Emc IP Holding Company LLC

Mahesh Reddy Appireddygari Venkataramana

Swaroop Shankar D H

Chetan Battal

Shelesh Chopra

Gururaj Reddy Kulkarni

Mahantesh M Ambaljeri

Swaroop Shankar Dh

Aneesh Kumar Gurindapalli

Sunil Kumar Yadav

Elango Chockalingam

Asif Khan

Avinash Kumar

Deepthi Urs

Tushar Dethe

Matthew Dickey Buchman

Chandrakantha T Nagaraja

Pradeep Viveki

Yagnavalkya Chennojwala

Lakshminarayanan Muniswamy

Divyangana Sisodia

One example method includes obtaining hop information of a metadata path for backup metadata, obtaining content sensitivity information indicating a relative sensitivity of backup data to an attack, based on the hop information and the content sensitivity information, selecting an encryption to be applied to the backup metadata, and applying the encryption to the backup metadata. The backup data may be encrypted with the same encryption algorithm that was used to encrypt the backup metadata.

Adaptive metadata encryption for a data protection software

A method for performing a backup operation includes obtaining, by a backup server, a backup request, wherein the backup request specifies a virtual machine to be backed up, wherein the virtual machine is hosted by a production host, and in response to the backup request: obtaining classification data from the backup agent, initiating a backup classification on an unprocessed backup associated with the virtual machine based on the classification data to obtain a sensitivity tag, and initiating a data processing on the unprocessed backup based on the sensitivity tag.

System and method for a content based classification and adaptive data encryption

The method includes obtaining, by a restoration policy manager, a restoration request for a plurality of application containers, and in response to the restoration request: obtaining, by a backup server, container information associated with the plurality of application containers, assigning a restoration type to each application container in the plurality of application containers, updating a restoration type list based on the assigning, and initiating a restoration of the plurality of application containers using the restoration type list.

System and method for an application container prioritization during a restoration

Embodiments are described for performing an uninterrupted backup in a storage system responsive to an abort event. A backup agent receives a plurality of file objects to be backed up on a target device during a first backup session. The backup agent initiates a parent interrupt service routine (ISR), which generates a plurality of child ISRs. Each of the plurality of child ISRs monitors a backup state of a corresponding file object. The parent ISR generates a virtual file object queue (VFOQ) to store a current backup state of each of the plurality of file objects. When an abort occurs, the current backup state of each of the plurality of file objects is saved in a respective child ISR of that file object. During a subsequent backup session, backup of the plurality of file objects commences based on the current backup state of each of the plurality of file objects.

Uninterrupted file level backup operation using a virtual object file queue

A method for generating a backup schedule, that includes receiving, by a scheduling agent, an event entry specifying an event associated with a container, determining that the event entry specifies an alert event, adding the event entry to a plurality of historical event entries in a historical event repository, determining that the plurality of historical event entries indicates a repeating error state of the container, determining that an error frequency of the repeating error state is greater than an existing backup frequency of a container backup schedule, and generating a backup schedule warning indicating a recommended backup frequency.

Methods and systems for determining backup schedules

A backup management system for providing data integrity services to an application host that hosts an application that uses application data includes storage for storing threshold values for creating an application backup and a processor programmed to monitor: a rate of change associated with the application data, and an input-output rate of the application data; make a determination, based on the threshold values, the rate of change, and the input-output rate, that an unscheduled backup for the application is to be generated; obtain a micro-backup for the application in response to the determination; and obtain a restoration ready backup for the application using the micro-backup and at least one previously generated backup.

System and method for micro-backup generation

A backup management system includes storage and a processor. The processor filters copies of storage system transactions of a service device using a block level filter to identify a portion of the storage system transactions impacting a protected data asset; obtains at least one data protection metric based on the portion of the storage system transactions; makes a determination that the at least one data protection metric indicates that the backup schedule will not provide the protected data asset with a predetermined level of data protection; in response to the determination: generates a service-device initiated backup for the protected data asset; stores the service-device initiated backup in backup storage; and remediates a backup schedule for the service device based on the service-device initiated backup.

System and method for service device initiated backup generation

A method for a backup operation in accordance with one or more embodiments of the invention includes obtaining, by a vulnerability analyzer executing on a backup server, a plurality of container event entries, wherein a container event entry of the plurality of container event entries specifies a an application container identifier, a container event identifier, an event severity, and an event type, selecting the container event identifier, identifying a portion of the plurality of container event entries that specify the container event identifier, generating a mean event severity based on the portion of the plurality of container event entries, generating a first vulnerability value associated with the application container identifier, and initiating a backup policy update based on a vulnerability ranking, wherein the vulnerability ranking is based on the first vulnerability value.

System and method for an application container evaluation based on container events

A method and system for prioritizing critical data object storage during backup operations. Specifically, the method and system disclosed herein entail reordering data objects, awaiting being written to storage and thus queued in one or more data object queues, in accordance with a nearest-critical based sequential order. The nearest-critical based sequential order may be derived through modified weight-based Euclidean distances calculated between adjacent data object pairs queued in any given data object queue. Further, the calculated modified weight-based Euclidean distances incorporate data criticality factors associated with the adjacent data object pairs. By reordering data objects in a nearest-critical based sequential order, critical data objects may be written into storage first, thereby avoiding possible critical data loss should a disaster occur during backup operations.

Method and system for prioritizing critical data object storage during backup operations

A method for performing a backup operation includes obtaining, by a backup server, container information associated with a plurality of application containers, generating a container score for each application container in the plurality of application containers based on the container information, identifying a resource availability for a backup agent associated with the plurality of application containers, generating an ordering of the plurality of application containers based on the availability and the container scores, and sending a prioritization list update request to the backup agent based on the ordering.

System and method for an application container backup prioritization based on container information and resource availability

A method for performing backup operations includes obtaining, by a stream allocator operating in a backup storage system, a plurality of media management entries, wherein a media management entry of the plurality of media management entries specifies a data object, a relative priority, and a maximum number of streams, selecting the media management entry based on the relative priority, allocating a number of backup streams to the data object based on the maximum number of streams, and initiating a transfer of a backup of the data object from the production host to the backup storage system.

System and method for a dynamic data stream prioritization using content based classification

Methods and systems for restoring data to a host device are described. According to some embodiments, a hybrid buffer may be used to generate a twin file of each file object to be restored and append the twin file to the corresponding file object. Each file object and its corresponding twin file may be transmitted to a construction container via a restore agent. In the event of an unexpected abort during the first restoration session, the restore agent may preserve the twin file of a file object currently being restored (if one has been created at the time of the abort) and instruct the hybrid buffer to terminate operation. During a subsequent restore session, the restore agent may poll for the preserved twin file and commence the data restore operation from the file object currently being restored using the twin file.

Uninterrupted file level restore service using siamese engine

A method for performing a backup operation includes obtaining a backup request, wherein the backup request specifies a virtual machine (VM) set, and, in response to the backup request: identifying a first set of virtual machines (VMs), wherein the first set of VMs comprises a first portion of the VM set, performing a criticality analysis on the first set of VMs using a machine learning algorithm and a trained machine learning model to obtain an ordered list of critical VMs, performing a non-critical VM prioritization on a second set of VMs using the machine learning algorithm and the trained machine learning model to obtain an ordered list of non-critical VMs, consolidating the ordered list of critical VMs and the ordered list of non-critical VMs to obtain a final list, and initiating a backup of virtual machines using the final list.

System and method to achieve virtual machine backup load balancing using machine learning

A method for backing up a storage volume that includes receiving, by a volume manager, a block allocation table of a cloned storage volume backup, selecting a modification entry that comprises a volume offset for modified file data, obtaining a backup offset for the cloned storage volume backup based on the block allocation table and the volume offset, updating, based on the backup offset, the block allocation table to obtain an updated block allocation table, and sending the modified file data and the updated block allocation table to a backup server.

Methods and systems for performing data backups

A method for managing data includes obtaining, by a backup agent, a migration request, wherein the migration request specifies a plurality of users, and in response to the migration request: identifying a set of source-format data sets in a backup storage system, mounting the set of source-format data sets from the backup storage system, performing data mining on the set of source-format data sets in response to the mounting to obtain a hierarchical structure, generating a cloud-based service user account for each user of the plurality of users, wherein the cloud-based service user accounts are associated with a cloud-based service, obtaining source-format data sets associated with each user of the plurality of users using the hierarchical structure, and initiating a migration of the source-format data sets to the cloud-based service.

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Bengaluru, India

Mahesh Reddy Appireddygari Venkataramana