Rubrik, Inc.

Jiangbin Luo

Arvind Jain

Christopher L Wong

Pin Zhou

Soham Mazumdar

Bipul Sinha

Arvind Nithrakashyap

Adam Gee

Guilherme Vale Ferreira Menezes

Rajesh Kumar Jaiswal

Joshua Duncan Hight

Fan Du

Biswaroop Palit

Jonathan Carlyle Derryberry

Kenny To

Manjunath Chinni

Sharvanath Pathak

Rajath Subramanyam

Aravind Menon

Nohhyun Park

Gaurav Khandelwal

Christopher Wong

Jayanth Madheswaran

Abhishek Dharmaprikar

Lei Shi

Pradeep Bansal

Keon Jang

Veera Venkata Naga Rama Satyam Kandula

Methods, systems, and devices for data management are described. A data management system (DMS) may provide backup and recovery services to one or more non-addressable hosts within a network. The DMS may receive a packet from a host within the network. A source internet protocol (IP) address of the packet, when received at the DMS, may be an IP address associated with the network. The packet may also include an identifier associated with the host. The DMS may include one or more storage entities used to back up the one or more hosts. To route the packet to a storage entity used to back up the host, the DMS may set the source IP address of the received packet to be a virtual IP address associated with the host based on the identifier and use the virtual IP address to route the packet to the storage entity.

Traffic routing in backup and recovery of non-addressable hosts

An application server host may receive, via a port forwarding tunnel, a connection request that includes an indication of a client internet protocol (IP) address for a client host. The application server host may identify based at least in part on the client IP address and using a mapping maintained for a plurality of client hosts, a virtual IP address that is associated with the client IP address and a client network identifier associated with the port forwarding tunnel from which the connection request is received. The application server host may open a connection between an application server hosted by the application server host and the client host using the identified virtual IP address.

Internet protocol based security over port forwarding tunnels

A data management system (DMS) may support authentication of a host using a non-addressable domain controller within a network. The DMS may obtain a list of domain controllers within the network and create an account at a domain controller on the list via a virtual machine instantiated within the network and used to create a tunnel between the DMS and the virtual machine The DMS may receive, via a port, a packet from a host within the network and route the packet, using a demultiplexer configured to monitor the port, to a storage entity. The storage entity may transmit, via the port to the domain controller, a request to authenticate the host, the request bypassing the demultiplexer that is configured not to monitor the port when the storage entity operates in a client mode. The DMS may receive an indication of whether the host is authenticated from the domain controller.

Host authentication using a non-addressable domain controller

Methods, systems, and devices for data management are described. A first data source may be identified to move from a source cloud deployment (that operates in accordance with a first release cadence for updating database schema) to a destination cloud deployment (that operates in accordance with second, different release cadence for updating database schema). The first source database is then migrated from the source cloud deployment to an intermediate cloud deployment hosted on the source cloud deployments that allows the schema of the first data source to remain unchanged for a duration of time that the first data source is hosted on the intermediate cloud deployment. The database schema associated with the first data source is then updated to an updated (most recent) database schema in accordance with the second release cadence of the destination cloud deployment, and migrated from the intermediate cloud deployment to the destination cloud deployment.

Techniques for handling schema mismatch when migrating databases

Methods and systems for recovering databases and other applications with reduced downtime using recoverable chains are described. When protecting or backing up a database, an integrated data management and storage system may capture snapshots of the database at a snapshot frequency (e.g., at 15 minute intervals) and acquire database transaction logs that include data changes of the database at a frequency that is greater than the snapshot frequency. The integrated data management and storage system may generate a particular point in time version of the database by identifying a recoverable chain that comprises a combination of one or more database snapshots including the snapshot closest to the recovery point and one or more database transaction logs.

Database snapshot and backup management with recoverable chains

In some examples, a cluster protection system comprises at least one processor and a memory storing instructions which, when executed by the at least one processor, cause the system to perform operations comprising identifying a target cluster or an object in a container management framework, identifying application data and metadata associated with the target cluster or the object, generating a first snapshot of the target cluster or the object, the first snapshot including at least the metadata, storing the first snapshot in offsite cloud storage, generating a second snapshot of the target cluster, the second snapshot including at least the application data, and storing the second snapshot in a persistent volume in onsite storage.

Data backup in container management frameworks

An example method of restoring a database includes obtaining information about backup data of a database from a source storage separate from a compute infrastructure. The information includes a list of data blocks of a file, transferring the data blocks on the list from the source storage to a local storage on the compute infrastructure, and tracking which data blocks of the file have been transferred from the source storage to the local storage concurrently when transferring the data blocks.

Instant recovery of databases

Methods and systems for automatically upgrading or synchronizing a remote data management agent running on a remote host machine (e.g., a hardware server) to a particular version that is in-sync with a corresponding version used by a cluster of data storage nodes controlling the remote data management agent are described. The remote agent may be initially installed on the remote host and subsequent updates to the remote agent may be performed using the remote agent itself without requiring intervention by the remote host. The remote agent may comprise a backup agent and a bootstrap agent that are each exposed in different network ports or associated with different port numbers or networking addresses. The backup agent may perform data backup related tasks for backing up files stored on the remote host and the bootstrap agent may perform upgrade related tasks for upgrading the backup agent.

Auto-upgrade of remote data management connectors

In one approach, a set of data blocks or files is tracked for changes between snapshots. This may be done by a file system filter running in kernel mode. The data blocks or files that are tagged as unchanged are not transferred to backup because there is no need to update since the last backup. Other data blocks and files may be first tested for change, for example by comparing digital fingerprints of the current data versus the previously backed up data, before transferring to backup.

Change block tracking for transfer of data for backups

Methods and systems for efficiently capturing snapshots of a computing application or environment over time and transferring the snapshots to an integrated data management and storage system are described. A snapshot agent may detect that one or more electronic files associated with the computing application or environment are greater than a threshold file size and in response perform an incremental backup optimization in which the snapshot agent may identify files that have been touched since a previous snapshot by accessing file system metadata (e.g., last modified timestamps) or utilizing a tracking agent to detect potential file changes that have occurred since the previous snapshot was captured. The snapshot agent may then generate fingerprints for data blocks of the touched files, which may reduce the total number of fingerprints needing to be generated to identify the changed data blocks corresponding with a current snapshot to be transferred.

Forever incremental backups for database and file servers

Methods and systems for managing, storing, and serving data within a virtualized environment are described. In some embodiments, a data management system may manage the extraction and storage of virtual machine snapshots, provide near instantaneous restoration of a virtual machine or one or more files located on the virtual machine, and enable secondary workloads to directly use the data management system as a primary storage target to read or modify past versions of data. The data management system may allow a virtual machine snapshot of a virtual machine stored within the system to be directly mounted to enable substantially instantaneous virtual machine recovery of the virtual machine.

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Cupertino, CA, United States of America

Jiangbin Luo