Vmware, Inc.

Sivaraj M

Amit Kumar

Yash Bhatnagar

Karthik Seshadri

Rachil Chandran

Akhil Sadashiv Hingane

Siddartha Laxman Karibhimanvar

Mageshwaran Rajendran

Akash Srivastava

Gurusreekanth Chagalakondu

Swarnalatha Pasupuleti

Venkata Naga Manohar Kondamudi

Jeevan Prabhu

Dileep Varma Kalidindi

Sathyamurthy Dattathreya Hassan

Vishal I Gupta

Rajat Garg

Atul Jadhav

Naina Verma

Keerthanaa K

Nibunan G S

Methods, apparatus, systems and articles of manufacture to provide a custom installable open virtualization application file for on-premise installation via the cloud are disclosed. Example instructions cause one or more processors to determine a sizing factor based on a response from a user device; determine customized resource information for an agent in a private cloud network using an inventory count algorithm based on the sizing factor; modify an open virtualization appliance (OVA) file to include the customized resource information, the OVA file being deployed in a public cloud network; and transmit an indication to a location of the modified OVA file to the user device, the location of the modified OVA file being the same location as the OVA file.

Methods and apparatus to provide a custom installable open virtualization application file for on-premise installation via the cloud

Disclosed are various embodiments for distributed resource scheduling. An eviction request from a first host is received. The eviction request comprises data regarding a virtual machine to be migrated from the first host. The eviction request is then broadcast to a plurality of hosts. A plurality of responses are received from the plurality of hosts, each response comprising a score representing an ability of a respective one of the plurality of hosts to act as a new host for the virtual machine. A second host is selected from the plurality of hosts to act as the new host for the virtual machine based at least in part on the score in each of the plurality of responses. Then, a response is sent to the first host, the response containing an identifier of the second host.

Decentralized resource scheduling

An example method is provided for recommending VM configurations, including one or more servers upon which one or more VMs can run. A user wishing to run these VMs can request a recommendation for an appropriate server or set of servers. The user can indicate a category corresponding to the type of workload that pertains to the VMs. The system can receive the request and identify a pool of servers available to the user. Using industry specifications and benchmarks, the system can classify the available servers into multiple categories. Within those categories, similar servers can be clustered and then ranked based on their levels of optimization. The sorted results can be displayed to the user, who can select a particular server (or group of servers) and customize the deployment as needed. This process allows a user to identify and select an optimized setup quickly and accurately.

Systems and methods for recommending optimized virtual-machine configurations

A maintenance recommendation for containerized services can find a time to perform maintenance on a particular service based on resource usage patterns such that the maintenance will have a reduced impact on dependent services. The dependent services can be determined for the particular service based on network interactions between the services.

Maintenance recommendation for containerized services

Various examples are disclosed for generating metrics for quantifying computing resource usage. A computing environment can identify a computing function that utilizes a plurality of computing services hosted in at least one virtual machine. The computing environment can determine a first cost metric for the at least one virtual machine based on hardware resources used by the at least one virtual machine and determine a second cost metric for individual ones of the computing services based on virtual machine resources used by the individual ones of the computing services and the first cost metric. A third cost metric can be determined for the computing function as a function of the second cost metric and a utilization ratio.

Generating metrics for quantifying computing resource usage based on cost and utilization of virtualized services and optimizing performance through virtualized service migration

Methods, apparatus, systems and articles of manufacture to provide a custom installable open virtualization application file for on-premise installation via the cloud are disclosed. An example apparatus includes a resource processor to determine a resource capacity for an agent in a private cloud network; a file manipulator to modify an open virtualization appliance (OVA) file by modifying a descriptor file of the OVA file to configure the resource capacity for the agent in the private cloud network, the OVA file being deployed in a public cloud network; and a first interface to transmit an indication to a location of the modified OVA file to a user device, the location of the modified OVA file being the same location as the OVA file.

Various aspects are disclosed for optimization of dependent systems for serverless frameworks. In some examples, a load test executes instances of a function on a dependent system to generate datapoints. The datapoints are organized, using a clustering algorithm, into an acceptable group and at least one unacceptable group. A maximum number of concurrent instances of the function is determined based on a number of instances specified by at least one datapoint selected from the acceptable group. A live workload is performed on the dependent system. The live workload includes instances of the function that are assigned to the dependent system according to the maximum number of concurrent instances.

Dependent system optimization for serverless frameworks

Growing community of inventors

Bengaluru, India

Sivaraj M