Emc IP Holding Company LLC

Gajendran Raghunathan

Shelesh Chopra

Matthew Dickey Buchman

Krishnendu Bagchi

Sudha Hebsur

Vipin Kumar Kaushal

Pallavi Prakash

Anand Reddy

Nitin Anand

Jaishree Balasubramanian

Niketan Narayan Kalaskar

Sainath Gonugunta

Shoukathali Chandrakandi

Yashomathi Krishnamurthy

Arathi Bhandari

Sunil Kumar Yadav

Soumen Acharya

Elango Chockalingam

Suman Chandra Tokuri

Sudha Vamanraj Hebsur

A backup storage includes a persistent storage and a backup manager. The persistent storage stores backups of entities and a global application data map. The backup manager obtains a restoration request for restoration of an application hosted by an entity of the entities; makes a determination to accelerate the restoration based, at least in part, on the application; in response to the determination: identifies a virtual disk level backup of the entity that is associated with the application using the global application data map; obtains the virtual disk level backup from the backups of the entities; and restores the application using the virtual disk level backup.

System and method for accelerated data access

A backup storage includes persistent storage and a backup manager. The persistent storage stores backups of entities and an entity list that lists the entities. The backup manager obtains a restoration availability request from a user; filters the entity list based on an identity of the user to obtain an available entity list; identifies, based on user input obtain based on the available entity list, an entity of the entities; and restores the entity using the backups.

System and method for limiting restoration access

A backup storage includes a persistent storage and a backup manager. The persistent storage stores virtual machine level backups and application level backups. The backup manager obtains a request for a point in time restoration of an application; identifies, based on the application, a virtual machine level backup of the virtual machine level backups that is associated with: a virtual machine that hosted an instance of the application and a first point in time prior to a restoration point in time specified by the request for the point in time restoration; identifies, based on the application, an application level backup of the application level backups that is associated with the restoration point in time; generates a point in time backup using: the identified virtual machine level backup, and the identified application level backup; and services the request using the point in time backup.

System and method for accelerated point in time restoration

Backing up availability group databases configured on multi-node virtual servers is described. A system identifies an availability group scheduled for backup. The system determines whether the availability group is configured on at least one virtual server in a cluster of nodes associated with the availability group. If the availability group is configured on at least one virtual server in the cluster of nodes, the system retrieves information from a server in the cluster of nodes. The system uses the retrieved information to identify a database replica that is preferred for backing up the availability group. The system identifies a virtual server, in the cluster of nodes, that is associated with the identified database replica. The system identifies a node for backing up the availability group by identifying an active node from the nodes in the identified virtual server. The system backs up the availability group via the identified node.

Backing up availability group databases configured on multi-node virtual servers

Embodiments describe concurrently backing up data associated with a relational database management system (RDBMS). In an embodiment, a request is received to back up data from multiple nodes to a target storage source. The multiple nodes are configured to provide storage services to data associated with the RDBMS and are communicatively coupled to a backup server configured to manage backup of one or more storage devices. In response to the request, one or more preference nodes are identified from multiple nodes based on a preference configuration. Using a backup algorithm, portions of the backup to be performed are assigned to one or more preference nodes selected from the identified preference nodes. The backup operations are initiated using the selected preference node(s). Each portion is a distinct subset of the data to be backed up and each of the selected preference node(s) is assigned a unique portion.

Parallel proxy backup methodology

In one example, a method for data backup includes surveying a database availability group (DAG) that includes multiple nodes which are each associated with one or more databases, to determine a distribution of the databases across the nodes. Next, federated logic is used to create a profile of the DAG based on the survey, and the profile is used to generate a dynamic preferred server order list (PSOL). Load balancing for the DAG is performed using the dynamic PSOL, and the dynamic PSOL is updated based on results of the load balancing. Finally, a federated backup of the databases is performed based on the updated dynamic PSOL.

Backup using instinctive preferred server order list (PSOL)

Embodiments described herein use a file server implementing a network file sharing protocol in an improved backup workflow in a storage system. The file server provides storage services to files stored in a plurality of storage devices via one or more file sharing protocols. In one embodiment, in response to a request to back up data that is received at the file server from an application server, the file server creates a snapshot of the data to be backed up using data stored in a source storage device. The file server sends the created snapshot to the target storage system for storage and sends a first notification to the application server indicating that the snapshot has been backed up in the target storage system. In addition, the application server sends a second notification to a backup server indicating that the data has been backed up.

Optimizing application data backup in SMB

In one example, a method for data backup includes surveying an environment, that has a plurality of nodes which are each associated with one or more databases, to determine a distribution of the databases across the nodes. A database profile is then created based on the survey and identifies a node with maximum ownership of databases. Next, a preferred server order list (PSOL) is generated that is based on the database profile, a last activation preference for one of the databases, and a failover preference for one of the databases. Using the PSOL, a backup workload is balanced across the nodes, and the databases are then backed up using the results of the backup workload balancing.

Backup operations for shared volumes are described. A shared volume is identified as used by a virtual machine scheduled for a backup operation by a first distributed system node. A second distributed system node is identified that has a responsibility for sending control signals to the shared volume. An association is saved of the second distributed system node to the shared volume. The responsibility for sending control signals to the shared volume is assigned to the first distributed system node. The backup operation is executed for the shared volume by the first distributed system node. The responsibility for sending control signals to the shared volume is assigned to the second distributed system node.

Growing community of inventors

Bengaluru, India

Gajendran Raghunathan