Netapp, Inc.

Network Appliance, Inc.

Jose Mathew

Ling Zheng

Tijin George

Atul Ramesh Pandit

Dnyaneshwar Nagorao Pawar

Roopesh Chuggani

Sriram Venketaraman

Jagavar Nehra

Ravindra Kuramkote

Abhishek Naidu

Anil Kumar Ponnapur

Krishna Murthy Chandraiah Setty Narasingarayanapeta

Rakesh Bhargava M R

Subramaniam Periyagaram

Andrew G Tucker

Rithin Kumar Shetty

Eric P Forgette

Mohit Gupta

Varun Jobanputra

Ravi Krishna Budhia

Sisir Shekhar

Vikas Yadav

James R Grier

Rajesh Desai

Kiran Kumar Modukuri

Vishwajith Shivappa

Rakesh Bhargava Mr

Chaitanya Nulkar

Sandeep Mukherjee

Harsha Vardhan Reddy Perannagari

Anudhar Emani

Aditya Toomula

Divya Yogesh

Jeffrey A Kemp

Techniques are provided for an object file system for an object store. Data, maintained by a computing device, is stored into slots of an object. The data within the slots of the object is represented as a data structure comprising a plurality of nodes comprising cloud block numbers used to identify the object and particular slots of the object. A mapping metafile is maintained to map block numbers used to store the data by the computing device to cloud block numbers of nodes representing portion of the data stored within slots of the object. The object is stored into the object store, and the mapping metafile and the data structure are used to provide access through the object file system to portions of data within the object.

Snapshot storage and management within an object store

Techniques are provided for backing up virtual machines from a computing environment to a storage environment. A virtual machine agent is utilized to generate a snapshot of the virtual machine. Metadata comprising a snapshot identifier of the snapshot and virtual disk information of virtual disks captured by snapshot is generated at the computing environment. The metadata is retrieved and used to create a metafile that is transferred to the storage environment within which snapshots of the virtual machine are to be stored. The snapshot is retrieved from the computing environment and is packaged into a snapshot package having a protocol format used by the storage environment. The snapshot package is transferred to the storage environment.

Virtual machine backup from computing environment to storage environment

Techniques are provided for orchestrating operations between a storage environment and a computing environment hosting virtual machines. A virtual machine proxy, associated with a computing environment hosting a virtual machine, is accessed by an orchestrator to identify the virtual machine and properties of the virtual machine. A storage proxy, associated with a storage environment comprising a volume within which snapshots of the virtual machine are to be stored, is accessed by the orchestrator to initialize a backup procedure. The orchestrator utilizes the virtual machine proxy to create a snapshot of the virtual machine. The orchestrator utilizes the storage proxy to back up the snapshot to the volume using the backup procedure.

Orchestrator for orchestrating operations between a computing environment hosting virtual machines and a storage environment

Techniques are provided for incrementally restoring a virtual machine hosted by a computing environment. In response to receiving an indication that the virtual machine is to be incrementally restored, a snapshot of the virtual machine may be created while the virtual machine is shut down into an off state. The snapshot is transmitted to a storage environment as a common snapshot. The snapshot and the common snapshot are common snapshots comprising a same representation of the virtual machine. The common snapshot and a prior snapshot of the virtual machine are evaluated to identify a data difference of the virtual machine between the common snapshot and the prior snapshot. An incremental restore is performed of the virtual machine by transmitting the data difference from the storage environment to the computing environment to restore the virtual machine to a state represented by the prior snapshot.

Incremental restore of a virtual machine

Methods, non-transitory computer readable media, and computing devices that receive data from a primary storage node. The data is stored in a primary volume within a primary composite aggregate hosted by the primary storage node. A determination is made when the data is tagged to indicate that the data is stored in the primary volume on a remote data storage device of the primary composite aggregate. The data is stored on another remote data storage device without storing the data in a local data storage device, when the determining indicates that the data is tagged to indicate that the data is stored in the primary volume on a remote data storage device of the primary composite aggregate. Accordingly, this technology allows data placement to remain consistent across primary and secondary volumes and facilitates efficient operation of secondary storage nodes by eliminating two-phase writes for data stored on cloud storage devices.

Methods for improved data replication across hybrid cloud volumes using data tagging and devices thereof

Object store file system format for representing, storing, and retrieving data in an object store according to a structured format

One or more techniques and/or systems are provided for profiling a dataset. For example, a snapshot of a volume may be evaluated to identify a set of data characteristics, such as file and directory size information. A baseline dataset profile of a dataset of data within the volume may be constructed based upon the set of data characteristics. Histograms and graphs of directory counts and file counts may be constructed based upon the baseline dataset profile. An incremental dataset profile may be constructed for the dataset based upon an evaluation of the snapshot and a subsequent snapshot of the volume. Histograms and graphs of directories and files that are modified, created, and/or deleted may be constructed based upon the incremental dataset profile. Performance predictions, analytics, field diagnostics of performance issues, and/or scheduling of service execution may be implemented for a storage network hosting the volume based upon dataset profiles.

Data profiler

One or more techniques and/or systems are provided for data recovery objective modeling. For example, a data recovery objective model may be defined for a storage network environment. The data recovery objective model may be defined based upon a client data ingest rate corresponding to a data change rate by one or more clients of data stored by a first storage controller. The data recovery objective model may be defined based upon an effective throughput of a data transfer utility for replicating modified data from first storage of the first storage controller to second storage of a second storage controller. Statistical utilization data may be collected from the storage network environment, and may be evaluated using the data recovery objective model to determine a data recovery objective metric. If the data recovery objective metric does not satisfy a client specified objective, then a computing resource recommendation may be provided.

Data recovery objective modeling

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Santa Clara, CA, United States of America

Jose Mathew