公开(公告)号：US20200334059A1

公开(公告)日：2020-10-22

申请号：US16387490

申请日：2019-04-17

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Balaji Ramamoorthi ,  Siva Subramaniam Manickam ,  Vinnarasu Ganesan ,  Thavamaniraja Sakthivel

IPC: G06F9/455

Abstract: Examples described relate to identifying a least cost cloud network for deploying a virtual machine instance. In an example, virtual machine images available across a plurality of cloud networks may be identified. A catalog of the virtual machine images may be generated. The catalog may comprise, for each virtual machine image, a mapping information, comprising: a name of a virtual machine image, a name of a virtual machine instance based on the virtual machine image, a name of a cloud network providing the virtual machine image, a cost of deploying the virtual machine instance on the cloud network, a tag identifying a feature of the virtual machine image, and an identification tag assigned to the virtual machine image. For a given virtual machine instance, the catalog of the virtual machine images may be analyzed to identify a least cost cloud network.

公开(公告)号：US20200301724A1

公开(公告)日：2020-09-24

申请号：US16820521

申请日：2020-03-16

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Thavamaniraja Sakthivel ,  Siva Subramaniam Manickam ,  Vinnarasu Ganesan ,  Balaji Ramamoorthi

IPC: G06F9/455 ,  G06F9/50

Abstract: In some examples, a system associates, with a plurality of virtual resources deployed in a cloud environment, properties representative of characteristics of the virtual resources, the properties comprising a performance level of a virtual resource. The system receives a request to create a virtual resource in the cloud environment, and, in response to determining that properties of the virtual resource to be created for the request satisfy a criterion with respect to properties of a given virtual resource of the plurality of virtual resources, selects the given virtual resource as a candidate virtual resource for the request.

公开(公告)号：US10609144B2

公开(公告)日：2020-03-31

申请号：US15877908

申请日：2018-01-23

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Rajashekar Dasari ,  Thavamaniraja Sakthivel ,  Sudheer Yetukuri

IPC: H04L29/08 ,  H04L12/851 ,  H04L12/24

Abstract: Examples disclosed herein relate to creation of a storage area network (SAN) zone based on a service level agreement (SLA). In an example, provisioning of a server in a cloud may be determined. Further, a Service Level Agreement (SLA) for the provisioned server may be determined. The SLA may define desired states of SAN configuration parameters to be met in configuring a SAN zone for the provisioned server. Network components and storage components in the cloud that meet the desired states of SAN configuration parameters defined in the SLA may be identified. A SAN zone for the provisioned server may be created based on the identified network components and storage components.

公开(公告)号：US20170222908A1

公开(公告)日：2017-08-03

申请号：US15407461

申请日：2017-01-17

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Vijay Ram Sevagapandian ,  Vikram Krishnamurthy ,  Thavamaniraja Sakthivel

IPC: H04L12/26 ,  H04L12/751 ,  H04L29/08

CPC classification number: H04L43/0888 ,  H04L41/065 ,  H04L41/12 ,  H04L43/0817 ,  H04L43/0876 ,  H04L45/02 ,  H04L47/122 ,  H04L47/125 ,  H04L67/1038 ,  H04L67/1097

Abstract: In an example implementation, a network topology map with storage paths between servers and storage volumes of storage arrays in a storage network through network switches may be generated. A network switch may be identified from the network switches in the network topology map as a bottleneck by monitoring a performance parameter for each of the network switches. The performance parameter is indicative of I/O load at a port of a respective network switch. Storage volumes in the network topology map and connected to the bottlenecked network switch may be identified, and storage volume I/O metrics associated with each of the servers with respect to the identified storage volumes may be aggregated. Based on the aggregated storage volume I/O metrics, at least one of the servers may be determined as a candidate for a root-cause of the bottleneck.