Emc IP Holding Company LLC

Dell Products Inc.

Hemant Ramesh Gaikwad

Rahul Deo Vishwakarma

Shelesh Chopra

Vaideeswaran Ganesan

Pravin Janakiram

Parmeshwr Prasad

Sharath Talkad Srinivasan

Gopal Singh

Ashish Singh

Vaideeswaran G

Nishant Yogendrakumar Vijayvergiya

Techniques described herein relate to methods and systems for thermal management of a thermal environment. The method may include using thermal data items from computing devices and time series analysis to predict future thermal values for the thermal data items; performing a clustering analysis using the predicted future thermal values to assign cluster labels to the computing devices; using the cluster labels and the predicted future thermal values to assign predicted thermal status labels to the computing devices; assigning a confidence value to the predicted thermal status labels and ranking the computing devices based on the confidence values; performing an analysis to determine a thermal data item contributing to the assigned thermal status; and sending the results to a thermal environment administrator.

Systems and methods for device thermal management using dynamic ranking of device cooling needs

A system update appliance includes a processor and a memory device with a Content Addressable Storage (CAS) space and a location addressable storage space. The location addressable storage space partitioned into an object storage space and a device storage space. The processor stores a device entry in the device storage space. The device entry is associated with a device external to the system update appliance and includes a component entry for a component of the device. The component operates based on an update. The component entry includes a description of the component and a pointer to a record stored in the CAS space. The processor stores the record in the CAS space. The record is associated with a combination of the component and the first update. The record includes the description, a second pointer to an update repository, and a third pointer to the object storage space. When the update is not stored in the object storage space, the third pointer is a null pointer and when the update is stored in the object storage space, the third pointer includes an address of the update in the object storage space.

System and method for content addressable storage system update appliance

Systems and methods are provided for context-aware maintenance window identification. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: estimate a completion time of a maintenance operation; predict future usage of the IHS; identify a time window for the maintenance operation based upon the estimation and the prediction.

Context-aware maintenance window identification

In general, embodiments relate to a managing a Redundant Array of Independent Disks (RAID) group. The embodiments include determining a minimum and maximum set of spare disks to allocate to the RAID group, wherein the RAID group comprises a plurality of active members, allocating the minimum number of spare members to the RAID group, allocating an additional spare member to the RAID group, setting a mode of the additional spare member to storage mode, enabling, after the setting, the RAID controller to store data in the plurality of active members and in the additional spare member, wherein the plurality of active members, the minimum number of spare members, and the additional spare member comprise persistent storage.

Variable sparing of disk drives in storage array

In general, in one aspect, the invention relates to a method for managing updates, the method includes identifying a sub-tree based on a call graph, generating an update sequence for the sub-tree using the call graph, selecting a first component of the sub-tree based on the update sequence, wherein the first component is a hardware resource, applying an update to the first component to obtain a first updated component, selecting, after applying the update to the first component, a second component of the sub-tree based on the update sequence, and performing an update on the second component.

Method of creating an intelligent upgrade flow for a heterogeneous data center

A method for managing updates of a data manager includes: obtaining a service call graph where the service call graph includes services grouped into service sub-trees and specifies a service hierarchy between the services; identifying the service sub-trees of the service call graph; identifying, using the service hierarchy, independent services among the services of the service call graph; generating, based on identifying the service sub-trees and the independent services, an update sequence for the services; predicting, using the update sequence and the services, an update window for the service sub-trees; and initiating an update of the services using the prediction of the update window.

System and method for intelligent update flow across inter and intra update dependencies

Techniques described herein relate to a method for deploying workflows with data management services. The method may include identifying a service update event; identifying a service sub-tree based on a service call graph; generating an update sequence for the service sub-tree; predicting an update window for the service sub-tree using a final estimated updated completion time for the service, wherein the final estimated updated completion time is based on a risk profile; selecting a first service of the service sub-tree based on the update sequence, wherein the first service includes a first standby service instance and a first active service instance; generating a backup of a first portion of a services shared data volume repository associated with the first service; and applying an update to the first standby service instance to obtain a first updated active service instance.

Method and system for determining favorability of upgrade window

Methods, apparatus, and processor-readable storage media for automatically allocating device resources using machine learning techniques are provided herein. An example computer-implemented method includes determining values for multiple parameters from data obtained from one or more devices; generating at least one device component failure prediction by applying one or more machine learning techniques to at least a portion of the determined values; computing one or more qualifying values attributable to the at least one generated device component failure prediction by providing the at least one generated device component failure prediction to a conformal prediction framework; and automatically allocating one or more resources to at least a portion of the one or more devices based at least in part on the at least one generated device component failure prediction and the one or more computed qualifying values.

Automatically allocating device resources using machine learning techniques

A system for data processing, comprising a plurality of data center nodes, each data center node having an associated power requirement. A dynamic power capping system operating on a processor and coupled to the plurality of data center nodes, wherein the processor is configured by the dynamic power capping system to implement one or more algorithms that cause the processor to determine a power requirement for each of the plurality of data center nodes and to implement a power setting at each of the plurality of data center nodes that corresponds to the power requirement for the data center node.

Intelligent and predictive optimization of power needs across virtualized environments

Techniques described herein relate to a method for deploying workflows with data management services. The method may include identifying a service update event; identifying a service sub-tree based on a service call graph; generating an update sequence for the service sub-tree; predicting an update window for the service sub-tree; selecting a first service of the service sub-tree based on the update sequence, wherein the first service includes a first standby service instance and a first active service instance; generating a backup of a first portion of a services shared data volume repository associated with the first service; applying an update to the first standby service instance to obtain a first updated active service instance; making a first determination that a first performance and reliability check associated with the first updated active service instance is below a threshold; applying the update to a second standby service instance.

Growing community of inventors

Bengaluru, India

Hemant Ramesh Gaikwad