AnnaBellaDB: Key-Value Store Made Cloud Native

2020 16th International Conference on Network and Service Management (CNSM)(2020)

引用 4|浏览15
暂无评分
摘要
The cloud-native paradigm has become a well-known approach to ensure the elasticity and reliability of applications running in the cloud. One recurrent motif is the stateless design of applications, which aims to decouple the life-cycle of application states from the life-cycle of individual application instances. Application data is written to and read from cloud databases, deployed close to the application code to ensure low latency bounds on state access. When applying a stateless design, the performance of the cloud service is often limited by the cloud database. In order not to become a bottleneck, database instances are distributed on multiple hosts, and strive to ensure data locality for all application functions. However, the shared nature of certain states, and the inevitable dynamics of the application workload necessarily lead to inter-host data access. If the service is geographically distributed, this is even across data centers and edge servers resulting in a significant delay. To minimize the service performance loss due to the stateless design of applications, we propose a latency and access pattern aware state storage method, called state-layer, that can be easily applied in any kind of key-value store with the ability of deciding where to store replicas in the cluster and measure networking/computing delay. By adapting our solution to Anna, a key-value store from academia, we show the proposed state-layer is ideal to use as a cloud database for storing application states. To foster further research in this area, we make our proof-of-concept solution open-source.
更多
查看译文
关键词
key-value store,cloud-native paradigm,elasticity,stateless design,life-cycle,application states,individual application instances,application data,cloud database,application code,state access,cloud service,database instances,data locality,application functions,inter-host data access,data centers,service performance loss,pattern aware state storage method,called state-layer
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要