Abstract: Embodiments automate the timely remediation of issues by matching failed operations to a script that is configured to fix the problem or problems without causing additional side effects, thus minimizing unavailability of services and loss of data. A method detects a backup operation alert message sent from a data manager or storage system that encodes one or more attributes affected by the backup operation, wherein the attributes are weighted to reflect a percentage importance of the a corresponding script to fix the problem. A script library is scanned to identify scripts that match the alert message. A component generates a score for each script, where the score factors the relevance of the script to the backup operation based on the weighted attributes, and executes the script with the highest score, as the script most likely to fix the issue causing the alert message.

Abstract: Embodiments automate the timely remediation of issues by matching failed operations to a script that is configured to fix the problem or problems without causing additional side effects, thus minimizing unavailability of services/data and loss of data. A method detects a backup operation alert message sent from a data manager or storage system that encodes one or more attributes affected by the backup operation. A script library is scanned to identify scripts that match the alert message. A component generates a score for each script, where the score factors the relevance of the script to the backup operation, and executes the script with the highest score, as the script most likely to remediate the issue causing the alert message.

Abstract: Embodiments are described for storing array snapshots of a block-based system in networked storage, such as an NAS or SAN device. A system and process determines a size of the block device and splits it into a number of slices based on the size of the block device, with each slice comprising slice data. The slice data is written to protection storage either directly or through temporary buffer memory. The slice number and memory location for the slice data is stored in a key/value map, where the key comprises the slice number, and the value comprises the location. Backup agents are deployed to back up the slice data for each slice of the block device to the networked storage, and the slice data is stored as array snapshots in the network storage.

Abstract: Embodiments are described for preventing undesired data deletion on protection storage by using delete restrictions. A delete restriction component prevents data from being staged for permanent erasure, such as by preventing files from being moved to a trash folder. A well-known process (WKP), such as a backup or migration operation that is known to request data expiration, is used to validate data deletions. The WKP identifies data that is no longer to be retained. The WKP uses a well-known process expiration list (WEL) that holds hashes of the data. A bucket confirmation count indicates candidates for data deletion. Separately, Garbage Collection maintains another list of hashes that are deletion candidates. A separate process finds common hashes between the WKP and GC hashes, and then removes the data pointed to by the common hashes.

Abstract: Embodiments for managing metadata in a high density network attached storage system. A change file list is obtained though external or internal crawler processes. A slicer creates multiple slices of the entire fileshare to enable parallel backup of the slices. A backup engine creates a separate backup containers and separate metadata files for each slice. The individual metadata files are combined into a single consolidated metadata file, and the individual metadata files are then deleted. The consolidated metadata file contains all of the elements comprising the entire fileshare, and a corresponding container ID is also added to each entry of the file. Another table contains details of the sub-assets and their backup properties. A backup agent obtains the backup IDs for the individual sub-assets, using a job ID field for a backup query operating on the single consolidated metadata file.

Abstract: Optimizing multiple backup operations for multiple sources by discovering shared data routes between sources and targets for backup operations performed in a certain time period. Backups using shared routes use a Best Time Algorithm that determines a size of a dataset to be saved an available bandwidth in each transfer window of the time period, and then determines an order of the backup operations based on first ordering the backups based on decreasing dataset size and second ordering the transfer windows in order of decreasing bandwidth, and matching the backups to the transfer windows in accordance with the first ordering and second ordering. The optimum time represents a time to initiate each backup of the multiple backups that results in a shortest data transfer time over the entire time period.

Abstract: A portable, self-contained data mover container with all required packages for data management, and which can be hosted on a physical host, VM, cloud or appliance, such as a storage array. The data mover container protects multiple workloads such as NAS, native OS filesystem, applications, and so on. An automated process spins up and tears down containers without any impact on the host. If a container fails to run on a host if desired resources are not available, it automatically runs on other hosts for same data set. Minimal user intervention to achieve scale and performance is required, as the system automatically computes the desired number of containers required depending upon dataset and available resources. Containers can be patched and upgraded independently on a host without making any change to the hosting environment.

Abstract: Optimizing backups for a data protection system by determining a size of a dataset to be saved in each backup operation and an available bandwidth in each transfer window of transfer windows for data transfers between a source and destination. An order of the backup operations is defined based on first ordering the backups based on decreasing dataset size and second ordering the transfer windows in order of decreasing bandwidth, and matching the backups to the transfer windows in accordance with these orderings. A dynamic window sizing process determines an initial change between the minimum and maximum bandwidth utilization over a period of time and then iteratively split and consolidate the time blocks until optimal utilization over the time period is reached.

Abstract: Embodiments are described for a method and system of applying data protection software mechanisms to network equipment devices to auto-discover the networking equipment, save changes from memory (TCAM) to local storage, backup changes to protection storage, provide auditing and tracking history of changes, and provide the ability to deploy test/development copies of changes using software defined networking techniques.

Abstract: Embodiments for a method of storing e-mail messages using a cloud native e-mail data protection process. E-mail messages are first compressed and stored in a container along with selected metadata. An Email Record is created for each e-mail message. A Container Record is created for each newly created container, and a Backup Record is created for each container for each backup. Once the required records are created, the process facilitates the execution of backup operations, such as full or incremental backups of the stored e-mail messages. Data tiering is supported so that low cost object storage in the public cloud is used instead of expensive processing methods, such as deduplication backups.

Abstract: Embodiments for optimizing a backup operation for a data protection system, by connecting with network devices in a network implementing the backup operation, the backup operation implementing a policy that specifies a plurality of service requirements and that is initiated at a time within a plurality of time windows, and determining a size of dataset to be backed up by the backup operation. The method further monitors a flow of data between a source and a destination of data in the network, compiles historical data of operational parameters for data transfers between the source and destination, and determines an optimum time within the plurality of time windows based on the dataset size and the historical data.

Abstract: Embodiments for a method of storing documents using a document data protection process. Documents are first compressed and stored in a container along with selected metadata. An Document Record is created for each document. A Container Record is created for each newly created container, and a Backup Record is created for each container for each backup. Once the required records are created, the process facilitates the execution of backup operations, such as full or incremental backups of the stored documents. Data tiering is supported so that low cost object storage in the public cloud is used instead of expensive processing methods like deduplication. A user interface receives a user setting dictating a storage media storing the container based on a relative availability of the storage media versus cost of storage.

Abstract: Embodiments are described for storing array snapshots of a file system in networked attached storage (NAS) device. A system and process determine an organization of the file system comprising directories and files in a defined hierarchy, and a size of each file and a number of files in each directory. One or more slicer processes slice the file system into a number of slices, wherein each slice contains at least one of: a defined number of files or files having a defined total size. Backup agents are deployed as proxies to back up the slices to the NAS device, and the slices are backed up as array snapshots in the NAS device.

Abstract: Optimizing backups for a data protection system by determining a size of a dataset to be saved in each backup operation and an available bandwidth in each transfer window of transfer windows for data transfers between a source and destination. An order of the backup operations is defined based on first ordering the backups based on decreasing dataset size and second ordering the transfer windows in order of decreasing bandwidth, and matching the backups to the transfer windows in accordance with these orderings. A dynamic window sizing process determines an initial change between the minimum and maximum bandwidth utilization over a period of time and then iteratively split and consolidate the time blocks until optimal utilization over the time period is reached.

Abstract: Tracking changes to a document by defining a document record having a unique document record and comprising an index and a file name of the document, and defining a backup record for the document in a series of backups, which includes a timestamp for each backup, and a bitmask for the document. The bitmask has a single bit position for each document in the container which is set to a first binary value to indicate that the corresponding document is unchanged and a second binary value to indicate whether the document is changed or deleted. A primary query is received and resolved for the document by analyzing the document record to find the file name. A secondary query using the document record ID is resolved to find all tracked versions of the document, and the results are returned to the user in the form of a version history list.

Abstract: Embodiments for a method performing data migration such as backups and restores in a network by identifying characteristics of data in a data saveset to separate the data into defined types based on respective characteristics, assigning a data label to each defined type by receiving user selection or automatically merging or selecting a priority label, from among many labels associated with a file, defining migration rules for each data label, discovering assigned labels during a migration operation; and applying respective migration rules to labeled data in the data saveset. The migration rules can dictate storage location, access rights, replication periods, retention periods, and similar parameters.

Abstract: Optimizing multiple backup operations for multiple sources by discovering shared data routes between sources and targets for backup operations performed in a certain time period. Backups using shared routes use a Best Time Algorithm that determines a size of a dataset to be saved an available bandwidth in each transfer window of the time period, and then determines an order of the backup operations based on first ordering the backups based on decreasing dataset size and second ordering the transfer windows in order of decreasing bandwidth, and matching the backups to the transfer windows in accordance with the first ordering and second ordering. The optimum time represents a time to initiate each backup of the multiple backups that results in a shortest data transfer time over the entire time period.

Abstract: Embodiments for optimizing a backup operation for a data protection system, by connecting with network devices in a network implementing the backup operation, the backup operation implementing a policy that specifies a plurality of service requirements and that is initiated at a time within a plurality of time windows, and determining a size of dataset to be backed up by the backup operation. The method further monitors a flow of data between a source and a destination of data in the network, compiles historical data of operational parameters for data transfers between the source and destination, and determines an optimum time within the plurality of time windows based on the dataset size and the historical data.

Abstract: Optimizing backups for a data protection system by determining a size of a dataset to be saved in each backup operation and an available bandwidth in each transfer window of transfer windows for data transfers between a source and destination. An order of the backup operations is defined based on first ordering the backups based on decreasing dataset size and second ordering the transfer windows in order of decreasing bandwidth, and matching the backups to the transfer windows in accordance with these orderings. A dynamic window sizing process determines an initial change between the minimum and maximum bandwidth utilization over a period of time and then iteratively split and consolidate the time blocks until optimal utilization over the time period is reached.

Abstract: Restoring data stored by a backup process in an object store of a cloud network by initiating a restore request to a server accessing the object store, by providing a source identifier of one or more data blocks of the requested data and a timestamp for a backup image at a requested point in time (PIT). The server manages a queue of blocks in temporary storage to provide blocks for retrieval by the client, and initially fills the queue with blocks from a full backup and unchanged by any incremental backup to the requested PIT. In response to the request, the server assembles blocks that are changed from the full backup through one or more incremental backups to the requested PIT using a full block synthesis process employing forward and reverse delta objects, and sends to the client the blocks initially filled in the queue with the assembled blocks to return a full PIT backup image for the requested PIT.