The microservice architecture for cloud-based systems is extended to not only require each loosely coupled component to be independently deployable, but also to provide independent routing for each component. This supports canary deployments, green/blue deployments and roll-back. Both ad hoc and system integration test traffic can be directed to components before they are released to production traffic. Front-end code is included in this architecture by using server-side rendering of JS bundles. Environments for integration testing are created with preproduction deploys side by side with production deploys using appropriate levels of isolation. After a successful integration test run, preproduction components are known to work with production precisely as it is. For isolation, test traffic uses staging databases that are copied daily from the production databases, omitting sensitive data. Safety and security concerns are dealt with in a targeted fashion, not monolithically. This architecture scales well with organization size; is more effective for integration testing; and is better aligned with agile business practices than traditional approaches.
Anomaly Detection in Offshore Open Radio Access Network Using Long Short-Term Memory Models on a Novel Artificial Intelligence-Driven Cloud-Native Data Platform
An Intelligent Native Network Slicing Security Architecture Empowered by Federated Learning
Federal University of Viçosa (UFV)（维索萨联邦大学）；Federal University of Espírito Santo (UFES)（圣埃斯皮里图联邦大学）；Salvador University (UNIFACS)（萨尔瓦多大学）；Federal University of Ceará (UFC)（塞阿拉联邦大学）；University of São Paulo (USP)（圣保罗大学）；University of Minho (UMinho)（米尼奥大学）
Towards AI-Native RAN: An Operator's Perspective of 6G Day 1 Standardization
Beijing University of Posts and Telecommunications, China（北京邮电大学）；China Mobile Research Institute, China（中国移动研究院）；ZGC Institute of Ubiquitous-X innovation and Applications, China（ZGC ubiquitous-X创新与应用研究院）
