Patents by Inventor Julie Dallen
Julie Dallen 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).
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Patent number: 11966324Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: June 6, 2022Date of Patent: April 23, 2024Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Publication number: 20240086872Abstract: Methods, systems, devices, and computer-readable media for detecting multi-party events and transactions are provided. User data may be monitored to detect data associated with an event involving multiple individuals, such as by identifying transaction data associated with certain types of merchants and/or scheduling, calendar, or correspondence data indicative of an event. The data may be further analyzed to identify a date, location, and/or parties associated with the event. A multi-party event may be generated. The user data may continue to be monitored to identify transactions associated with multiple parties and occurring during a time and/or at a location of the event. At a conclusion of the event, the transactions may be aggregated and an optimal payment scheme may be determined for settlement of the transactions between the parties. In accordance with the determined payment scheme, delegation of portions of the aggregated transactions may be initiated for settlement amongst the parties.Type: ApplicationFiled: November 22, 2023Publication date: March 14, 2024Inventors: Vijay Sahebgouda Bantanur, Muralidharan Balasubramanian, Julie Dallen
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Patent number: 11868973Abstract: Methods, systems, devices, and computer-readable media for detecting multi-party events and transactions are provided. User data may be monitored to detect data associated with an event involving multiple individuals, such as by identifying transaction data associated with certain types of merchants and/or scheduling, calendar, or correspondence data indicative of an event. The data may be further analyzed to identify a date, location, and/or parties associated with the event. A multi-party event may be generated. The user data may continue to be monitored to identify transactions associated with multiple parties and occurring during a time and/or at a location of the event. At a conclusion of the event, the transactions may be aggregated and an optimal payment scheme may be determined for settlement of the transactions between the parties. In accordance with the determined payment scheme, delegation of portions of the aggregated transactions may be initiated for settlement amongst the parties.Type: GrantFiled: August 19, 2021Date of Patent: January 9, 2024Assignee: Capital One Services, LLCInventors: Vijay Sahebgouda Bantanur, Muralidharan Balasubramanian, Julie Dallen
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Patent number: 11868237Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: December 15, 2022Date of Patent: January 9, 2024Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Publication number: 20230401143Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: July 18, 2023Publication date: December 14, 2023Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Publication number: 20230401114Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: April 18, 2023Publication date: December 14, 2023Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Publication number: 20230267074Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: April 28, 2023Publication date: August 24, 2023Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Publication number: 20230251955Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: April 18, 2023Publication date: August 10, 2023Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Patent number: 11675692Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: August 12, 2021Date of Patent: June 13, 2023Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Patent number: 11663055Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: January 10, 2022Date of Patent: May 30, 2023Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Patent number: 11650909Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: September 16, 2020Date of Patent: May 16, 2023Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Publication number: 20230126113Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: December 15, 2022Publication date: April 27, 2023Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Patent number: 11620211Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: June 6, 2022Date of Patent: April 4, 2023Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Determining problem dependencies in application dependency discovery, reporting, and management tool
Patent number: 11614943Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: June 6, 2022Date of Patent: March 28, 2023Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson -
Publication number: 20230067467Abstract: Methods, systems, devices, and computer-readable media for a multi-party transaction decisioning system are provided. The system may analyze a purchase transaction associated with a first user and may identify that the transaction is associated with more than one party based on determining that an amount of the transaction is atypical for the first user. The system may identify a party associated with the multi-party transaction based on analyzing data associated with the first user. The system may generate a delegation request for a portion of the amount of the multi-party transaction to be delegated to the identified party and may transmit the delegation request to the identified party. Subsequently, the system may receive a payment transaction from the identified party, and the system may identify that the payment transaction is associated with the previously transmitted delegation request.Type: ApplicationFiled: August 19, 2021Publication date: March 2, 2023Inventors: Vijay Sahebgouda Bantanur, Muralidharan Balasubramanian, Julie Dallen
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Publication number: 20230061296Abstract: Methods, systems, devices, and computer-readable media for detecting multi-party events and transactions are provided. User data may be monitored to detect data associated with an event involving multiple individuals, such as by identifying transaction data associated with certain types of merchants and/or scheduling, calendar, or correspondence data indicative of an event. The data may be further analyzed to identify a date, location, and/or parties associated with the event. A multi-party event may be generated. The user data may continue to be monitored to identify transactions associated with multiple parties and occurring during a time and/or at a location of the event. At a conclusion of the event, the transactions may be aggregated and an optimal payment scheme may be determined for settlement of the transactions between the parties. In accordance with the determined payment scheme, delegation of portions of the aggregated transactions may be initiated for settlement amongst the parties.Type: ApplicationFiled: August 19, 2021Publication date: March 2, 2023Inventors: Vijay Sahebgouda Bantanur, Muralidharan Balasubramanian, Julie Dallen
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Patent number: 11556459Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: GrantFiled: February 22, 2021Date of Patent: January 17, 2023Assignee: Capital One Services, LLCInventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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DETERMINING PROBLEM DEPENDENCIES IN APPLICATION DEPENDENCY DISCOVERY, REPORTING, AND MANAGEMENT TOOL
Publication number: 20220300290Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: June 6, 2022Publication date: September 22, 2022Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson -
Publication number: 20220300397Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: June 6, 2022Publication date: September 22, 2022Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson
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Publication number: 20220300398Abstract: Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls.Type: ApplicationFiled: June 6, 2022Publication date: September 22, 2022Inventors: Muralidharan Balasubramanian, Eric K. Barnum, Julie Dallen, David Watson