Abstract: A synthetic full backup of a source volume is retrieved, the synthetic full having been created from merging a backup chain including an incremental backup into a full backup. The full backup corresponds to a state of the source volume at a first time. The synthetic full corresponds to a state of the source volume at a second time, after the first time. A bitmap embedded into a snapshot of the source volume taken at the second time is retrieved. The bitmap identifies data from the source volume copied to secondary storage for the incremental backup. The backup chain is regenerated by copying from the snapshot the data identified by the bitmap to a regenerated incremental backup.

Abstract: A synthetic full backup of a source volume representing a state of the volume at a current time is retrieved, the synthetic full having been generated by merging a full backup of the volume performed at an initial time with an incremental backup of the volume performed at the current time, after the initial time. A bitmap tracking changes to the volume made between the initial and current times is accessed. The bitmap is used to identify a location on the volume having changes made between the initial and current times. First data written to the location on the volume is read. Second data written to the same location on the synthetic full backup is read. First and second checksums are generated based on the first and second data, respectively. The checksums are compared and if any do not match, an indication is generated that the synthetic full is corrupt.

Abstract: An incremental backup is made of a source volume on a production host to on premise secondary storage. The incremental backup includes a bitmap specifying locations of blocks that have changed since a last backup of the source volume, and data of the changed blocks. First checksums are calculated from data of the changed blocks. The incremental backup, including the changed blocks and the bitmap, are moved to cloud storage. The changed blocks are merged, at the cloud storage, with the last backup of the source volume to generate a synthetic full backup of the source volume. The bitmap is consulted to identify locations of the changed blocks. Second checksums are calculated from data written to the locations on the synthetic full backup. The first and second checksums are compared. If the first and second checksums do not match, an indication is generated that the synthetic full backup is corrupt.

Abstract: A backup manager for providing backup services includes persistent storage and a backup orchestrator. The persistent storage includes protection policies. The backup orchestrator generates a backup for a client based on the protection policies; obtains system metadata from the client; generates a backup map for the backup based on the system metadata; generates a backup hierarchy for the backup based on the backup map; and stores the backup and at least one selected from a group consisting of the backup hierarchy and the backup map.

Abstract: Described is a system (and method) for leveraging data previously transferred to a cloud-based object storage as part of a failed backup when performing a subsequent backup operation. The system may leverage the native configuration of an object storage that may retain certain data even when a backup operation is classified as a failed operation. To provide such capabilities, the system may store specialized metadata that tracks which backups have failed and metadata indicating which backup data has not been committed. Accordingly, upon a subsequent backup operation, the system may expediently refer to the stored metadata to identify retained backup data that may be reused for the subsequent backup. As a result, the system may improve the efficiency of a backup procedure by reducing the amount of data required to be transferred from the backup source.

Abstract: Creating vendor-neutral data protection operations for vendors' application resources is described. Capabilities specified for data protection operations by a vendor of an application are input from a host of the application. Any capabilities specified for the data protection operations are used to create a vendor-neutral version of a data protection operation for a resource of the application. The vendor-neutral version of the data protection operation for the application resource is output to the host. A result of performing the vendor-neutral version of the data protection operation on the application resource is input from the host.

Abstract: In one example, a method includes receiving, at a physical proxy node, a backup request from a client outside the cluster environment, the backup request identifies a VM that is to be backed up, and including data that resides on a virtual federated database that is an element of the cluster environment and to which respective databases of each node of the cluster environment are mapped, and the backup request is received at the physical proxy node due to the position of the physical proxy node in a PSOL. Next, initiating, with an agent at the physical proxy node, a save program on the physical proxy node, and initiating, with the save program, a secondary save process on the physical proxy node that is a federated backup process and includes reading the VM identification from the backup request, and backing up the VM identified in the backup request.

Abstract: A method and system for object metadata maintenance pertinent to object restoration. Concerning the realm of data protection, metadata, descriptive of data, may be considered as critical, if not more, than the data being protected itself. Metadata, amongst other purposes, may facilitate the rapid and/or efficient restoration of the data. Like data, metadata may also be susceptible to corruption due to various reasons. With corrupted metadata, restoration of the data may prove challenging. Accordingly, the disclosed method and system propose a framework through which metadata, if corrupted partially or wholly, may be repaired or rebuilt, respectively, using the data itself as references.

Abstract: Described is a system for managing the expiration of objects storing incremental backup data by leveraging specialized metadata. The system may provide a layer of intelligence when freeing up storage space on an object storage to ensure that a full recovery of client backup data may be performed when storing incremental backup data. The system may maintain metadata indicating the latest and/or earliest backups that reference particular objects. The system may then leverage this information to mark particular objects for removal (e.g. deletion or re-tiering). For example, the system may access the metadata to identify which objects stored by a previous (e.g. expired) backup are still referenced by a subsequent (e.g. non-expired) backup. As a result, the system may ensure that objects are not removed prematurely and that a full recovery of the client data to a point-in-time of any incremental backup may be performed.

Abstract: Described is a system for intelligent re-tiering of backup data stored on a cloud-based object storage. More specifically, the system may re-tier objects such that the system retains the ability to efficiently perform a full restore of backup data even when incremental backups are performed to a cloud-based object storage. To provide such a capability, the system may maintain a specialized metadata database that stores information indicating the backup time for each backup, and a list of objects required to perform a full restore to each of the backup times. Accordingly, when using a threshold time (e.g. expiry) to select object candidates for re-tiering, the system may leverage the metadata database to ensure that objects that may still need to be referenced are not unnecessarily moved to a lower storage tier.

Abstract: Described is a system (and method) for efficient access-based reallocation of backup data stored within an object storage. The system may implement various specialized procedures to efficiently store and manage backup data within the object storage. These procedures may include packing backup data into objects to improve data operation efficiency. The system may also conserve storage space on the object storage by performing an analysis to reallocate backup data as necessary. For example, data may be stored in objects in an immutable manner, and thus, the system may efficiently reallocate data to new objects based on data access patterns. For example, the system may determine an access pattern associated with live data remaining within the first object satisfies a condition, and in response, reallocated the live data to a new object.

Abstract: Techniques described herein relate to a method for generating backups of virtual machines. The method may include, in response to identifying a backup generation event associated with virtual machines: obtaining, by a backup agent, virtual machine metadata associated with the virtual machines; identifying groups of virtual machines based on the virtual machine metadata; provisioning resources to generate backups of the virtual machines based on the groups of virtual machines; and generating a backup of the virtual machines based on the groups of virtual machines using the provisioned resources associated with the groups of virtual machines.

Abstract: Backup operations may save a full backup and subsequent checkpoints. Systems and methods for handling backup and restore operations when checkpoints are deleted. Checkpoints can be merged during a restore operation to account for deleted checkpoints. Also, the backup can continue to leverage existing backups even though checkpoints have been deleted.

Abstract: A method and system for object metadata maintenance pertinent to object restoration. Concerning the realm of data protection, metadata, descriptive of data, may be considered as critical, if not more, than the data being protected itself. Metadata, amongst other purposes, may facilitate the rapid and/or efficient restoration of the data. Like data, metadata may also be susceptible to corruption due to various reasons. With corrupted metadata, restoration of the data may prove challenging. Accordingly, the disclosed method and system propose a framework through which metadata, if corrupted partially or wholly, may be repaired or rebuilt, respectively, using the data itself as references.

Abstract: A method and system for stream optimized backups to a cloud object store. When considering data protection, many prominent applications engage in backup operations by streaming their respective data to the cloud; however, the stream(s) is/are often ill-optimized (e.g., non-uniform data rates, non-uniform block sizes, different backup types, non-uniform data types or formats, etc.) to be written into cloud storage. The disclosed method and system, accordingly, propose a dynamic framework through which any arbitrary backup stream may be optimized according to the profile of any specific cloud-based object data store.

Abstract: A system including persistent storage for storing an object repository and a user data backup. The system also includes a manager that obtains fragmented user data associated with an object that is potentially duplicative of an object stored in the object repository; makes a determination that the object is duplicative based on a copy of the object stored in the object repository; in response to making the determination, adds the fragmented user data to a user data backup without adding the object to the backup; associates the fragmented user data in the user data backup with the copy of the object stored in the object repository; and stores the user data backup in the persistent storage.

Abstract: Embodiments described herein relate to a method for managing file based backups (FBBs). The method may include obtaining a FBB mount request for a FBB mount of a FBB from an application, wherein the application is executing in a production host environment and the FBB is stored on backup storage; in response to the FBB mount request: capturing an entity context associated with the application; authenticating the entity context; obtaining, when the authenticating is successful, access control information corresponding to the FBB from the backup storage; determining a subset of the FBB for which the access control information indicates the entity context has permission to access; and enabling access to a portion of the FBB by the application.

Abstract: Embodiments described herein relate to a method for managing file based backups (FBBs). The method may include obtaining a FBB mount request for a FBB mount of a FBB from an application, wherein the application is executing in a production host environment and the FBB is stored on backup storage; in response to the FBB mount request: enabling access to a portion of the FBB by the application; notifying a cyber sense device that the access is enabled; providing, to the cyber sense device, a storage location of the portion of the FBB for which access was enabled; receiving, from the cyber sense device, a security event notification; and performing, in response to the security event notification, a security action set.

Abstract: Described is a system for predictive storage policy selection for a cloud-based storage based on backup monitoring. The system may reduce storage costs incurred by a subscriber of a backup service that leverages a cloud-based storage. The system may monitor backup operations and collect backup statistics associated with the resource requirements of performing a backup to a cloud-based storage. To collect such information, the system may execute a specialized monitoring process that works in conjunction with a backup application and/or server. The collected information may be stored as part of a metadata database associated with the object storage. Accordingly, the system may retrieve the information from the metadata database to predict storage costs associated with performing future backup operations. Based on the predicted storage costs, the system may automatically select an appropriate storage policy.

Abstract: Systems and methods for performing differential and full data protection operations. Parameters that define minimum, interval, and maximum values are provided to an agent. These values relate to changes in the data or in a database. The agent monitors the database and backups are triggered in accordance with these values. A differential backup is not performed until the minimum value is reached and differential backups are performed only after subsequent intervals are reached. A full backup is performed once the maximum value is reached.