A Robust Microservice Architecture for Scaling Automated Scoring Applications

Author(s):: Madnani, Nitin; Cahill, Aoife; Blanchard, Daniel; Andreyev, Slava; Napolitano, Diane; Gyawali, Binod; Heilman, Michael; Lee, Chong Min; Leong, Chee Wee; Mulholland, Matthew; Riordan, Brian
Publication Year:: 2018
Report Number:: RR-18-14
Source:: ETS Research Report
Document Type:: Report
Page Count:: 10
Subject/Key Words:: Automated Scoring and Natural Language Processing, Machine Learning, Test Reliability, Apache Storm, Programming Languages, Robustness (Statistics), Microservices

Abstract

We present a microservice architecture for large‐scale automated scoring applications. Our architecture builds on the open‐source Apache Storm framework and facilitates the development of robust, scalable automated scoring applications that can easily be extended and customized. We demonstrate our architecture with an application for automated content scoring.

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https://doi.org/10.1002/ets2.12202

A Robust Microservice Architecture for Scaling Automated Scoring Applications

Abstract

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