Patents by Inventor Muhammad Khizar QAZI

Muhammad Khizar QAZI 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).

  • NODE HEALTH PREDICTION BASED ON FAILURE ISSUES EXPERIENCED PRIOR TO DEPLOYMENT IN A CLOUD COMPUTING SYSTEM
    Publication number: 20230239194
    Abstract: To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.
    Type: Application
    Filed: January 26, 2023
    Publication date: July 27, 2023
    Inventors: Sanjay RAMANUJAN, Luke Rafael RODRIGUEZ, Muhammad Khizar QAZI, Aleksandr Mikhailovich GERSHAFT, Marwan Elias JUBRAN, Saurabh AGARWAL
  • Node health prediction based on failure issues experienced prior to deployment in a cloud computing system
    Patent number: 11582087
    Abstract: To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.
    Type: Grant
    Filed: December 17, 2019
    Date of Patent: February 14, 2023
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Sanjay Ramanujan, Luke Rafael Rodriguez, Muhammad Khizar Qazi, Aleksandr Mikhailovich Gershaft, Marwan Elias Jubran, Saurabh Agarwal
  • NODE HEALTH PREDICTION BASED ON FAILURE ISSUES EXPERIENCED PRIOR TO DEPLOYMENT IN A CLOUD COMPUTING SYSTEM
    Publication number: 20210184916
    Abstract: To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.
    Type: Application
    Filed: December 17, 2019
    Publication date: June 17, 2021
    Inventors: Sanjay RAMANUJAN, Luke Rafael RODRIGUEZ, Muhammad Khizar QAZI, Aleksandr Mikhailovich GERSHAFT, Marwan Elias JUBRAN, Saurabh AGARWAL