Emc IP Holding Company LLC

Virtual Power Systems, Inc.

Cato

Other

Nikhil Sharma

Stephen J Todd

Said Tabet

Shankar Ramamurthy

Karimulla Raja Shaikh

Ravi S Subramaniam

Martin P Leslie

Akshay Krishnamoorthy

Dhanaraja Kasinathan

Craig Broadbent

Marina Zeldin

In disclosed techniques, simulations are performed to determine data center performance under certain conditions. The simulations are dynamic and allow for changes in power demand due to temporal data center activities. In order to accommodate predicted and unpredicted fluctuations in power demand of a data center, one or more power caches are configured to supply additional power during periods of peak demand. Power caches provide supplemental power during periods of peak demand. The simulations are used for a variety of purposes, including determining the effects of power caches going offline under various conditions. Disclosed techniques can simulate the cycling of a power cache and can determine if additional configuration changes to the data center are warranted to maintain optimal health of the power caches. Thus, power scenario simulation of a data center can provide information vital to efficient operation of the data center.

Data center power scenario simulation

In disclosed techniques, datacenter power management uses AC and DC power sources. An AC power distribution topology within a datacenter provides one or more AC power sources to computing devices. A DC power distribution topology within the datacenter provides one or more DC power sources to computing devices. An uninterruptible power supply (UPS) is provisioned to a rack of computing devices, wherein the UPS is capable of receiving the one or more AC power sources using the AC power distribution topology and the one or more DC power sources using the DC power distribution topology. The one or more DC power sources are evaluated for energizing the DC power distribution topology. The one or more DC power sources are connected to the UPS which is provisioned to the rack of computing devices, based on the evaluating and a datacenter power requirement.

Datacenter power management using AC and DC power sources

Embodiments provide techniques for datacenter power management using variable power sources. Power from the variable power sources is stored in a power cache. An optimization engine receives input criteria such as power availability from non-variable and variable power sources, as well as one or more power management goals. The optimization engine implements a dispatch strategy that dispatches stored energy from the power cache and feeds it to the datacenter, resulting in a mixture of non-variable and variable power sources used to achieve the power management goals, such as reduced power cost, increased power availability, and lowered carbon footprint for the datacenter.

Datacenter power management using variable power sources

In disclosed techniques, augmented power control within a datacenter uses predictive modeling. A power usage by a first data rack within a datacenter is measured, using one or more processors, over a first period of time. A predicted power usage by the first data rack over a second period of time is generated on a computing device, wherein the second period of time is subsequent to the first period of time. A power correlation model is calculated that correlates a power prediction to an actual power usage. The predicted power usage for the second period of time is refined, based on the predicted power usage and the power correlation model. The refining is accomplished using a power prediction model comprising the predicted power usage and the power correlation model. Datacenter power structure is configured, based on the refined power usage prediction.

Augmented power control within a datacenter using predictive modeling

Techniques for datacenter power management using dynamic redundancy are disclosed. A power control switch is configured to selectively apply power to one or two power cords of a dual-corded electronic apparatus. When the power control switch energizes both power cords, the electronic apparatus operates in 2N redundancy. When the power control switch energizes only one of the power cords, the electronic apparatus operates in 1N redundancy. The power control switch is configured to dynamically change the redundancy mode based on service level agreement (SLA) criteria, power policies, power supply and demand, and environmental factors.

Datacenter power management using dynamic redundancy

Example embodiments of the present invention relate to methods, a system, and a computer program product for performing governed replay for compliance applications. The method includes maintaining a repository and executing an audit, including a control and one or more processes, to determine compliance of a state of the cloud infrastructure environment. The method further includes storing in the repository a control metadata object including content addresses to the processes for the audit as an immutable control and process objects, respectively, storing in the repository input metadata and output metadata identifying inputs to and outputs from the control and the processes as immutable input metadata objects and output metadata objects, respectively, and storing a timestamp metadata object, including a timestamp and content addresses to the control object, the process objects, the input objects, and the output objects, as an immutable metadata object in the repository.

Method and system for governed replay for compliance applications

A value is obtained from a set of values respectively assigned to a set of characteristics of a first control associated with at least one trust dimension attributable to a given infrastructure, wherein the given infrastructure comprises one or more elements. An infrastructure trust index is computed based at least on the obtained value, wherein the infrastructure trust index characterizes a trustworthiness attributable to the given infrastructure.

Infrastructure trust index

Techniques for determining and representing the veracity of data stored in a data repository and results of queries directed to the stored data by utilizing information lineage that is indicative of the veracity of the stored data. For example, in one example, one or more data repositories are maintained. The one or more data repositories comprise metadata representative of the veracity of one or more data sets stored in the one or more data repositories. In response to a query to at least one data set of the one or more data sets stored in the one or more data repositories, a result of the query for the at least one data set is returned in combination with corresponding metadata representing the veracity of the at least one data set.

Lineage-based veracity for data repositories

One or more trust characteristics are obtained. The one or more trust characteristics are attributable to a storage infrastructure from which one or more data sets stored in one or more data repositories are obtained. The one or more trust characteristics attributable to the storage infrastructure are associated with the one or more data sets such that the one or more data sets are characterized as having a trustworthiness reflective of the one or more trust characteristics. The one or more trust characteristics and the association with the one or more data sets are stored as metadata in the one or more data repositories.

Use of trust characteristics of storage infrastructure in data repositories

Techniques are disclosed for governed or constrained deployment of one or more applications on trusted infrastructure of a cloud infrastructure environment. For example, a repository of metadata (e.g., metadata lake) is maintained. The metadata repository includes metadata associated with applications, metadata associated with content associated with the applications, and metadata associated with a cloud infrastructure environment in which the applications are deployable. A deployment is determined for a given application on a trusted infrastructure within the cloud infrastructure environment based on at least a subset of the metadata maintained in the metadata repository. The determination of the deployment of the given application based on the subset of the metadata includes mapping trust-based criteria associated with the given application with a portion of infrastructure of the cloud infrastructure environment that satisfies the trust-based criteria.

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El Dorado Hills, CA, United States of America

Nikhil Sharma