Nutanix, Inc.

Deepak Narayan

Prakash Narayanasamy

Monil Devang Shah

Kiran Tatiparthi

Mukul Sharma

Praveen Kumar Padia

Dezhou Jiang

Sagi Sai Sruthi

Vivek Venkatesan

Abhishek Gupta

Brajesh Kumar Shrivastava

Vinayak Hindurao Khot

Pradeep Kashyap Ramaswamy

Ajaykumar Rajubhai Bhammar

Prachi Gupta

Siddhant Meshram

Bhoomi Sawant

Kamalneet Singh

Akshay Pandita

In accordance with some aspects of the present disclosure, a non-transitory computer readable medium is disclosed. In some embodiments, the non-transitory computer readable medium includes instructions that, when executed by a processor, cause the processor to receive, from a workload hosted on a host of a cluster, first I/O traffic programmed according to a first I/O traffic protocol supported by a cluster-wide storage fabric exposed to the workload as being hosted on the same host. In some embodiments, the workload is recovered by a hypervisor hosted on the same host. In some embodiments, the non-transitory computer readable medium includes the instructions that, when executed by the processor, cause the processor to adapt the first I/O traffic to generate second I/O traffic programmed according to a second I/O traffic protocol supported by a repository external to the storage fabric and forward the second I/O traffic to the repository.

Instant recovery as an enabler for uninhibited mobility between primary storage and secondary storage

A technique enables recovery of failover data used to generate one or more High Frequency Snapshots (HFSs) at a source and replicated to a target for storage and recovery. The target is illustratively an intermediary repository embodied as a long-term storage service (LTSS) configured to organize and store the HFSs as recovery points (RPs) in an object store. The LTSS stores a HFS identifier (ID), a logical offset in an object of the object store storing data of the HFS, and a logical timestamp associated with each replicated HFS as a key of a segment descriptor in a key-value database configured to store metadata describing the failover data of the HFS stored as one or more objects in the object store. Upon recovery of the failover data, the technique enables identification of the HFS stored in the object store and creation of a HFS index metadata structure (B+ tree) to extract the identified HFS as a RP.

Technique to store and rapidly hydrate high frequency snapshots on object storage

A technique utilizes grafting and differential based (diff-based) data seeding to hydrate a special virtual disk (vdisk) on a multi-node cluster with data changes (differences) between a reference vdisk stored on the cluster and a snapshot stored in an external repository to enable failover (including failback) recovery of an application workload in a disaster recovery environment. The application workload is stored as a workload vdisk on local storage of the cluster and snapshots of the workload vdisk are generated and organized as a vdisk chain on the cluster. One or more snapshots of the vdisk chain may be replicated to the external repository using a long-term snapshot service. Each replicated snapshot may be backed up from the cluster to the external repository at the granularity of a vdisk, referred to herein as an external datasource disk. The special vdisk is a thinly provisioned, datasource-backed vdisk that is grafted onto the vdisk chain, e.g., as a child vdisk of the reference vdisk. The differences between the reference vdisk and datasource disk are seeded from the datasource disk to hydrate the datasource-backed vdisk.

Virtual disk grafting and differential based data pulling from external repository

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Kerala, India

Deepak Narayan