youtube image
From YouTube: Keep Persistent Volumes Healthy for Stateful Workloads - Xing Yang, VMware & Yuquan Ren, ByteDance

Description

Don’t miss out! Join us at our next event: KubeCon + CloudNativeCon Europe 2022 in Valencia, Spain from May 17-20. Learn more at https://kubecon.io The conference features presentations from developers and end users of Kubernetes, Prometheus, Envoy, and all of the other CNCF-hosted projects.

为有状态工作负载保持持久卷的健康性 | Keep Persistent Volumes Healthy for Stateful Workloads - Xing Yang, VMware & Yuquan Ren, ByteDance

越来越多的有状态工作负载已被迁移至 Kubernetes 平台。这些工作负载依靠持久卷来储存数据。然而,在有状态工作负载配置卷并予以使用后,底层储存系统可能会发生很多情况。该卷可能会因意外被删除、该卷所在的磁盘可能会发生故障、磁盘可能会持续退化影响其性能等。Kubernetes 如何及早发现这些问题并提醒用户?Kubernetes 引入了卷健康监测功能,以发现这些存储问题,并通过发送事件信息将这些问题公开给用户。虽然这种方式很有用,但是需要用户手动修复这些问题。如果 Kubernetes 侦测到卷异常情况后也有方法进行自动修正呢?在此次讨论中,我们将讨论目前卷健康监测功能有何作用,以及我们正在做哪些努力以将此功能提升至下一层次?

More and more stateful workloads have been migrated to Kubernetes platforms. These workloads rely on persistent volumes to store data. However, many things could happen to the underlying storage system after a volume is provisioned and used by a stateful workload. The volume could be deleted by accident, the disk that the volume resides on could fail, the disk may be degrading which affects its performance, etc. How can Kubernetes detect these problems early and alert users? The volume health monitoring feature has been introduced in Kubernetes to detect these storage issues and expose them to users by sending events. This has been very helpful, however, the problem has to be fixed by users manually. What if Kubernetes also has a way to do automatic correction after detecting abnormal volume conditions? In this session, we will discuss what the volume health monitoring feature can do currently and what we are working on to move this feature to the next level.