Abstract: Embodiments for a storage classifier that provides recommendations to a backup server for storage targets among a plurality of disparate target storage types. The storage classifier receives metadata (name, type, size), and the Service Level Agreement with information such as: retention time, Recovery Point Objective, and Recovery Time Objective) from the backup software. The backup software itself receives policy recommendations from a data label rules engine based on certain file attributes. The storage classifier receives an initial recommendation for the storage type and location (e.g., on-premises deduplication storage or public-cloud object storage, etc.) from a data classifier. Based on these inputs, the storage classifier provides recommended specific storage targets to the backup software on a file-by-file basis for data stored in a backup operation.

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 optimizing multiple backup operations 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 a plurality of transfer windows for transfer data between a source and destination; then determining 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 the backup operation that results in a shortest data transfer time over all of the transfer windows from as compared to other possible transfer windows in a defined backup period.

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: 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, 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: In general, embodiments of the invention relate to a method and system for backing up data. More specifically, embodiments of the invention are directed to using a scalable backup infrastructure that enables portions of the backup process to be performed in parallel. The amount of parallelism that may be implemented in the backup process may be dynamically adjusted based on customer requirements and/or limitations on the computing devices, backup storage, and/or production storage that are used to perform the backup process.

Abstract: Described is a system for a Policy Derivation Engine (PDE) that, when accessed by one or more organizations, assists such organizations in updating and managing data protection policies based on external policy updates from one or more other organizations that share the same organizational peer group. The system receives a policy request from a first computing system associated with a first organization. The system computes a list of peer organizations of the first organization. The system builds policy update data based on respective policy data received from one or more peer organizations and transmits at least a portion of policy update data to the first computing system associated with the first organization.

Abstract: Embodiments for recording application program interface (API) calls through an API recorder component or process that captures API calls as they are used by a number of users. API flows can be recorded to define recorded macros. An API collector collects API data for executed APIs and macros for storage in an API collection database and API performance analysis using at least one of a sequence analyzer, a runtime analyzer, a usage frequency analyzer, and an error analyzer. Output from the analyzers is provided to a user for review and determination of API improvement with respect to error reduction, API sequencing, runtime reduction, and usage frequency.

Abstract: A three-phase full quorum commit method enabling backing up of network devices that do not offer direct hooks in order to have application consistent protection. Devices are verified to be ready to perform a backup, and a condition of reaching and maintaining a full quorum of devices within a maximum time period is required before the system can be backed up. The three phase backup process reduces the chance of changes to network devices from corrupting consistency among the saved states of the different and disparate network devices. Multiple devices of different makes and models participate together as a unified backup as a network partition and all devices are verified as being in a ready state. The device configuration data is moved from device memory to local disk, and can then be tiered to secondary storage.

Abstract: Embodiments for executing selected remediation scripts to remedy issues in a data storage system through an API/script recorder component or process that presents a DVR (digital video recorder)-like interface and capability to capture scripts and API calls as they are used when navigating a graphical user interface (GUI). Internal components of this function perform the recording and macro creation to allow constant playback of these recorded and selected scripts. By easily generating and managing scripts macros, system administrators can easily re-execute customer workflows to apply known fixes to current issues in the data storage system.

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: Embodiments for optimizing a cost of storing backup data in an object store of a public cloud network provided by a cloud provider by storing delta objects each embodying changes to blocks of the backup data between a full backup incremental backups. The delta objects are each of a same block size, which can be changed. The process selects two sequential delta objects to form a larger object by extending each block to a minimal part size that is larger than the block size and inserting a region of unchanged data between the two delta objects. The larger object is divided into three different parts comprising the inserted region, and each of the extended delta object blocks. The process calculates an API and a compute cost for a synthesis operation on the delta objects based on a cost model and current price schedule of the cloud provider for the three different parts, and for the substantially larger object as a whole. The process selects a block size for the delta objects based on a lowest calculated cost.

Abstract: According to one embodiment, one or more consistent states of a virtual machine (VM) are backed up and stored. An index library is used to extract, from the consistent state(s) of the VM, metadata corresponding to content files captured in the consistent state(s). The extracted metadata is stored into a metadata catalog, where the metadata catalog is subsequently downloaded by an index server to index the content files captured in the consistent state(s).

Abstract: Storing documents in an object store in the cloud by creating a container for the documents, defining a document record including unique document ID and an index. A backup record for every backup includes a timestamp for each backup, and a bitmask for each document in the container has a single bit position for each document to indicate the corresponding document as unchanged or that it has been changed/deleted. Each bit location in the bitmask is referenced by the index in the document record. Large documents have a multi-part record identifying the containers. During point-in-time recovery, containers that match a given timestamp are found, and documents where the bitmask bit is set are restored.

Abstract: Embodiments for recording application program interface (API) calls through an API recorder component or process that captures API calls as they are used by a number of users. API flows can be recorded to define recorded macros. An API collector collects API data for executed APIs and macros for storage in an API collection database and API performance analysis using at least one of a sequence analyzer, a runtime analyzer, a usage frequency analyzer, and an error analyzer. Output from the analyzers is provided to a user for review and determination of API improvement with respect to error reduction, API sequencing, runtime reduction, and usage frequency.

Abstract: Embodiments for automating backup policy application to users in a data protection system of an organization, by defining a plurality of backup policies to apply to data processed by users in the organization, wherein each backup policy dictates a different performance characteristic based on storage cost and target storage type and location. Next, identifying a hierarchical position of a user within the organization and determining communication and grouping behavior of the user within the organization. A score is calculated for the user based on their hierarchical position and communication and grouping behavior, and an appropriate backup policy is assigned to a data processing device operated by the user based on the total score for the user.

Abstract: Embodiments for automating backup policy application to users in a data protection system of an organization, by defining a plurality of backup policies to apply to data processed by users in the organization, wherein each backup policy dictates a different performance characteristic based on storage cost and target storage type and location. Next, identifying a hierarchical position of a user within the organization and determining communication and grouping behavior of the user within the organization. A score is calculated for the user based on their hierarchical position and communication and grouping behavior, and an appropriate backup policy is assigned to the user based on their total score.

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.

Abstract: Storing data in an object store in cloud-based storage for data protection applications to address key user workflows, and provide an easily and seamlessly scalable system that minimizes the cost economics of the various resources, considers how backups are transmitted and which target data is most important during a restore operation. The system uses a client-server model in which data sources in a client store data to a cloud-based server that manages each data source as a separate namespace. The server process breaks up each data source into a series of fixed size sequential blocks, and uses a specialized change record type comprising reverse delta objects to synthesize full backup images from a first full image, wherein the full backup images are stored for every point in time in the object store. This provides a full backup to be available for client retrieval at any desired point in time. A simple block hash catalog is provided to reduce data duplication.

Abstract: Embodiments for automating backup policies applied to users in an organization by defining backup policies based on hierarchical positions of users within the organization as modified by any communication and grouping behavior of the user within the organization. A social graph generator utilizes relevant relationships revealed by active participant communications to create a greater knowledge of data usage within the enterprise to generate social graphs that quantify a type of commonality between people. The integration of social graph information in calculating a score based on hierarchical data adds organizational awareness to the process by factoring in people's communication patterns within the organization and leverages any links that are revealed by such patterns.