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公开(公告)号:US20230214306A1
公开(公告)日:2023-07-06
申请号:US17565815
申请日:2021-12-30
Applicant: Microsoft Technology Licensing, LLC
Inventor: Zi YE , Justin Grant MOELLER , Ya LIN , Willis LANG
CPC classification number: G06F11/3433 , G06F16/27 , G06F16/217 , G06F11/3457 , G06F11/3006
Abstract: Methods, systems, and computer program products are provided for creating a resource management testing environment. An initial population of databases is established in a database ring, having an in initial count of databases and different types of databases that are determined based on an initial database population model. The initial population model receives ring classification information for the database ring from a ring grouping model. A sequence of database population-change events is generated based on a model, to change the population of the databases over time in the ring. An orchestration framework performs testing of resource manager operations based on the model-defined initial population of databases and the model-defined populations of databases changed over time. Model-defined resource usage metrics for each database are utilized to test the resource manager operations. Resource usage metrics and database add/drop events of a production system are used to train the models.
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公开(公告)号:US20240036964A1
公开(公告)日:2024-02-01
申请号:US17878375
申请日:2022-08-01
Applicant: Microsoft Technology Licensing, LLC
Inventor: Wenjing WANG , Youquan SU , Zi YE , Ya LIN , Shirley F. TAN , Ashwin SHRINIVAS , Mathieu Baptiste DEMARNE , Grant R. CULBERTSON , Yvonne MCKAY , Thomas R. MICHAELS, JR. , Barton K. DUNCAN , Zhirui YUAN
IPC: G06F11/07
CPC classification number: G06F11/079 , G06F11/0784 , G06F11/076
Abstract: A computing system automatically manages error reports. Each error report specifies an error that occurred within a subsystem of the computing system. A received error report is added into a root cause grouping. Each root cause grouping contains error reports having error types traceable to a same root cause. A deployment time at which the subsystem corresponding to the error report was deployed within the computing system is determined. A severity score for the root cause grouping is generated as a function of the deployment time. The severity score inversely correlates to a time period length between the deployment time and the occurrence time of the error. The root cause grouping is assigned to a ranked error container of a plurality of ranked error containers based on the generated severity score. Each ranked error container contains root cause groupings having severity scores within a specified score range.
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公开(公告)号:US20240103994A1
公开(公告)日:2024-03-28
申请号:US18530914
申请日:2023-12-06
Applicant: Microsoft Technology Licensing, LLC
Inventor: Zi YE , Justin Grant MOELLER , Ya LIN , Willis LANG
CPC classification number: G06F11/3433 , G06F11/3006 , G06F11/3457 , G06F16/217 , G06F16/27
Abstract: Methods, systems, and computer program products are provided for creating a resource management testing environment. An initial population of databases is established in a database ring, having an in initial count of databases and different types of databases that are determined based on an initial database population model. The initial population model receives ring classification information for the database ring from a ring grouping model. A sequence of database population-change events is generated based on a model, to change the population of the databases over time in the ring. An orchestration framework performs testing of resource manager operations based on the model-defined initial population of databases and the model-defined populations of databases changed over time. Model-defined resource usage metrics for each database are utilized to test the resource manager operations. Resource usage metrics and database add/drop events of a production system are used to train the models.
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公开(公告)号:US20230029888A1
公开(公告)日:2023-02-02
申请号:US17556781
申请日:2021-12-20
Applicant: Microsoft Technology Licensing, LLC
Inventor: Wenjing WANG , Joyce Yu CAHOON , Yiwen ZHU , Ya LIN , Subramaniam Venkatraman KRISHNAN , Neetu SINGH , Raymond TRUONG , XingYu LIU , Maria Alexandra CIORTEA , Sreraman NARASIMHAN , Pratyush RAWAT , Haitao SONG
Abstract: Methods, systems, apparatuses, and computer-readable storage mediums described herein are directed to determining and recommending an optimal compute resource configuration for a cloud-based resource (e.g., a server, a virtual machine, etc.) for migrating a customer to the cloud. The embodiments described herein utilize a statistically robust approach that makes recommendations that are more flexible (elastic) and account for the full distribution of the amount of resource usage. Such an approach is utilized to develop a personalized rank of relevant recommendations to a customer. To determine which compute resource configuration to recommend to the customer, the customer’s usage profile is matched to a set of customers that have already migrated to the cloud. The compute resource configuration that reaches the performance most similar to the performance of the configurations utilized by customers in the matched set is recommended to the user.
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