Vce IP Holding Company LLC

Emc IP Holding Company LLC

Dell Products Inc.

Ryan Joseph Andersen

Donald Edward Norbeck, Jr

James A Ellers

Seamus Patrick Kerrigan

Nitin John

Patrick Barry

Jonathan Peter Streete

Joshua L Bonczkowski

Praphul Krottapalli

Kendrick A Coleman

Jeffery Jon Hayward

Thaddeus W Stoner

John James Mulqueeney, Jr

Jian Liu

Joshua C Atwell

A Hyper-Converged Infrastructure (HCI) ephemeral workload/data provisioning system includes a workload system coupled to a plurality of HCI systems by a manager system. The manager system identifies a first ephemeral workload that is provided by the workload system and that is configured to operate on one of the plurality of HCI systems for less than a first time period. In response to identifying the first ephemeral workload, the manager system determines first data that is to-be utilized by the first ephemeral workload and that is stored on a first HCI system that is included in the plurality of HCI systems. In response to determining that the first HCI system includes the first data that is to-be utilized by the first ephemeral workload, the manager system causes the first ephemeral workload to be provisioned on the first HCI system.

Hyper-converged infrastructure (HCI) ephemeral workload/data provisioning system

A layer-based method and system for defining and enforcing policies in an information technology (IT) environment. Specifically, the disclosed method and system propose and implement a layer-based infrastructure management model, which partitions the scope and problem set of application and operational policy definition and/or enforcement into a hierarchy of abstraction layers.

Layer-based method and system for defining and enforcing policies in an information technology environment

Methods, systems, and computer readable mediums for managing fault tolerance. A method includes receiving a request to establish a pool of data storage for an application of a distributed computing system. The distributed computing system includes hardware storage nodes integrated with compute nodes. The method includes receiving a target level of fault tolerance for the pool of data storage. The method includes establishing the pool of data storage by specifying, for each hardware storage node, a mirror hardware storage node for mirroring data stored on the hardware storage node so that the hardware storage node and the mirror hardware storage node do not share one or more pieces of physical equipment as specified in a physical layout of the hardware storage nodes to meet the target level of fault tolerance.

Methods, systems, and computer readable mediums for managing fault tolerance of hardware storage nodes

A system for determining when to order computing resources includes one or more processors to receive a request to determine when to order computing resources for a computing environment, receive at least one report for the computing environment, the report detailing past usage of at least one object included in the computing environment over a period of time, compute future usage of the at least one object included in the computing environment based on estimated growth of utilization of the at least one object included in the computing environment using data in the at least one usage report, determine at least one recommended reorder point for an upgrade to the at least one object and at least one recommended upgrade for the computing environment based on the past usage, the future usage, and a time to complete and deploy the at least one recommended upgrade to the computing environment.

System and method for managing computing resource orders

An apparatus in one embodiment comprises a processing platform configured to implement multi-layer infrastructure comprising compute, storage and network resources at a relatively low level of the multi-layer infrastructure, an application layer at a relatively high level of the multi-layer infrastructure, and one or more additional layers arranged between the relatively high level and the relatively low level. The processing platform is further configured to determine policies for respective different ones of the layers of the multi-layer infrastructure, the policy for a given one of the layers of the multi-layer infrastructure defining rules and requirements relating to that layer, to enforce the policies at the respective layers of the multi-layer infrastructure, and to monitor performance of an application executing in the multi-layer infrastructure. One or more configuration parameters of the multi-layer infrastructure are adjusted based at least in part on a result of the monitoring.

Processing platform with distributed policy definition, enforcement and monitoring across multi-layer infrastructure

Aspects of the present disclosure involve systems and methods for a tiered scheme of quality of service settings for ports of a network switch based at least on a performance metric of a storage pool of a software defined storage (SDS) appliance. In one particular embodiment, a network switch associated with one or more storage appliances may be configured to apply the networking tiered scheme to the ports of the network switch. The tiered scheme may be associated with a storage tier assigned or associated with a storage pool of the SDS system. Thus, a networking tier may be provided to one or more ports or networking components of the network if those ports or components are associated with the storage tier. The particular networking tier associated with a port or component may determine one or more quality of service settings applied to the port or component.

Software defined storage (SDS) system with network tiering

Aspects of the present disclosure involve system and methods for the automatic prediction and offering of cloud computing services to end users. The disclosed systems generate a predictive cloud service offering that is presented to end users via an interface, such as a graphical-user interface. The predictive cloud services may be consumed by the end-users to support various workloads.

Systems and methods of predictive display of cloud offerings based on real-time infrastructure data configurations

A system for comparing disparate computing resource offerings receives a request to compare at least one computing resource offering for a computing environment, the request including at least one infrastructure requirement and a computing environment design topology, the request associated with a unique order identifier, transmits the request to at least one computing resource provider via at least one provider application programming interface (API), the at least one computing resource provider comprising one of an external computing resource provider and an internal computing resource provider, receives a list of at least one computing resource offering from the at least one computing resource provider, normalizes the at least one computing resource offering based on the at least one infrastructure requirement and the computing environment design, and compares the at least one computing resource offering based on the at least one infrastructure requirement and the computing environment design topology.

System and method for comparing computing resource offerings

An apparatus in one embodiment comprises a processing platform configured to implement multi-layer infrastructure comprising compute, storage and network resources at a relatively low level of the multi-layer infrastructure and an application layer at a relatively high level of the multi-layer infrastructure. The processing platform is further configured to determine operational policies for respective different ones of the layers of the multi-layer infrastructure other than the application layer, the operational policies defining operational rules and requirements relating to the corresponding layers, to determine an application policy for the application layer, the application policy defining application workload rules and requirements for an application to be executed in the multi-layer infrastructure, and to manage the multi-layer infrastructure in accordance with the operational policies and the application policy. The operational policies are defined independently of the application policy but mutually enforced with the application policy in conjunction with execution of the application in the multi-layer infrastructure.

Processing platform with independent definition and mutual enforcement of operational and application policies

Methods, systems, and computer readable mediums for optimizing a system configuration are disclosed. In some examples, a method includes determining whether a system configuration for executing a workload using a distributed computer system is optimizable and in response to determining that the system configuration is optimizable, modifying the system configuration such that at least one storage resource for storing workload data is located at a server node that is executing the workload in the distributed computer system.

Methods, systems, and computer readable mediums for system configuration optimization

A predictive order status system includes one or more processors to receive a request for a current order status of an order for a computing environment, the order having at least one task representing a segment of an order process for completing the order and the request associated with a unique order identifier, determine the current order status for the order for the computing environment, the current order status comprising a simulated percentage value that is based on an amount of elapsed time since the order was placed divided by a total order process time to complete the order, determine an exception status for the order for the computing environment, the exception status being one of on track to be completed within the total order process time to complete the order, possibly at risk for being completed within the total order process time to complete the order, and at risk for being completed within the total order process time, and send a graphical user interface representation of the current order status and the exception status.

Growing community of inventors

Belmont, MA, United States of America

Ryan Joseph Andersen