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公开(公告)号：US11956298B2
公开(公告)日：2024-04-09
申请号：US18047623
申请日：2022-10-18
Applicant: Nutanix, Inc.
Inventor： Akhilesh Joshi , Gaurav Poothia , Heiko Friedrich Koehler , Naorem Khogendro Singh , Pranav Desai
Abstract: A platform-as-a-service infrastructure and application lifecycle manager is configured to implement a common services model to deploy selected services from a common set of services to service domains hosted on multiple different cloud platforms by abstracting dependence on availability of various additional supporting services, such as services that are platform-specific. The platform-as-a-service infrastructure and application lifecycle manager may also manage a lifecycle of available services, such as managing upgrades and/or patches to services.
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公开(公告)号：US10691481B2
公开(公告)日：2020-06-23
申请号：US15923165
申请日：2018-03-16
Applicant: Nutanix, Inc.
Inventor： Miao Cui , Malcolm Crossley , Gaurav Poothia
IPC: G06F9/455 , G06F9/50 , G06F12/1009
Abstract: A system and method include determining underprovisioning of a guest physical memory of a virtual machine running on a computing node. The node includes hardware resources that are mapped the guest physical memory by a hypervisor. The hypervisor receives page fault information from the virtual machine based on page faults in the virtual machine. The hypervisor generates a table that includes virtual memory address-process indicator pair entries and corresponding page fault numbers. The hypervisor removes those entries that have a corresponding page fault number that is less than a first threshold value. The hypervisor determines a size of a revolving memory based on the number of remaining entries and a page size of the guest physical memory. If the revolving memory size is less than a second threshold value in relation to the allocated size of the guest physical memory, the hypervisor indicates underprovisioning of the guest physical memory.
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3.发明申请公开(公告)号：US20200174815A1
公开(公告)日：2020-06-04
申请号：US16207046
申请日：2018-11-30
Applicant: Nutanix, Inc.
Inventor： Aditya Ramesh , Fabien Hermenier , Gaurav Poothia , Hemanth Kumar Mantri , Robert Schwenz , Swathi Koundinya
IPC: G06F9/455
Abstract: A system and method include migrating virtual machines (VMs) between compute only (CO) and hyper converged (HC) nodes. The method includes identifying, by a management processor of a virtual computing system, a plurality of virtual machines hosted on compute only (CO) nodes in the virtual computing system. The management processor then identifies hyper converged (HC) nodes having virtual disks hosting data for the plurality of virtual machines hosted on CO nodes. When a virtual machine (VM) in the plurality of virtual machines is migrating, the management processor biases the VM to migrate to a first HC node hosting a virtual disk assigned to host data for the VM.
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公开(公告)号：US20200042338A1
公开(公告)日：2020-02-06
申请号：US16051242
申请日：2018-07-31
Applicant: Nutanix, Inc.
Inventor： Gaurav Poothia , Arun Navasivasakthivelsamy , Abhinay Nagpal , Miao Cui , Srinivas Bandi Ramesh Babu , Weiheng Chen
Abstract: A system and method for dynamically adjusting the amount of memory allocated to a virtual machine includes generating, by a memory resizing system, a current memory usage profile for the virtual machine. The memory resizing system and the virtual machine are part of a virtual computing system and the current memory usage profile is generated by mapping, as a function of time, memory usage information from the virtual machine. The system and method also include computing an upper baseline based upon a peak memory usage in the current memory profile, updating an initial memory allocation of the virtual machine based upon the upper baseline and a predetermined threshold for obtaining an initial revised memory allocation, determining a moving average of memory usage from a historical memory usage profile, and updating the initial revised memory allocation based upon the moving average of memory usage for obtaining a final revised memory allocation.
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公开(公告)号：US12021915B2
公开(公告)日：2024-06-25
申请号：US18047623
申请日：2022-10-18
Applicant: Nutanix, Inc.
Inventor： Akhilesh Joshi , Gaurav Poothia , Heiko Friedrich Koehler , Naorem Khogendro Singh , Pranav Desai
Abstract: A platform-as-a-service infrastructure and application lifecycle manager is configured to implement a common services model to deploy selected services from a common set of services to service domains hosted on multiple different cloud platforms by abstracting dependence on availability of various additional supporting services, such as services that are platform-specific. The platform-as-a-service infrastructure and application lifecycle manager may also manage a lifecycle of available services, such as managing upgrades and/or patches to services.
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Patent Agency Ranking
公开(公告)号：US10929165B2
公开(公告)日：2021-02-23
申请号：US16051242
申请日：2018-07-31
Applicant: Nutanix, Inc.
Inventor： Gaurav Poothia , Arun Navasivasakthivelsamy , Abhinay Nagpal , Miao Cui , Srinivas Bandi Ramesh Babu , Weiheng Chen , Himanshu Shukla
Abstract: A system and method for dynamically adjusting the amount of memory allocated to a virtual machine includes generating, by a memory resizing system, a current memory usage profile for the virtual machine. The memory resizing system and the virtual machine are part of a virtual computing system and the current memory usage profile is generated by mapping, as a function of time, memory usage information from the virtual machine. The system and method also include computing an upper baseline based upon a peak memory usage in the current memory profile, updating an initial memory allocation of the virtual machine based upon the upper baseline and a predetermined threshold for obtaining an initial revised memory allocation, determining a moving average of memory usage from a historical memory usage profile, and updating the initial revised memory allocation based upon the moving average of memory usage for obtaining a final revised memory allocation.
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公开(公告)号：US10782992B2
公开(公告)日：2020-09-22
申请号：US15340871
申请日：2016-11-01
Applicant: Nutanix, Inc.
Inventor： Miao Cui , Aroosh Sohi , Srinivas Bandi Ramesh Babu , Jaspal Singh Dhillon , Gaurav Poothia , Pulkit Yadav , Supreeth Srinivasan
IPC: G06F9/455
Abstract: In one embodiment, a system for managing communication connections in a virtualization environment includes (1) a first host machine implementing a virtualization environment based on a first platform, wherein the first host machine includes a first hypervisor, at least one virtual machine, and one or more virtual infrastructure elements and (2) a virtual disk including a plurality of storage devices. A management module for the system may perform steps to convert the first host machine to a second platform by installing (on the first host machine) a second hypervisor associated with the second platform, disabling the first hypervisor, capturing a configuration describing elements of a virtual infrastructure associated with the first hypervisor, registering the captured configuration with the second hypervisor, creating elements of the captured configuration in the context of the second platform and in association with the second hypervisor, and then enabling the second hypervisor.
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公开(公告)号：US20200249973A1
公开(公告)日：2020-08-06
申请号：US16267262
申请日：2019-02-04
Applicant: Nutanix, Inc.
Inventor： Aditya Ramesh , Ashwin Thennaram Vakkayil , Gaurav Poothia , Gokul Kannan , Hemanth Kumar Mantri , Kamalneet Singh , Robert Schwenz
Abstract: A system and method include classifying and assigning virtual disks accessed from compute only nodes. The method determines, by a management processor of a virtual computing system, characteristics for a plurality of virtual disks hosted on a plurality of hyper converged nodes in a cluster of nodes in the virtual computing system. The method further classifies, by the management processor, each of the plurality of virtual disks based on the determined characteristics and identifies, by the management processor, one of the plurality of virtual disks to host data for a virtual machine on a compute only node based on the classification to spread out input-output demand in the cluster, reducing probability of input-output bottlenecks and increasing cluster-wide storage throughput. The method also assigns, by the management processor, the identified virtual disk to host data for the virtual machine located on the compute only node.
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公开(公告)号：US20220121543A1
公开(公告)日：2022-04-21
申请号：US17139325
申请日：2020-12-31
Applicant: Nutanix, Inc.
Inventor： Gaurav Poothia , Heiko Koehler , Pankit Thapar
Abstract: A containerized clustered computing system may be used to provide a platform as a service (PaaS) environment. The clustered system may be configured by initiating a bootstrap node including a first cluster infrastructure orchestrator and first container orchestrator and migrating cluster metadata to a key value store of the first container orchestrator. A second node in the cluster may be initiated by configuring a second cluster infrastructure orchestrator of the second node with a dependency on the first container orchestrator of the bootstrap node.
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公开(公告)号：US20220083389A1
公开(公告)日：2022-03-17
申请号：US17350636
申请日：2021-06-17
Applicant: Nutanix, Inc.
Inventor： Gaurav Poothia , Sandeep Reddy Goli , Deepak Muley , Pranav Desai
Abstract: Systems and methods described herein generally relate to compute node resource scheduling. AI inference services described herein may receive a request to execute a machine learning model in a clustered edge system. To determine which hardware resource comprising computing nodes of the clustered edge system on which to execute the machine learning model, AI inference services may compare the computational workload of the machine learning model, with the computational abilities and functions of the hardware resources. In examples, the comparison is based on a scheduling algorithm, including an identification stage to identify candidate hardware resources capable of executing the machine learning model, and a scoring stage to select the best candidate hardware resource for executing the machine learning model. A scheduler may assign the machine learning model to the selected hardware resource for execution by the AI inference services.
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