Loading...
Please wait, while we are loading the content...
Similar Documents
Design and Implementation of Cloud Docker Application Architecture Based on Machine Learning in Container Management for Smart Manufacturing
Content Provider | MDPI |
---|---|
Author | Kim, Byoung Soo Lee, Sang Hyeop Lee, Ye Rim Park, Yong Hyun Jeong, Jongpil |
Copyright Year | 2022 |
Description | Manufacturers are expanding their business-process innovation and customized manufacturing to reduce their information technology costs and increase their operational efficiency. Large companies are building enterprise-wide hybrid cloud platforms to further accelerate their digital transformation. Many companies are also introducing container virtualization technology to maximize their cloud transition and cloud benefits. However, small- and mid-sized manufacturers are struggling with their digital transformation owing to technological barriers. Herein, for small- and medium-sized manufacturing enterprises transitioning onto the cloud, we introduce a Docker Container application architecture, a customized container-based defect inspection machine-learning model for the AWS cloud environment developed for use in small manufacturing plants. By linking with open-source software, the development was improved and a datadog-based container monitoring system, built to enable real-time anomaly detection, was implemented. |
Starting Page | 6737 |
e-ISSN | 20763417 |
DOI | 10.3390/app12136737 |
Journal | Applied Sciences |
Issue Number | 13 |
Volume Number | 12 |
Language | English |
Publisher | MDPI |
Publisher Date | 2022-07-03 |
Access Restriction | Open |
Subject Keyword | Applied Sciences Cloud Docker Docker Container Machine Learning Monitoring Smart Manufacturing Container Management |
Content Type | Text |
Resource Type | Article |