Emc IP Holding Company LLC

Dell Products Inc.

Mahantesh M Ambaljeri

Shelesh Chopra

Chetan Battal

Mahesh Reddy A V

Gururaj Reddy Kulkarni

Swaroop Shankar Dh

Rahul Deo Vishwakarma

Mahesh Reddy Appireddygari Venkataramana

Swaroop Shankar D H

Iresha R Gadikar

Girish Chandra Belmanu Sadananda

Parmeshwr Prasad

Battal Chetan

Raghuprasad Prasad

Amitabh Mehta

Siddappa N Ambiger

Pradeep Viveki

Amith Ramachandran

Gopal Singh

Venkatraman Venkatasubramanyam

Mahesh Rao

Jafarullah Noordeen

Sunil Amban Kandambeth

Kruthi Ramesh

Ramesh Chilukoti

Srinivasan Govindaraju

Gururaj Kulkami

A method for managing a client environment includes obtaining a notification for an auto-generated service request, wherein the auto-generated service request is associated with a configuration of nodes in the client environment, in response to the notification: obtaining metadata associated with the auto-generated service request, analyzing the metadata to extract current node configuration details, comparing the current node configuration details to an node optimization model, making a determination, based on the comparing, that an optimization is required, based on the determination, performing a re-configuration on the nodes in the client environment.

System and method for managing automatic service requests for scaling nodes in a client environment

A method for managing a client environment includes obtaining a notification for an auto-generated service request, wherein the auto-generated service request is associated with an issue with the client environment, in response to the notification: obtaining metadata associated with the auto-generated service request, analyzing the metadata to extract pattern information, comparing the pattern information to a service request pattern database, making a determination, using the service request pattern database, that a recommendation is associated with the pattern information, and based on the determination, performing a remediation action associated with the recommendation.

System and method for managing automatic service requests for workload management

A method for managing a data protection module (DPM) includes: obtaining metadata associated with the DPM; analyzing the metadata to extract relevant data; making, based on the relevant data, a first determination that a resource-related change has occurred in the DPM; making, based on the first determination, a second determination that the resource-related change is an increased resource-related change; sending, based on the second determination, the relevant data to a vendor environment (VE) analyzer; in response to sending the relevant data, receiving a recommendation from the VE analyzer; sending the recommendation to a user of a client about the recommendation using a graphical user interface (GUI) of the client; making, after sending the recommendation to the user, a third determination that the DPM is not reconfigured by the user based on the recommendation; and resending, based on the third determination, the recommendation to the user using the GUI.

Method and system for reconfiguring a data protection module based on metadata

A method for managing a data protection module includes: obtaining client metadata associated with client environment (CE) data protection modules, in which the client metadata includes first product configuration information; obtaining vendor metadata associated with a vendor environment (VE) data protection module, in which the vendor metadata includes second product configuration information; analyzing the client metadata and vendor metadata to extract relevant data; obtaining product features that are commonly utilized by at least one user of the CE data protection modules; making a first determination that a mismatch exists between the client metadata and vendor metadata; generating a ranked list of the product features that are commonly utilized; identifying a product feature that has the highest rank in the ranked list; making a second determination that the mismatch is a vendor-related mismatch; and sending a recommendation to a user of the VE data protection module to manage the mismatch.

Method and system for identifying product features based on metadata

A method for managing a data protection module (DPM) includes: obtaining an alert generated by the DPM within a predetermined period of time; obtaining metadata associated with the DPM; analyzing the metadata to extract relevant data; analyzing the alert to extract second relevant data; making, based on the second relevant data, a determination that a tolerance level associated with the alert has been exceeded; sending, based on the determination, the alert, the relevant data, and the second relevant data to a vendor environment (VE) analyzer; in response to sending the alert, the relevant data, and the second relevant data, receiving a service request (SR) generated by the VE analyzer for the DPM; and providing the SR to the client to notify a user of the client about the SR using a graphical user interface (GUI) of the client.

Method and system for generating an automatic service request based on metadata

Methods and systems for restoring data are described. According to some embodiments, the method, in response to receiving a first restore request, initiates a second restore request to a hybrid data buffer to route blocks of backup data to the hybrid data buffer. The method further invokes an interrupt service routine (ISR) that is initialized with reserved addresses. When the blocks of backup data are transmitted to the hybrid data buffer, the method further tags, by the ISR, the blocks of backup data to a specified location, where the specified location is one of the reserved addresses.

Uninterrupted block-based restore operation using a read-ahead buffer

In general, in one aspect, the invention relates to a method for enabling enhanced logging. The method includes obtaining a log associated with a job; determining, using the log, that enhanced logging is to be enabled prior to initiating the job; enabling, in response to the determination, enhanced logging on at least one node, and initiating servicing of the job, after the enabling, on the at least one node.

Intelligently determining when to perform enhanced logging

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 managing a data protection module includes: obtaining client metadata of a client environment data protection module (CEDPM); analyzing the client metadata to extract relevant data; inferring at least a period of time a first user of the CEDPM spent to initiate performing a task, a number of steps taken by the first user to initiate performing the task, and a number of attempts made by the first user to initiate performing the task; obtaining at least an ease of use score, an automation efficiency score, and a success score for a product feature; obtaining a maturity rating for the product feature based on the scores; determining that the maturity rating for the product feature is less than a predetermined maturity rating; and sending a recommendation to a second user of a vendor environment (VE) data protection module to manage the maturity rating for the product feature.

Method and system for identifying user behavior based on metadata

A method and system for health rank based virtual machine restoration using a conformal framework. With respect to enterprise data protection, solutions need to address two primary responsibilities: at the onset of failure or disaster, restore any running applications, as well as any lost or damaged data; and minimize (if not eliminate) the future occurrence of such failures or disasters. In tackling the latter responsibility, the disclosed method and system leverage health-score assessments to ensure the restoration of virtual machines onto healthy infrastructure. The aforementioned health-score assessments employ clustering to identify, and a conformal framework to rank, healthy hosts onto which virtual machines may be restored.

Method and system for health rank based virtual machine restoration using a conformal framework

For restoring data, a system with uninterrupted block-based restore has a hybrid container. The hybrid container has an operational buffer and a virtual container unit. The system receives blocks of data from a target device into the hybrid container and sends the blocks of data from the hybrid container to a destination device for a restore session. The system writes information about the blocks of data into one or more virtual containers. If there is an abort of the restore session, the system freezes state of the hybrid container and the virtual container(s). For a next restore session that resumes from where the aborted restore session stopped, the system resumes receiving blocks of data from the target device into the hybrid container and sends only leftover blocks of data to the destination device in accordance with the information in the virtual container(s).

Uninterrupted block-based restore using a virtual container

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 method and system for risk score based asset data protection using a conformal framework. Concerning Internet-of-Things (IoT) environments, there is a growing challenge to ensure the availability and continuity of applications executing, as well as relevant application data maintained, on IoT devices, in order to mitigate potential operational failures and/or interruptions. The disclosed method and system address this growing challenge through risk-score assessments of the applications and their respective relevant application data (collectively referred to as assets), as well as the potential degradation of the underlying IoT device hardware. The aforementioned risk-score assessments employ clustering to identify, and a conformal framework to rank, high-risk (for failure) assets, which may subsequently be subjected to backup operations (overriding existing policies) to guarantee asset protection.

Method and system for risk score based asset data protection using a conformal framework

In general, embodiments of the invention relate to a method for enabling enhanced logging. The method includes obtaining a historical data for a target entity, determining an error probability of the target entity using the historical data, and enabling, based on the error probability, enhanced logging on the target entity.

Method and system for intelligent proactive error log activation

In general, embodiments of the invention relate to a method for enabling enhanced logging. The method includes obtaining historical data for a target entity, determining a steady state error probability of the target entity using the historical data, and enabling, based on the steady state error probability, a first level of enhanced logging on the target entity.

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Bengaluru, India

Mahantesh M Ambaljeri