not only enables 3D assets to be customized without the need for computer graphic tools or designers, but also allows 3D models to be visualized through web technologies (e.g., HTML, Javascript and web component to visualize and interact with 3D models), thereby avoiding the development of computer graphics libraries or components in final software products. The article describes the elements that
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S3D comprises, explains how it works and presents a series of load tests to compare the performance (time consumption, CPU and memory utilization) of
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S3D when implemented and deployed as a microservices platform against a monolithic-based implementation, showing similar results with a low number of users (and requests) but reducing, on average, 64.32% the response time in the microservice-based implementation for a large number of users; reducing CPU utilization on microservice-based implementation and remaining the memory usage more or less constant in both implementations.