Abstract: The technology described herein is directed towards automating/orchestrating removal of one or more nodes of a node cluster, including in a cloud computing environment in which nodes in a cluster map to deployed virtual machines. An automated workflow can be started based on user input specifying an amount of capacity to remove, which corresponds to one or more nodes to remove. In a node cluster with associated nodes arranged into pools of nodes, node removal is per node pool. An orchestrated workflow performs pre-validation based on satisfying appropriate removal criteria, followed by data move and node removal jobs, and post-validation to check that removed capacity is generally as specified and that the remaining node layout is appropriate. Data of any removed node is re-protected, such as by restoring data from removed nodes to remaining cluster nodes in a manner that maintains the data with a data protection scheme.

Abstract: The technology described herein is directed towards automating/orchestrating removal of one or more nodes of a node cluster, including in a cloud computing environment in which nodes in a cluster map to deployed virtual machines. An automated workflow can be started based on user input specifying an amount of capacity to remove, which corresponds to one or more nodes to remove. In a node cluster with associated nodes arranged into pools of nodes, node removal is per node pool. An orchestrated workflow performs pre-validation based on satisfying appropriate removal criteria, followed by data move and node removal jobs, and post-validation to check that removed capacity is generally as specified and that the remaining node layout is appropriate. Data of any removed node is re-protected, such as by restoring data from removed nodes to remaining cluster nodes in a manner that maintains the data with a data protection scheme.

Abstract: The technology described herein is directed towards automating the replacement of a virtual machine when the hardware underlying the virtual machine fails, including in a cloud computing environment in which nodes in a cluster map to virtual machines being deployed within that cloud provider. An automated workflow to perform cluster self-healing is started upon detection of an unrecoverable instance failure of a virtual machine, e.g., because of underlying hardware failure. The failed virtual machine is terminated, and a new, replacement virtual machine that matches characteristics of the failed virtual machine is created to join the cluster. Data of the failed node is re-protected, such as by restoring data maintained with a protection scheme to remaining virtual machines of the cluster. When the data is re-protected and the replacement virtual machine has joined the cluster, the data is rebalanced across the cluster nodes, including to the new virtual machine.

Abstract: The technology described herein is directed towards automating the replacement of a virtual machine when the hardware underlying the virtual machine fails, including in a cloud computing environment in which nodes in a cluster map to virtual machines being deployed within that cloud provider. An automated workflow to perform cluster self-healing is started upon detection of an unrecoverable instance failure of a virtual machine, e.g., because of underlying hardware failure. The failed virtual machine is terminated, and a new, replacement virtual machine that matches characteristics of the failed virtual machine is created to join the cluster. Data of the failed node is re-protected, such as by restoring data maintained with a protection scheme to remaining virtual machines of the cluster. When the data is re-protected and the replacement virtual machine has joined the cluster, the data is rebalanced across the cluster nodes, including to the new virtual machine.

Abstract: Compression of data for a file system utilizing protection groups can be implemented and managed. A compression management component (CMC) can control compression of data via inline or post-process compression for storage in protection groups in memory, including determining whether to compress data, determining a compression algorithm to utilize to compress data, and/or determining whether to perform inline and/or post-process compression of data. CMC can generate protection group (PG) metadata for a PG in which compressed data is stored. PG metadata can comprise a logical extent map that describes which logical blocks contain compressed data, a list of cyclic redundancy check values for logical blocks, and a list of compression chunks that store individual metadata regarding individual compressed streams, wherein, for an individual compressed stream, the individual metadata comprises a compression format, compressed size, uncompressed size, and/or starting offset in physical space within the PG.

Abstract: Compression of data for a file system utilizing protection groups can be implemented and managed. A compression management component (CMC) can control compression of data via inline or post-process compression for storage in protection groups in memory, including determining whether to compress data, determining a compression algorithm to utilize to compress data, and/or determining whether to perform inline and/or post-process compression of data. CMC can generate protection group (PG) metadata for a PG in which compressed data is stored. PG metadata can comprise a logical extent map that describes which logical blocks contain compressed data, a list of cyclic redundancy check values for logical blocks, and a list of compression chunks that store individual metadata regarding individual compressed streams, wherein, for an individual compressed stream, the individual metadata comprises a compression format, compressed size, uncompressed size, and/or starting offset in physical space within the PG.