Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving, by a systems management console, a network address of a device in a virtual environment, and determining a network address associated with a virtual environment management console based on the received network address of the device in the virtual environment. The method also includes sending, by the systems management console via a systems management agent to the virtual environment management console using the determined network address associated with the virtual environment management console, a request for network addresses of virtual machine (VM) host servers and VMs in the virtual environment. The method also includes receiving, by the systems management console via the systems management agent from the virtual environment management console, the network addresses of the VM host servers and the VMs in the virtual environment and providing a notification of the discovered VM host servers and VMs.
Abstract: A method includes receiving data collected from a plurality of managed devices in a plurality of data collections. The data collections are performed using a plurality of collection protocols. A trigger that generated each of given ones of the data collections is determined. The method further includes identifying a collection protocol of the plurality of collection protocols used for each of the given ones of the data collections, and determining one or more attributes of a plurality of attributes of the plurality of managed devices that have been collected using given ones of the collection protocols. A mapping is generated between the triggers, the collection protocols and the attributes using one or more machine learning algorithms. The generated mapping is used to predict one or more collection protocols of the plurality of collection protocols to use to collect data from one or more of the managed devices.
Type:
Application
Filed:
May 6, 2020
Publication date:
November 11, 2021
Inventors:
Parminder Singh Sethi, Durai S. Singh, Lakshmi Saroja Nalam
Abstract: Techniques for failure prediction and remediation are disclosed. For example, a method comprises training one or more machine learning algorithms with a training dataset corresponding to a plurality of users, wherein the training dataset comprises at least one of product purchase data, product service data and product return data corresponding to the plurality of users. In the method, an input dataset corresponding to at least one user is received. The input dataset comprises at least one of product purchase data, product service data and product return data corresponding to the user. The input dataset is analyzed using the one or more machine learning algorithms. The method further comprises predicting, based at least in part on the analyzing, a likelihood of whether at least one product corresponding to the user will fail to be returned to a product providing entity when a return of the product has been requested.
Abstract: In some examples, after a client system encounters a problem, a technical support specialist may connect to the client system via a console. The console may display a graphical representation of a client system that includes a plurality of components. The console may execute a machine learning module to determine one or more potential solutions to the particular problem. Each solution of the one or more solutions may correspond to a previously resolved problem that is similar to the particular problem and may have an associated confidence level determined based on: a similarity of the particular problem to the previously resolved problem, a similarity of the plurality of components to a second plurality of components included in a second client system associated with the previously resolved problem, a similarity of a network topology of the client system to a second network topology of the second client system.
Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving, by a systems management console, a network address of a device in a virtual environment, and determining a network address associated with a virtual environment management console based on the received network address of the device in the virtual environment. The method also includes sending, by the systems management console via a systems management agent to the virtual environment management console using the determined network address associated with the virtual environment management console, a request for network addresses of virtual machine (VM) host servers and VMs in the virtual environment. The method also includes receiving, by the systems management console via the systems management agent from the virtual environment management console, the network addresses of the VM host servers and the VMs in the virtual environment and providing a notification of the discovered VM host servers and VMs.
Abstract: A method includes receiving data collected from a plurality of managed devices in a plurality of data collections. The data collections are performed using a plurality of collection protocols. A trigger that generated each of given ones of the data collections is determined. The method further includes identifying a collection protocol of the plurality of collection protocols used for each of the given ones of the data collections, and determining one or more attributes of a plurality of attributes of the plurality of managed devices that have been collected using given ones of the collection protocols. A mapping is generated between the triggers, the collection protocols and the attributes using one or more machine learning algorithms. The generated mapping is used to predict one or more collection protocols of the plurality of collection protocols to use to collect data from one or more of the managed devices.
Type:
Grant
Filed:
May 6, 2020
Date of Patent:
June 27, 2023
Assignee:
EMC IP Holding Company LLC
Inventors:
Parminder Singh Sethi, Durai S. Singh, Lakshmi Saroja Nalam
Abstract: A system and method intelligently collect performance data from managed electronic devices. A machine learning model (e.g. linear time series forecasting) is used to predict a future workload for each of a selection of devices, and a regression analysis is used to predict how long is likely to be required to collect performance state from each component of each device. These data are then mapped together to predict future overall idle periods of each device, together with components whose performance data may be collected during those periods. The components are grouped in batches according to a relevance order that itself may be determined by applying a machine learning model such as k-nearest neighbors. Then, performance data are collected according to the batches. In this way, performance data may be collected in chunks while avoiding a negative impact on execution of the primary functions of the managed devices.
Type:
Application
Filed:
July 16, 2021
Publication date:
December 8, 2022
Applicant:
Dell Products L.P.
Inventors:
Parminder Singh SETHI, Lakshmi S. NALAM, Durai SINGH
Abstract: An apparatus comprises a processing device configured to collect system state information from host devices, to split the collected system state information into logical chunks, and to determine, based at least in part on a plurality of factors, a compression level to be applied to each of the logical chunks. The plurality of factors comprise a first factor characterizing a time at which the collected system state information is needed at a destination device and at least a second factor characterizing resources available for at least one of performing compression of the collected system state information and transmitting the collected system state information over at least one network to the destination device. The processing device is further configured to apply the determined compression level to each of the logical chunks to generate compressed logical chunks, and to transmit the compressed logical chunks to the destination device.
Type:
Grant
Filed:
July 20, 2021
Date of Patent:
April 18, 2023
Assignee:
Dell Products L.P.
Inventors:
Parminder Singh Sethi, Lakshmi Saroja Nalam, Durai S. Singh
Abstract: A method for managing resource utilization includes identifying a quota limit of an environment, performing a forecast of system resource utilization for an application running on the environment, making a determination that the forecast of system resource utilization would cause the quota limit to be exceeded, and increasing the quota limit based on the determination.
Abstract: An access credential is modified at one device, wherein the device is part of a secure private network of multiple devices. Each other device in the secure private network receives notification of the modification. The credential modification is implemented when at least a subset of the other devices each accept the credential modification.
Abstract: In general, embodiments relate to a method for managing a technical support session, comprising: generating a question path graph (QPG) based on a plurality of question sequences associated with technical support sessions, and displaying at least a portion of the QPG to a technical support person (TSP) during a technical support session.
Abstract: A method comprises analyzing performance data of a system using one or more machine learning techniques. The system comprises a plurality of hardware components. In the method, a priority list of the plurality of hardware components is generated based on the analysis, and power from one or more power sources is distributed to one or more of the plurality of hardware components based on the priority list.
Abstract: An information handling system includes a processor configured to store a first module of a software application, the first module of the software application selected based on customer journey information pertaining to usage of the software application. The processor begins execution of the first module prior to receipt of a second module of the software application, the second module selected based on the customer journey information.
Abstract: In general, embodiments relate to a method for managing a technical support session, comprising: determining a technical support issue (TSI) for a technical support session; identifying a question path graph (QPG) associated with the TSI; and displaying at least a portion of the QPG to a technical support person (TSP) during the technical support session.
Abstract: Techniques for management of data security are disclosed. For example, a method comprises collecting data from one or more devices, and predicting security levels of respective portions of the data using one or more machine learning algorithms. In the method, security configurations for a subset of the respective portions of the data are implemented based, at least in part, on corresponding predicted security levels of the subset of the respective portions.
Type:
Application
Filed:
June 7, 2022
Publication date:
December 7, 2023
Inventors:
Parminder Singh Sethi, Nithish Kote, Thanuja C
Abstract: An access credential is modified at one device, wherein the device is part of a secure private network of multiple devices. Each other device in the secure private network receives notification of the modification. The credential modification is implemented when at least a subset of the other devices each accept the credential modification.
Abstract: A method comprises extracting data for one or more assets corresponding to a user, and analyzing the data using one or more machine learning models. The analyzing comprises predicting whether the one or more assets will require at least one of replacement and service. In the method, one or more entitlement recommendations for the user are generated based on the analysis, and the one or more entitlement recommendations are transmitted to the user.
Abstract: A user interface is presented to a user. The method determines whether or not to customize a size of one or more components on the user interface. The method then determines one or more candidate components on the user interface to customize, when a determination is made to customize a size of one or more components on the user interface. The method customizes the one or more candidate components on the user interface, and presents a customized user interface to the user.
Abstract: A method comprises receiving a notification of an issue with at least one component of a plurality of components in a computing environment. One or more machine learning algorithms are used to determine one or more components of the plurality of components impacted by the issue with the at least one component. The method further comprises collecting operational data for the at least one component and the one or more impacted components.
Type:
Application
Filed:
January 15, 2021
Publication date:
July 21, 2022
Inventors:
Parminder Singh Sethi, Anannya Roy Chowdhury
Abstract: Aspects of the disclosure include an escalated authentication system based on user behavior patterns. A user's behavior pattern on a device is collected and/or learned. The collected or learned pattern can be compared to subsequent behavior patterns to determine whether the current user is genuine or suspicious. Users deemed suspicious are subject to increased authentication requirements, often on-the-fly.