Abstract: Embodiments are directed to managing data in a file system that includes a plurality of storage nodes and a plurality of storage volumes in a cloud computing environment. Metrics associated with each storage volume may be monitored. In response to the metrics exceeding a threshold value, performing further actions, including: determining storage volumes that are unhealthy based on the metrics that exceed the threshold value; updating metadata associated with the storage volumes to indicate that the storage volumes are unhealthy; decoupling the unhealthy storage volumes from storage nodes coupled to the unhealthy storage volumes; determining replacement storage volumes based on the metadata associated with the unhealthy storage volumes; updating other metadata associated with the replacement storage volumes to indicate that the replacement storage volumes are healthy storage volumes; and coupling the healthy storage volumes with the storage nodes that were coupled to the unhealthy storage volumes.

Abstract: Embodiments are directed to managing data in a file system that includes a plurality of storage nodes and a plurality of storage volumes in a cloud computing environment. Metrics associated with each storage volume may be monitored. In response to the metrics exceeding a threshold value, performing further actions, including: determining storage volumes that are unhealthy based on the metrics that exceed the threshold value; updating metadata associated with the storage volumes to indicate that the storage volumes are unhealthy; decoupling the unhealthy storage volumes from storage nodes coupled to the unhealthy storage volumes; determining replacement storage volumes based on the metadata associated with the unhealthy storage volumes; updating other metadata associated with the replacement storage volumes to indicate that the replacement storage volumes are healthy storage volumes; and coupling the healthy storage volumes with the storage nodes that were coupled to the unhealthy storage volumes.