Rubrik, Inc.

Tintri by Ddn, Inc.

Karthikeyan Attaiyempatty Srinivasan

Looi Chow Lee

Andrew Park

Shobhit Dayal

Zhicong Wang

Amit Gud

Andrew Kwangyum Park, Jr

In some embodiments, a process for restoring a version of a virtual machine using a data storage system comprises identifying a particular version of a virtual machine to be restored, determining a base image from which the particular version may be derived, determining a set of incremental files for generating the particular version, generating a file associated with the particular version using the base image and the set of incremental files, and outputting at least a portion of the file.

Scaling single file snapshot performance across clustered system

Some embodiments may include a process for determining a type of snapshot to be stored using a data storage system. An example the process comprises identifying a snapshot chain for a first virtual machine, determining whether the snapshot chain includes a dependent base file, determining a maximum incremental chain length for the snapshot chain based on whether the snapshot chain includes a dependent base file, or based on an age of the backed up versions within the snapshot chain, determining whether a new snapshot chain should be created based on the maximum incremental chain length, and determining a type of snapshot to be stored for the first virtual machine based on the maximum incremental chain length.

A data management and storage (DMS) cluster of peer DMS nodes manages data of a compute infrastructure by generating snapshots of partitions of a fileset of the compute infrastructure and providing a passthrough for storing the snapshots in a data storage separate from the DMS cluster, such as a cloud computing system. In one approach, the DMS nodes determine partitions of a fileset using fileset metadata, generates snapshots of the partitions, and stores the snapshots in the data storage. Each DMS node may include a local storage which is used to facilitate creation of a snapshot of a partition. The snapshot may be removed from the local storage after being sent to the data storage. Rather than storing the snapshot, the DMS cluster stores fileset metadata that is referenced to retrieve the snapshot from the data storage. The snapshot is deployed to retrieve a file stored in the partition.

Fileset passthrough using data management and storage node

In some embodiments, there is provided a method for operating a data management system. The method comprising certain operations including determining a schedule for backing up a first virtual machine, configuring a job scheduler to implement the schedule for backing up the first virtual machine, initiating a snapshot process for acquiring a snapshot of the first virtual machine, determining a type of snapshot to be stored, and determining whether a full image of the first virtual machine is required to be stored in order to store the snapshot of the first virtual machine.

Methods and systems for backing up and restoring different point in time versions of a virtual machine, a real machine, an application, a database, or a set of electronic files using a plurality of independently managed snapshot chains are described. The different point in time versions of the data being backed-up may be stored using two or more snapshot chains corresponding with two or more data partitions of the data being backed-up. Over time, additional full image snapshots may be acquired from an external server or generated locally by a storage appliance to limit the snapshot chain lengths and to limit the aggregate block chain lengths for the snapshot chains. Acquisition and generation of the additional full image snapshots may be staggered across different data partitions to limit computational and storage costs per snapshot.

Preemptively breaking incremental snapshot chains

Staggered full partitioned snapshots

Dynamic block optimization for space and performance is disclosed, including: determining that a data pattern associated with a data block included in a write request matches a promoted data pattern; and performing the write request by associating the data block with a previously stored copy of the data block without updating an associated reference count. Dynamic block optimization for space and performance further includes determining that a data pattern associated with a data block included in a write request matches a predetermined data pattern; and performing the write request by storing a static representation associated with the data block and not storing the data block, wherein the static representation is usable to generate the data block.

Growing community of inventors

Fremont, CA, United States of America

Karthikeyan Attaiyempatty Srinivasan