Abstract: The methods and systems described herein provide a solution that allows the necessary drivers to be automatically injected into a restored or migrated virtual machine. In one solution, using an access node installed in the destination virtual cloud environment, the required drivers are injected into a restored operating system volume/disk after the source VM has been restored/migrated to the new environment. In another solution, a customized machine image is created comprising of tools necessary to determine and install necessary drivers during migrations. This machine image is then used to create an intermediary virtual machine that determines and injects the necessary drivers needed for the source VM to properly function with the destination hypervisor.

Abstract: An executable utility is injected into cloud-based virtual machines (VMs) that are subject to backups by a data storage management system tasked with protecting the cloud-based VMs and their associated data. The utility is injected into a target VM which is “live” and operating. The utility analyzes the VM’s live volume to discover data extents therein, and for each extent computes a respective checksum and determines whether the extent is a “hole.” Afterwards, checksums help identify changed data in successive snapshots of the live volume, so that only changed data will be read and backed up in incremental backups. Time is saved in performing the backup operation first by pre-warming the backup’s source volume in parallel with the utility analyzing the live volume, and second by skipping read operations for extents unchanged since a preceding backup. The resulting incremental backup operation is sped up as compared to prior art approaches.

Abstract: An executable utility is injected into cloud-based virtual machines (VMs) that are subject to backups by a data storage management system tasked with protecting the cloud-based VMs and their associated data. The utility is injected into a target VM which is “live” and operating. The utility analyzes the VM's live volume to discover data extents therein, and for each extent computes a respective checksum and determines whether the extent is a “hole.” Afterwards, checksums help identify changed data in successive snapshots of the live volume, so that only changed data will be read and backed up in incremental backups. Time is saved in performing the backup operation first by pre-warming the backup's source volume in parallel with the utility analyzing the live volume, and second by skipping read operations for extents unchanged since a preceding backup. The resulting incremental backup operation is sped up as compared to prior art approaches.

Abstract: An executable utility is injected into cloud-based virtual machines (VMs) that are subject to backups by a data storage management system tasked with protecting the cloud-based VMs and their associated data. The utility is injected into a target VM which is “live” and operating. The utility analyzes the VM's live volume to discover data extents therein, and for each extent computes a respective checksum and determines whether the extent is a “hole.” Afterwards, checksums help identify changed data in successive snapshots of the live volume, so that only changed data will be read and backed up in incremental backups. Time is saved in performing the backup operation first by pre-warming the backup's source volume in parallel with the utility analyzing the live volume, and second by skipping read operations for extents unchanged since a preceding backup. The resulting incremental backup operation is sped up as compared to prior art approaches.

Abstract: An executable utility is injected into cloud-based virtual machines (VMs) that are subject to backups by a data storage management system tasked with protecting the cloud-based VMs and their associated data. The utility is injected into a target VM which is “live” and operating. The utility analyzes the VM's live volume to discover data extents therein, and for each extent computes a respective checksum and determines whether the extent is a “hole.” Afterwards, checksums help identify changed data in successive snapshots of the live volume, so that only changed data will be read and backed up in incremental backups. Time is saved in performing the backup operation first by pre-warming the backup's source volume in parallel with the utility analyzing the live volume, and second by skipping read operations for extents unchanged since a preceding backup. The resulting incremental backup operation is sped up as compared to prior art approaches.

Abstract: An executable utility is injected into cloud-based virtual machines (VMs) that are subject to backups by a data storage management system tasked with protecting the cloud-based VMs and their associated data. The utility is injected into a target VM which is “live” and operating. The utility analyzes the VM's live volume to discover data extents therein, and for each extent computes a respective checksum and determines whether the extent is a “hole.” Afterwards, checksums help identify changed data in successive snapshots of the live volume, so that only changed data will be read and backed up in incremental backups. Time is saved in performing the backup operation first by pre-warming the backup's source volume in parallel with the utility analyzing the live volume, and second by skipping read operations for extents unchanged since a preceding backup. The resulting incremental backup operation is sped up as compared to prior art approaches.