Patents by Inventor Nidhi Verma

Nidhi Verma 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).

  • Publication number: 20240037077
    Abstract: New and innovative systems and methods for federating operations, maintenance and governance of day to day activities in a data mesh platform are provided via a self-service mesh. A variety of embodiments include a computer-implemented method including obtaining a new data product request from a domain data system, generating domain data product definitions, providing the domain data product definitions to the domain data system, and updating a data catalog to indicate the domain data system and the domain data product definitions.
    Type: Application
    Filed: July 28, 2023
    Publication date: February 1, 2024
    Inventors: Sumedha Verma, Syed Atif Akhtar, Nidhi Mann
  • Publication number: 20240020199
    Abstract: A data processing system implements managing the deployment of updates to a cloud-based service by deploying an update to one or more components of a cloud-based service according to a deployment plan. The deployment plan defines a plurality of stages in which the update is deployed to a subset of the components associated with a different subset of users of a userbase. The system implements receiving signal data that includes information regarding the performance of the update at each stage of the deployment plan; analyzing the signal data to determine whether one or more trigger conditions of halt and recovery rules associated with the update have been satisfied; and automatically halting deployment of the update to the one or more components of the cloud-based service responsive to at least one of the trigger conditions associated with the halt and recovery rules associated with the update having been satisfied.
    Type: Application
    Filed: July 14, 2022
    Publication date: January 18, 2024
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nidhi VERMA, Rahul NIGAM, Sudharsan GANESAN
  • Patent number: 11855844
    Abstract: Technologies are disclosed for improving the deployment of a cloud-hosted service. Before being deployed to a particular environment, a cloud-hosted service must be configured for that environment. Configuring a deployment includes determining which components to deploy, determining how to connect with external components, identifying onboarding procedures, etc. A dependency data model defines a hierarchy of components utilized by the cloud-hosted service. For each component in the hierarchy, configuration parameters define how to deploy that component. A list of configuration parameters that do not yet have values for a target environment may be generated and provided to a user. Values for these parameters may then be received. A configuration for the target environment is then generated based on the dependency data model and the received values. The dependency data model may inherit dependencies and configuration properties from ancestors in a hierarchy of dependency data models.
    Type: Grant
    Filed: May 27, 2021
    Date of Patent: December 26, 2023
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Nidhi Verma, Roberta Cannerozzi, Erik Wahlstrom, Le Chang
  • Publication number: 20230385101
    Abstract: Systems and methods for creating and deploying jobs in a cloud-based service include receiving a job definition defining job attributes pertaining to a job to be deployed in a cloud-based service. The job definition is processed to determine whether the job definition complies with predefined rules for job creation in the cloud-based service. Based on the determination of whether the job definition complies with the predefined rules for job creation in the cloud-based server, the job may be validated or not validated in the cloud-based service. Deployment policies are determined for validated jobs based on the job definition for the validated job.
    Type: Application
    Filed: May 31, 2022
    Publication date: November 30, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nidhi VERMA, Rahul NIGAM, Chandramouleeswaran KRISHNASWAMY
  • Patent number: 11829743
    Abstract: A method of and system for customizing a rollout process of application features includes providing a list of one or more application features for display on a user interface screen, the software application features being application features that are scheduled for a staged rollout, enabling selection of one of the application features for enrolling in late-stage rollout or opting out of the staged rollout, receiving a request for enrolling a user entity in late-stage rollout or opting the user entity out of the staged rollout, storing a property associated with the user entity in a data store, the property indicative of the user entity enrolling in late-stage rollout or opting out of the staged rollout, accessing the stored property, when selecting a plurality of enterprises or users for the staged rollout of the application feature, and depending on the accessed property, selecting the user entity for late-stage rollout or not selecting the user entity for the staged rollout.
    Type: Grant
    Filed: September 29, 2021
    Date of Patent: November 28, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Nidhi Verma, Divyachapan Sridharan Padur, Zohar Raz
  • Patent number: 11803310
    Abstract: Disclosed herein is a system for improving the user experience in the face of a regression by returning resources that offer a service to a “last known good” upgrade. In other words, the state of the resources is reconfigured to scale back from recent upgrade(s), the deployments of which likely caused the regression, to a previous upgrade that is known to have little or no effect on the user experience. To identify a problem, the system collects performance data from different resource units that make up a cloud-based platform. The performance data is collected for each upgrade event in a sequence of upgrade events that are currently deployed or being deployed. The system continually tracks and analyzes qualification data collected for each of the deployed upgrade events. The system can tag an upgrade event as the last known good upgrade event when the collected qualification data satisfies predefined qualifications.
    Type: Grant
    Filed: April 28, 2021
    Date of Patent: October 31, 2023
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Nidhi Verma, Daniel Oh, Amber Litteken, Rahul Nigam
  • Publication number: 20230344700
    Abstract: Please replace the Abstract of the Disclosure with the following Abstract showing all changes relative to the previous version of the Abstract (In the replacement Abstract, the header and footer have been marked out):
    Type: Application
    Filed: April 26, 2022
    Publication date: October 26, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nidhi VERMA, Rahul NIGAM, Sudharsan GANESAN
  • Patent number: 11782695
    Abstract: A data processing system implements obtaining a set of first input parameters associated with a first update to be deployed to one or more components of a cloud-based service; providing the set of first input parameters to a machine learning model to obtain a first deployment policy for the first update; analyzing the set of first input parameters using the machine learning model to generate the first deployment policy, the machine learning model being trained to analyze input parameters associated with an update to be deployed to the cloud-based service and to generate a deployment policy for the update, the deployment policy identifying a set of rings for deploying the update and when the update is to be deployed to a subset of the userbase of the cloud-based service associated with that ring; and executing the first deployment policy to deploy the update to the one or more components.
    Type: Grant
    Filed: November 29, 2021
    Date of Patent: October 10, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Nidhi Verma, Rahul Nigam, Rohan Khanna
  • Publication number: 20230306064
    Abstract: A system and method to allow an authorized searcher to conduct a search of a current primary version of a document being developed in an application as well as versions of the document which were used in the development of the current primary version. In an exemplary system, instructions cause a processor to grant a search request to search, via a search index in a cloud storage, stored selected versions of the document. The stored selected versions of the document are historical versions of the current primary version of the document which has been selected from among the stored selected versions to be accessible, via the search index, to other searchers having a lower access authorization than the predetermined access authorization. The authorized searcher is provided with a capability to toggle between searching only the primary version of the document and searching the stored selected versions of the document.
    Type: Application
    Filed: March 24, 2022
    Publication date: September 28, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nidhi VERMA, Neetha Sumana TULURI, John R. BERKELEY, Roberta CANNEROZZI, Kristofer Duncan HOFFMAN
  • Publication number: 20230221941
    Abstract: A data processing system implements obtaining policy information for an update to be deployed to one or more components of a cloud-based service identifying a plurality of rings of the cloud-based service to which the update is to be deployed; analyzing the policy information to determine configuration information for a plurality of installer instances each associated with one or more rings or one or more stages of a ring to which the update is to be deployed; obtaining payload information for each respective installer instance, the payload information indicating one or more payloads associated with the update to be deployed to the respective one or more rings or one or more stages of the ring associated with the respective installer instance; and deploying the one or more payloads for each of the one or more rings or the one or more stages of the ring associated with each installer instance.
    Type: Application
    Filed: January 12, 2022
    Publication date: July 13, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Dmitry Valentinovich KHOLODKOV, Rahul NIGAM, Nidhi VERMA
  • Publication number: 20230222001
    Abstract: A data processing system implements obtaining a set of input parameters associated with an update to be deployed to a plurality of server farms of a cloud-based service, wherein each server farm includes a primary replica configured to handle user traffic and a disaster recovery replica configured to handle user traffic responsive to a failure of the primary replica; determining temperature information for each of the server farms, ranking the server farms based on the temperature information to determine an order in which an update is to be deployed to the server farms; iteratively deploying the updates to the primary replicas of the server farms according to the ranking until an deployment threshold has been satisfied; and iteratively deploying the updates to the primary replicas of server farms for which the primary replicas have not yet been updated and to the disaster recovery replicas of the server farms.
    Type: Application
    Filed: January 11, 2022
    Publication date: July 13, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nidhi VERMA, Rahul NIGAM, Rohan KHANNA
  • Publication number: 20230168880
    Abstract: A data processing system implements obtaining a set of first input parameters associated with a first update to be deployed to one or more components of a cloud-based service; providing the set of first input parameters to a machine learning model to obtain a first deployment policy for the first update; analyzing the set of first input parameters using the machine learning model to generate the first deployment policy, the machine learning model being trained to analyze input parameters associated with an update to be deployed to the cloud-based service and to generate a deployment policy for the update, the deployment policy identifying a set of rings for deploying the update and when the update is to be deployed to a subset of the userbase of the cloud-based service associated with that ring; and executing the first deployment policy to deploy the update to the one or more components.
    Type: Application
    Filed: November 29, 2021
    Publication date: June 1, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nidhi VERMA, Rahul NIGAM, Rohan KHANNA
  • Patent number: 11650805
    Abstract: Reliable feature deployment is provided. Features are evaluated for their readiness to be graduated and features that are ready to be graduated are added to a graduation list. When features are added to the graduation list, evaluation of the features is discontinued, thereby reducing the performance and runtime costs associated with deploying features. Furthermore, engineers can consult the graduation list to identify features that are ready for graduation, thereby reducing the risk of premature flight graduation. Data associated with features is analyzed to map the features to corresponding flights. In this way, when an engineer identifies a feature for graduation, the engineer is able to identify the corresponding flight (or flights) from the mapping. Even when a feature is selected for graduation, the present systems provide additional safeguards to ensure that corresponding flights are not improperly or prematurely graduated, thereby preventing a subpar customer experience.
    Type: Grant
    Filed: June 16, 2020
    Date of Patent: May 16, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Nidhi Verma, Ankur Jauhari, Min Shao, Shobana Krishnamoorthy
  • Publication number: 20230146669
    Abstract: The techniques disclosed herein enable improved security as well as more scalable and reliable job execution by utilizing granular security boundaries and certificate-based authentication for all communication within cloud-based platforms. To manage a cloud-based platform, a system receives a plurality of jobs and associated certificates at a first security boundary that are to be executed at various resource units within a second security boundary. The system then authenticates each certificate before transmitting each job to its respective resource unit for execution. In addition, the system is further configured to monitor active certificates for compromise and accordingly isolate various security boundaries in the event of a security breach. By isolating portions of the cloud-based platform within security boundaries, the system can mitigate the impact of security breaches. Furthermore, certificate-based authentication addresses performance constraints to enable more efficient and scalable job execution.
    Type: Application
    Filed: November 5, 2021
    Publication date: May 11, 2023
    Inventors: Nidhi VERMA, Roberta CANNEROZZI, Brian Gregory O'CONNOR, Darius SNAPKAUSKAS, Le CHANG, Harpreet Singh MIGLANI, Phillip Isaac BEISH, Dylan Thomas NUNLEY
  • Publication number: 20230106021
    Abstract: A method of and system for customizing a rollout process of application features includes providing a list of one or more application features for display on a user interface screen, the software application features being application features that are scheduled for a staged rollout, enabling selection of one of the application features for enrolling in late-stage rollout or opting out of the staged rollout, receiving a request for enrolling a user entity in late-stage rollout or opting the user entity out of the staged rollout, storing a property associated with the user entity in a data store, the property indicative of the user entity enrolling in late-stage rollout or opting out of the staged rollout, accessing the stored property, when selecting a plurality of enterprises or users for the staged rollout of the application feature, and depending on the accessed property, selecting the user entity for late-stage rollout or not selecting the user entity for the staged rollout.
    Type: Application
    Filed: September 29, 2021
    Publication date: April 6, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Nidhi VERMA, Divyachapan Sridharan PADUR, Zohar RAZ
  • Patent number: 11616882
    Abstract: Traditionally, when a feature is updated or a new feature is released, the feature undergoes internal testing and validation before external distribution. However, some features may receive proportionately less internal usage than customer usage reflected externally. Low internal usage of features can lead to weak telemetry data, which can allow code regressions (e.g., bugs) to go undetected until the features are released to customers. Accordingly, accelerated internal feature usage is provided to mirror external customer usage. Highly used features are dynamically identified and, any deficiencies in internal feature usage are identified. Tenant sites estimated to generate at least a portion of the deficiency in feature usage are identified. These sites may be migrated or replicated to internal validation rings to generate additional internal feature usage.
    Type: Grant
    Filed: May 22, 2020
    Date of Patent: March 28, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Nidhi Verma, Andrei Nicolae, Rahul Nigam, Parminder Pal Singh
  • Publication number: 20230067057
    Abstract: The techniques disclosed herein enable systems to safely deploy a plurality of upgrade variants to different resource units that provide a service by utilizing small-scale deployment and validation. To deploy upgrade variants, a system receives a selection of upgrade variants from a feature group and automatically selects an appropriate set of resource units at which to deploy the upgrade variants. The system is further configured to collect and analyze telemetry data from the set of resource units to determine if any problems have occurred as a result of the deployed upgrade variants. By analyzing the telemetry data, the system can also identify one or more upgrade variants that are causing the problems. In response, the system can remove the identified variants and proceed with deployment of the remaining upgrade variants.
    Type: Application
    Filed: August 31, 2021
    Publication date: March 2, 2023
    Inventors: Nidhi Verma, Hans Christian Andersen, Pritvinath Obla, Daniel Oh, Rahul Nigam, Rohan Khanna
  • Publication number: 20220385535
    Abstract: Technologies are disclosed for improving the deployment of a cloud-hosted service. Before being deployed to a particular environment, a cloud-hosted service must be configured for that environment. Configuring a deployment includes determining which components to deploy, determining how to connect with external components, identifying onboarding procedures, etc. A dependency data model defines a hierarchy of components utilized by the cloud-hosted service. For each component in the hierarchy, configuration parameters define how to deploy that component. A list of configuration parameters that do not yet have values for a target environment may be generated and provided to a user. Values for these parameters may then be received. A configuration for the target environment is then generated based on the dependency data model and the received values. The dependency data model may inherit dependencies and configuration properties from ancestors in a hierarchy of dependency data models.
    Type: Application
    Filed: May 27, 2021
    Publication date: December 1, 2022
    Inventors: Nidhi VERMA, Roberta CANNEROZZI, Erik WAHLSTROM, Le CHANG
  • Publication number: 20220350509
    Abstract: Disclosed herein is a system for improving the user experience in the face of a regression by returning resources that offer a service to a “last known good” upgrade. In other words, the state of the resources is reconfigured to scale back from recent upgrade(s), the deployments of which likely caused the regression, to a previous upgrade that is known to have little or no effect on the user experience. To identify a problem, the system collects performance data from different resource units that make up a cloud-based platform. The performance data is collected for each upgrade event in a sequence of upgrade events that are currently deployed or being deployed. The system continually tracks and analyzes qualification data collected for each of the deployed upgrade events. The system can tag an upgrade event as the last known good upgrade event when the collected qualification data satisfies predefined qualifications.
    Type: Application
    Filed: April 28, 2021
    Publication date: November 3, 2022
    Inventors: Nidhi VERMA, Daniel OH, Amber LITTEKEN, Rahul NIGAM
  • Patent number: 11354113
    Abstract: The techniques disclosed herein enable systems to deploy upgrade events in a controlled manner to different resource units that provide a service utilizing predefined rollout policies. To deploy an upgrade event, a system determines a risk factor for the upgrade event and presents predefined rollout policies to a feature group for selection based on the risk factor. Upon selection of a rollout policy, the system can deploy the upgrade event according to parameters defined by the selected rollout policy. The system is further configured to analyze telemetry data received from the resource units to determine an updated risk factor and determine whether the updated risk factor crosses a risk factor threshold. If the updated risk factor crosses the threshold, the system can identify another rollout policy to replace the selected policy. In addition, the system can receive an override workflow request to expedite upgrade event deployment.
    Type: Grant
    Filed: January 14, 2021
    Date of Patent: June 7, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Nidhi Verma, Ankur Jauhari, Min Shao, Sudharsan Ganesan, Shobana Krishnamoorthy, Rahul Nigam, Roberta Cannerozzi