面向Kubernetes的多集群资源监控方案

应用系统的复杂化与微服务化促进了容器的广泛使用, 企业往往会根据业务需要使用Kubernetes搭建多个集群进行容器的编排管理与资源分配. 为实时监控多个集群的工作状态与资源使用情况, 提出了面向Kubernetes的多集群资源监控方案, 对Kubernetes提供的CPU、内存、网络以及存储指标进行采集, 根据采集数据的类型对部分数据进行计算以获取更直观的监控指标, 实现了多层级多类型的存储, 并提供监控数据的REST接口. 通过实验, 验证了本设计对集群资源的消耗低, 具有较好的性能.

Multi-cluster Resource Monitoring Scheme for Kubernetes

The increasing complexity and microservice of application systems promote the widespread use of containers. Enterprises often build multiple clusters for container arrangement and management and resource allocation with Kubernetes according to their business needs. To monitor the working status and resource usage by multiple clusters in real time, this study proposes a multi-cluster resource monitoring scheme for Kubernetes. The CPU, memory, network, and storage indicators provided by Kubernetes are collected, and part of the data collected are calculated according to their data type to obtain more intuitive monitoring indicators. As a result, multi-level and multi-type storage is achieved, and REST interfaces for monitoring data are provided. Experiments verify that this design consumes a small amount of cluster resources and achieves good performance.