Patents by Inventor Ajay Krishna BORRA

Ajay Krishna BORRA has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11327952
    Abstract: A metric data stream for a plurality of metrics may be retrieved from a database system. Each metric may measure a respective computing characteristic. The metric data stream may include a plurality of values for each of a sequence of time intervals. Each value may correspond with a respective one of the metrics. A plurality of metric correlation matrices may be determined for the metrics, each of which is associated with a respective time period in the metric data stream. A subset of comparison metric correlation matrices may be selected from the plurality of metric correlation metric matrices. A designated anomaly score may be determined for a designated time period by comparing a designated metric correlation matrix associated with the designated time period with the selected subset of comparison metric correlation metric matrices.
    Type: Grant
    Filed: September 6, 2019
    Date of Patent: May 10, 2022
    Assignee: salesforce.com, Inc.
    Inventors: Ajay Krishna Borra, Gokulakrishnan Gopalakrishnan, Manpreet Singh, Brian Toal, Laksh Venka, Metarya Ruparel
  • Patent number: 11270210
    Abstract: Systems, device and techniques are disclosed for outlier discovery system selection. A set of time series data including time series data objects may be received. A sample of time series data objects may be extracted from the time series data. The sample of time series data objects may be decomposed into sub-components. Statistical classification may be used to select an outlier discovery system based on the sub-components. A neural network may be used to select an outlier discovery system based on the sub-components. A level of error of the neural network may be determined based on a comparison of the outlier discovery system selection made using statistical classification and the outlier discovery system selection made by the neural network. Weight of the neural network may be updated based on the level of error of the neural network.
    Type: Grant
    Filed: April 6, 2020
    Date of Patent: March 8, 2022
    Assignee: salesforce.com, inc.
    Inventors: Ajay Krishna Borra, Manpreet Singh
  • Publication number: 20210173670
    Abstract: Example implementations relate to performing automated hierarchical configuration tuning for a multi-layer service. According to an example, a service definition and optimization criteria are received for tuning a configuration of a service. The service definition includes information regarding multiple of layers of the service and corresponding configuration groups. An acyclic dependency graph is created including nodes representing each of the of layers and each of the corresponding configuration groups.
    Type: Application
    Filed: December 10, 2019
    Publication date: June 10, 2021
    Inventors: Ajay Krishna Borra, Himanshu Mittal, Metarya Ruparel, Ravi Teja Pothana, Manpreet Singh
  • Patent number: 10979424
    Abstract: A cloud services application executing on a cloud computing platform receives from a browser application executing on a customer computer system a request of a user to login to the cloud services application. The cloud services application further receives an indication via the browser application that biometric identifier authentication of the user is supported by the customer computer system, and transmits an indication to the browser application that biometric identifier authentication of the user is enabled for a session that is to be established. The cloud services application transmits a response to the login request, responsive to receipt of the login request, the response prompting the user to input a biometric identifier, and receives a unique identifier (UID) associated with the biometric identifier.
    Type: Grant
    Filed: October 1, 2018
    Date of Patent: April 13, 2021
    Assignee: salesforce.com, inc.
    Inventors: Amal Thannuvelil Surendran, Himanshu Mittal, Ajay Krishna Borra, Manpreet Singh
  • Publication number: 20210073200
    Abstract: A metric data stream for a plurality of metrics may be retrieved from a database system. Each metric may measure a respective computing characteristic. The metric data stream may include a plurality of values for each of a sequence of time intervals. Each value may correspond with a respective one of the metrics. A plurality of metric correlation matrices may be determined for the metrics, each of which is associated with a respective time period in the metric data stream. A subset of comparison metric correlation matrices may be selected from the plurality of metric correlation metric matrices. A designated anomaly score may be determined for a designated time period by comparing a designated metric correlation matrix associated with the designated time period with the selected subset of comparison metric correlation metric matrices.
    Type: Application
    Filed: September 6, 2019
    Publication date: March 11, 2021
    Applicant: Salesforce.com, Inc.
    Inventors: Ajay Krishna BORRA, Gokulakrishnan GOPALAKRISHNAN, Manpreet SINGH, Brian TOAL, Laksh VENKA, Metarya RUPAREL
  • Patent number: 10936308
    Abstract: Systems, methods, and computer-readable media are provided for a multi-tenant collaborative learning environment, where information from all tenants in a multi-tenant system is collected and used to provide individual tenants with code fixes and/or optimization recommendations based on the collected information. Other embodiments may be described and/or claimed.
    Type: Grant
    Filed: April 30, 2018
    Date of Patent: March 2, 2021
    Assignee: SALESFORCE.COM, INC.
    Inventors: Ajay Krishna Borra, Manpreet Singh, Himanshu Mittal, Edet Nkposong
  • Publication number: 20200334540
    Abstract: Systems, device and techniques are disclosed for outlier discovery system selection. A set of time series data including time series data objects may be received. A sample of time series data objects may be extracted from the time series data. The sample of time series data objects may be decomposed into sub-components. Statistical classification may be used to select an outlier discovery system based on the sub-components. A neural network may be used to select an outlier discovery system based on the sub-components. A level of error of the neural network may be determined based on a comparison of the outlier discovery system selection made using statistical classification and the outlier discovery system selection made by the neural network. Weight of the neural network may be updated based on the level of error of the neural network.
    Type: Application
    Filed: April 6, 2020
    Publication date: October 22, 2020
    Inventors: Ajay Krishna BORRA, Manpreet SINGH
  • Patent number: 10802884
    Abstract: Systems and methods for provisioning infrastructure to application workloads may include receiving, by a server computing system, profile information of an application workload, the profile information describing resource usage of the application workload; receiving, by the server computing system, burn-in information for hardware components of an infrastructure, the burn-in information including benchmark information; receiving, by the server computing system, hardware configuration information associated with the infrastructure, the hardware information including capacity information; receiving, by the server computing system, a policy definition describing provisioning parameters; generating, by the server computing system, a first infrastructure distribution based at least on the profile information, the burn-in information, the hardware configuration information, and the policy definition; and provisioning, by the server computing system, the infrastructure to the application workload based at least on t
    Type: Grant
    Filed: January 17, 2018
    Date of Patent: October 13, 2020
    Assignee: salesforce.com, inc.
    Inventors: Ajay Krishna Borra, Manpreet Singh, Edet Nkposong, Himanshu Mittal
  • Publication number: 20200226156
    Abstract: Embodiments of the invention identify entities stored within or across a number of data stores and identify relationships between the entities. A relationships graph is generated that represents the entities and the identified relationships between entities, the relationships graph comprising nodes in the relationships graph to represent one or more entities and edges between any two nodes in the relationships graph to represent the identified relationships between the one or more entities represented by each of the two nodes. The relationships graph is stored in a graph store. A graph query is received against selected nodes and edges in the graph store. One or more data store queries are generated therefrom, to be executed against respective selected ones of the one or more entities and their respective identified relationships based on the graph query and the graph store. The one or more data store queries are applied to selected one or more of the number of data stores.
    Type: Application
    Filed: January 14, 2019
    Publication date: July 16, 2020
    Inventors: Ajay Krishna Borra, Manpreet Singh, Himanshu Mittal, Mitesh Jain
  • Patent number: 10614362
    Abstract: Systems, device and techniques are disclosed for outlier discovery system selection. A set of time series data including time series data objects may be received. A sample of time series data objects may be extracted from the time series data. The sample of time series data objects may be decomposed into sub-components. Statistical classification may be used to select an outlier discovery system based on the sub-components. A neural network may be used to select an outlier discovery system based on the sub-components. A level of error of the neural network may be determined based on a comparison of the outlier discovery system selection made using statistical classification and the outlier discovery system selection made by the neural network. Weight of the neural network may be updated based on the level of error of the neural network.
    Type: Grant
    Filed: May 30, 2017
    Date of Patent: April 7, 2020
    Assignee: salesforce.com, inc.
    Inventors: Ajay Krishna Borra, Manpreet Singh
  • Publication number: 20200106770
    Abstract: A cloud services application executing on a cloud computing platform receives from a browser application executing on a customer computer system a request of a user to login to the cloud services application. The cloud services application further receives an indication via the browser application that biometric identifier authentication of the user is supported by the customer computer system, and transmits an indication to the browser application that biometric identifier authentication of the user is enabled for a session that is to be established. The cloud services application transmits a response to the login request, responsive to receipt of the login request, the response prompting the user to input a biometric identifier, and receives a unique identifier (UID) associated with the biometric identifier.
    Type: Application
    Filed: October 1, 2018
    Publication date: April 2, 2020
    Inventors: Amal Thannuvelil Surendran, Himanshu Mittal, Ajay Krishna Borra, Manpreet Singh
  • Publication number: 20190332376
    Abstract: Systems, methods, and computer-readable media are provided for a multi-tenant collaborative learning environment, where information from all tenants in a multi-tenant system is collected and used to provide individual tenants with code fixes and/or optimization recommendations based on the collected information. Other embodiments may be described and/or claimed.
    Type: Application
    Filed: April 30, 2018
    Publication date: October 31, 2019
    Applicant: salesforce.com, inc.
    Inventors: Ajay Krishna BORRA, Manpreet SINGH, Himanshu MITTAL, Edet NKPOSONG
  • Publication number: 20190220314
    Abstract: Systems and methods for provisioning infrastructure to application workloads may include receiving, by a server computing system, profile information of an application workload, the profile information describing resource usage of the application workload; receiving, by the server computing system, burn-in information for hardware components of an infrastructure, the burn-in information including benchmark information; receiving, by the server computing system, hardware configuration information associated with the infrastructure, the hardware information including capacity information; receiving, by the server computing system, a policy definition describing provisioning parameters; generating, by the server computing system, a first infrastructure distribution based at least on the profile information, the burn-in information, the hardware configuration information, and the policy definition; and provisioning, by the server computing system, the infrastructure to the application workload based at least on t
    Type: Application
    Filed: January 17, 2018
    Publication date: July 18, 2019
    Inventors: Ajay Krishna Borra, Manpreet Singh, Edet Nkposong, Himanshu Mittal
  • Publication number: 20180349323
    Abstract: Systems, device and techniques are disclosed for outlier discovery system selection. A set of time series data including time series data objects may be received. A sample of time series data objects may be extracted from the time series data. The sample of time series data objects may be decomposed into sub-components. Statistical classification may be used to select an outlier discovery system based on the sub-components. A neural network may be used to select an outlier discovery system based on the sub-components. A level of error of the neural network may be determined based on a comparison of the outlier discovery system selection made using statistical classification and the outlier discovery system selection made by the neural network. Weight of the neural network may be updated based on the level of error of the neural network.
    Type: Application
    Filed: May 30, 2017
    Publication date: December 6, 2018
    Inventors: Ajay Krishna BORRA, Manpreet SINGH