Nutanix, Inc.

Ramesh U Chandra

Mohan Maturi

Artem Yevgenyevich Livshits

Rahul Singh

Ming Chen

Manjul Sahay

Karan Gupta

Ranjan Parthasarathy

Vinod Gupta

Kiran Tatiparthi

Abhijit S Khinvasara

Rahul Paul

Suresh Sivaprakasam

Ning Zhou

Vaishali Gupta

Shrivatsan Vasudhevan

Swagat Borah

Vyas Ram Selvam

Pritesh Lahoti

Ahmad Mohammad

Akanksha Deswal

An illustrative embodiment disclosed herein is an apparatus including a processor having programmed instructions to request, from each of a plurality of services spanning multiple clusters, a plurality of time instances. A plurality of snapshots were taken during the plurality of time instances. The processor has programmed instructions to present, to a user, the plurality of time instances and a plurality of identifiers. Each of the plurality of identifiers corresponds to one of the plurality of services. The processor has programmed instructions to receive, from the user, a first selection of a first time instance of the plurality of time instances and a second selection of a subset of the plurality of identifiers. Each of the subset of identifiers corresponds to one of a subset of the plurality of services. The processor has programmed instructions to apply, to a target, a subset of the plurality of snapshots.

System and method of time-based snapshot synchronization

In one embodiment, a computing device accesses an entity database storing information about entities in a virtualization environment. Each of the entities is associated with a single entity type and a shard. The shard further corresponds to the single entity type. The computing device determines an entity trail for the single shard, based on a modification history for one or more of the entities associated with the shard. The entity trail is divided into a plurality of time segments. The computing device receives an update from a client device indicating an update to an entity that is associated with the shard, and a client timestamp. The computing device selects a time segment corresponding to the client timestamp, and updates that portion of the entity trail with the client update.

Entity database historical data

A method includes receiving, by a host server on a public cloud including one or more physical data centers associated with one or more logical zones, a pairing request by a client device associated with a private cloud, allocating, by the host server, access to resources on the one or more physical data centers to the client device, and pairing, by the host server, the private cloud to the public cloud based on receiving an identity provider token from an identity provider.

Systems and methods for pairing on-premise clusters to clouds using identity service providers

Techniques for rebalancing computing workloads between a set of on-premises resources of an on-premises system and a set of cloud computing resources of a cloud computing system. A method embodiment commences upon detecting a rebalancing trigger event. Responsive to the trigger event, a set of resource data corresponding to observations pertaining to the on-premises resources and resource data corresponding to observations pertaining the cloud resources is accessed. Based at least in part on the resource data, a plurality of candidate workload rebalancing plans are generated. The candidate workload rebalancing plans are evaluated against the likelihood of achieving quantitative objectives resulting from the rebalancing. A portion of the scheduling commands to carry out the workload rebalancing plans are sent to the cloud computing system, and another portion of the scheduling commands are sent to the on-premises computing system. The receiving computing systems carry out the scheduling commands.

Workload rebalancing in heterogeneous resource environments

Systems for distributed resource management. A method for deploying two or more computing workloads across heterogeneous computing systems commences upon establishing network communications between an on-premises computing system and a cloud computing system. Resource data corresponding to the on-premises resources and the cloud resources are collected continuously and saved as a time series history of observations. Upon a user request or other event, workload placement planning commences. A set of workload placement plans are generated, which workload placement plans are then evaluated in accordance with one or more quantitative objectives. Scheduling commands to carry out the workload placement plans are generated. A first portion of the scheduling commands is executed at the cloud computing system, and another portion of the scheduling commands is executed at the on-premises computing system.

Workload scheduling across heterogeneous resource environments

In particular embodiments, a system for managing a virtualization environment includes host machines, each of the host machines including a hypervisor, user virtual machines (UVMs) and a virtual machine controller. The virtualization environment also includes virtual disks comprising a plurality of storage devices, and being accessible by the virtual machine controllers. The virtual machine controllers conduct I/O transactions with the virtual disks. The system stores an entity-relationship graph representing elements in the virtualization environment. Each of the elements is represented by an entity-type node in the entity-relationship graph, and relationships between the elements are represented by edges between the nodes.

Entity database framework

Growing community of inventors

Santa Clara, CA, United States of America

Ramesh U Chandra