A multi-dimensional extensible cloud-native service stack for enterprises

• Published in: Journal of Cloud Computing: Advances, Systems and Applications
• Main Authors: Jian Lin, Dongming Xie, Jinjun Huang, Zinan Liao, Long Ye
• Format: Article
• Language: English
• Published: SpringerOpen 2022-11-01
• Subjects: Cloud-native; Container cluster; Service stack; Kubernetes; PaaS; SaaS
• Online Access: https://doi.org/10.1186/s13677-022-00366-7

Abstract With the widespread acceptance of the cloud-native concept and the emergence of a large number of dedicated cloud-native applications, the service stacks of cloud-native applications have received extensive attention in the industry. To analyze the extensibility problems of service stacks, a cloud-native light-cone model is proposed, which focuses on the dimensions of application, infrastructure, tenant and workflow, and provides a perspective view that reflects the concerns of stakeholders. Based on this model, various challenges in designing extensible cloud-native service stacks are identified by classification. To solve these challenges, a holistic architecture and a set of key technologies are designed, involving unified runtime abstraction, cluster bootstrapped creation, application-specific controllers, etc. Furthermore, the OMStack (Oriental Mind Stack) is implemented, which integrates these technologies and provides a group of PaaS and SaaS services for container cluster (OMCC), artificial intelligence (OMAI), big data (OMBD) and so on. Experimental analysis and production applications demonstrate the practicality, efficiency and reliability of the proposed architecture, stack and services.