Rubrik, Inc.

Mudit Malpani

Hardik Vohra

Benjamin Travis Meadowcroft

Abhay Mitra

Prateek Pandey

Li Ding

Arijit Banerjee

Kushaagra Goyal

Shaomin Chen

Kunal Sean Munshani

Samir Rishi Chaudhry

Arnav Gautum Mishra

Biswaroop Palit

Suman Swaroop

Zhicong Wang

Fabiano C Botelho

Janmejay Singh

Soham Mazumdar

Saurabh Goyal

Atanu Chakraborty

Sanjari Srivastava

Swapnil Agarwal

Rahil Shah

Ajay Arvind Bhave

Rohit Agrawal

Abdul Jabbar Abdul Rasheed

Abdullah Al Reza

Prasenjit Sarkar

Adam Gee

Noel Moldvai

Jonathan Carlyle Derryberry

Muraliraja Muniraju

Disheng Su

Shaswat Chaubey

Michael Wronski

Arvind Batra

Shivam Rajpal

Sriharshitha Velivelli

Arnav Rupde

Chak Fai Yuen

Vasu Murthy

Inderpal Arora

Daniel Mark Rogers

Nandish Kotadia

Akhil Singh

Anmol Arora

Satwant Rana

Abhishek Modi

Koki Yoshida

A data management and storage (DMS) cluster of peer DMS nodes manages migration of an application between a primary compute infrastructure and a secondary compute infrastructure. The secondary compute infrastructure may be a failover environment for the primary compute infrastructure. Primary snapshots of virtual machines of the application in the primary compute infrastructure are generated, and provided to the secondary compute infrastructure. During a failover, the primary snapshots are deployed in the secondary compute infrastructure as virtual machines. Secondary snapshots of the virtual machines are generated, where the secondary snapshots are incremental snapshots of the primary snapshots. In failback, the secondary snapshots are provided to the primary compute infrastructure, where they are combined with the primary snapshots into construct a current state of the application, and the application is deployed in the current state by deploying virtual machines on the primary compute infrastructure.

Application migration between environments

Methods, systems, and devices for data management are described. A data management system (DMS) may obtain a snapshot of a file system that includes multiple files and permission sets associated with the files. A permission set may indicate one or more access approvals for associated principals. The DMS may scan the files to identify unique pairs each including a unique combination of a respective permission set and a respective sensitive information type. The DMS may store a first mapping that maps the unique pairs to respective values that indicate an amount of sensitive information, of the respective sensitive information type, that is included in one or more files associated with the unique pair. The DMS may identify a respective set of sensitive data types included in files to which a principal has access based on the first mapping and an evaluation of the permission sets.

Aggregation of policy information for principals associated with a file system

Example embodiments relate generally to systems and methods for continuous data protection (CDP) and more specifically to an input and output (I/O) filtering framework and log management system to seek a near-zero recovery point objective (RPO).

Systems and methods for continuous data protection comprising storage of completed I/O requests intercepted from an I/O stream using touch points

In some examples, a cluster comprises peer nodes and a distributed data store implemented across the peer nodes, a method of remote linking of data objects for data transfer between a first node cluster and a second node cluster among the peer nodes, the method comprising: creating a data object group including multiple remote data objects, wherein a plurality of remote data objects in the data object group represent a same first virtual machine and are registrable on at least the first and second node clusters of the peer DMS nodes; creating or identifying remote links to a plurality of the remote data objects in the data object group; designating a member of the data object group as an active member of the group; and assigning a task to the active member to be completed using remote links.

Remote snappable linking

A data management system may support a configuration backup of a first backup system that manages backup procedures for data of a host environment that is separate from the first backup system. The data management system may transmit, to the first backup system, a request to generate the configuration backup that includes information for the one or more backup procedures managed by the first backup system. The data management system may cause the configuration backup to be stored in a separate storage location. In response to first backup system failure, the data management system may transmit, to a second backup system, a request to apply one or more configurations for the first backup system to the second backup system based on the stored configuration backup for the first backup system.

Configuration recovery for a data management system

A data management and storage (DMS) cluster of peer DMS nodes manages data of a tenant of a multi-tenant compute infrastructure. The compute infrastructure includes an envoy connecting the DMS cluster to virtual machines of the tenant executing on the compute infrastructure. The envoy provides the DMS cluster with access to the virtual tenant network and the virtual machines of the tenant connected via the virtual tenant network for DMS services such as data fetch jobs to generate snapshots of the virtual machines. The envoy sends the snapshot from the virtual machine to a peer DMS node via the connection for storage within the DMS cluster. The envoy provides the DMS cluster with secure access to authorized tenants of the compute infrastructure while maintaining data isolation of tenants within the compute infrastructure.

Envoy for multi-tenant compute infrastructure

A data management system (DMS) may support intelligent snapshot protection techniques. For example, the DMS may backup a computing system and facilitate that capture and storage of snapshots of the computing system. The DMS may identify a deletion event associated with one or more of the snapshots, the deletion event being associated with the one or more snapshots being deleted at a first time. The DMS may determine that deletion event is anomalous and retain the one or more snapshots beyond the first time. For example, the DMS may determine that one or more parameters associated with the deletion event are indicative of the deletion event being anomalous. In response, the DMS may retain the one or more snapshots for a retention period beyond the first time.

Intelligent protection of computing snapshots

In some examples, a duster comprises peer nodes and a distributed data store implemented across the peer nodes, a method of remote linking of data objects for data transfer between a first node cluster and a second node cluster among the peer nodes; the method comprising: creating a data object group including multiple remote data objects, wherein a plurality of remote data objects in the data object group represent a same first virtual machine and are registrable on at least the first and second node clusters of the peer DMS nodes; creating or identifying remote links to a plurality of the remote data objects in the data object group; designating a member of the data object group as an active member of the group; and assigning a task to the active member to be completed using remote links.

A data management and storage (DMS) cluster of peer DMS nodes manages data of an application distributed across a set of machines of a compute infrastructure. A DMS node associates a set of machines with the application, and generates data fetch jobs for the set of machines for execution by multiple peer DMS nodes. The DMS node determining whether each of the data fetch jobs for the set of machines is ready for execution by the peer DMS nodes. In response to determining that each of the data fetch jobs is ready for execution, the peer DMS nodes execute the data fetch jobs to generate snapshots of the set of machines. The snapshots may be full or incremental snapshots, and collectively form a snapshot of the application.

Application backup and management

Systems and methods for continuous data protection

Systems and method for continuous data protection and recovery by implementing a set of algorithms based on the length of I/O data streams

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Mountain View, CA, United States of America

Mudit Malpani