Open AccessA 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
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/ets2.12202
Subject(s) - computer science , architecture , scalability , microservices , scale (ratio) , scaling , artificial intelligence , computer architecture , machine learning , operating system , cloud computing , mathematics , art , geometry , visual arts , physics , quantum mechanics
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.