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: Reducing backup data by providing a data protection target for storing content data from clients running operating system and applications, and a common data protection target (CDPT) separate from the data protection target for storing Gold image data for the operating system and applications. During backup, user content data is copied from the client to the data protection target, and Gold image data is copied to the CDPT. It is also referenced in the DP target to prevent redundant storage. During backup, the CDPT is queried to determine if the Gold image exists, and if so, the DP target does not store the Gold image data in the DP target, but uses the reference to indicate the location of the Gold image data corresponding to the backed up content data. During a restore, the restore stream is built from the DP target and CDPT to combine user content data and Gold image data.

Abstract: Reducing backup data by providing a data protection target for storing content data from clients running operating system and applications, and a common data protection target (CDPT) separate from the data protection target for storing Gold image data for the operating system and applications. Gold image data is stored by a user in a defined location or tagged with a defined tag. The stored or tagged Gold image data is identified by the backup software and copied to the CDPT. The identified Gold image data is cataloged. During backup, the CDPT is queried to determine if the Gold image exists, and if so, the DP target does not store the Gold image data in the DP target, but uses the reference to indicate the location of the Gold image data corresponding to the backed up content data. During a restore, the restore stream is built from the DP target and CDPT to combine user content data and Gold image data.

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 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 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: A number of backup agents to be deployed to a system can be predicted by training one or more machine learning (ML) objects of a first prediction algorithm and training one or more ML objects of a second prediction algorithm. The training can be performed with archived backup job data. Both prediction algorithms can be applied to the backup job data to predict execution duration of the backup jobs. The prediction algorithm with a lower error can be used to predict a total execution duration of a current number of backup jobs. An optimal number of backup agents can be predicted based on the predicted total execution duration and the current number of backup jobs.

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: 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 the user based on their total score.

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 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 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: 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: 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.

Abstract: Embodiments for a system and method of monitoring performance metrics of a computer network, by defining key performance indicators for the user behavior in the computer network, collecting behavior statistics for each user for each of the key performance indicators, and providing one or more anomaly detection policies to define anomalous behavior of the users with respect to data assets of the computer network. An anomaly detection policy is applied to the collected behavior statistics to detect anomalous user behavior and an alert notification is sent to administrative or security personnel upon each detected instance of abnormal user behavior.

Abstract: Embodiments for monitoring performance metrics of a computer network by defining key performance indicators for the computer network, collecting performance data for the key performance indicators, and providing one or more anomaly detection policies to define anomalous performance of the computer network using defined threshold values. A policy is applied to the collected performance data to detect abnormal performance and a notification is sent to a user upon each instance of the detected abnormal performance. An alert tracking component is used to reduce alert generation by compiling and displaying past alert response data to allow a user to directly modify threshold values for alert generation and define temporary parameters to increase alert thresholds.

Abstract: Embodiments are described for a method and system of applying data protection software mechanisms to network 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. Embodiments include an efficient visual mapping aspect provided through a GUI to display the topography and backup/protection configuration of network devices in a system.

Abstract: Controlling data retention cost in cloud-based object storage by first obtaining current storage prices from the cloud provider for their different available storage tiers, and receiving user input for different possible retention parameters identity of data source and the retention period per storage tier. A cost calculator calculates the cost per time unit for each storage tier based on the current provider-specified price and the user-specified period. The calculated costs are displayed to the user a UI in tabular and/or graphical form. The user can change the retention period or data source parameters, and any impact of such changes on the cost will be calculated in real time and reflected in the graphical display. If the user changes the retention period to force an immediate movement of data from one tier to another, a data mover control facilitates this movement in the cloud object storage.