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1.发明授权公开(公告)号：US11128696B2
公开(公告)日：2021-09-21
申请号：US16367914
申请日：2019-03-28
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , Leslie Johann Lamprecht , John Merrill Phillips , Umesh Chandani , Roberto Pentz De Faria , Hou Liu , Ladan Mahabadi , Letian Feng
Abstract: Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
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公开(公告)号：US11068312B2
公开(公告)日：2021-07-20
申请号：US16368072
申请日：2019-03-28
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , Leslie Johann Lamprecht , John Merrill Phillips , Umesh Chandani , Roberto Pentz De Faria , Hou Liu , Ladan Mahabadi , Letian Feng
Abstract: Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
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公开(公告)号：US11941454B1
公开(公告)日：2024-03-26
申请号：US17115617
申请日：2020-12-08
Applicant: Amazon Technologies, Inc.
Inventor： Mohit Gupta , Letian Feng , Leslie Johann Lamprecht
CPC classification number: G06F9/5077 , G06F9/45533 , G06F9/5011 , G06F9/5044 , G06F3/0604 , G06F3/064 , G06F3/067 , G06F2009/45579 , G06F9/50 , G06F9/5027
Abstract: Features are disclosed for correlating a workload type with particular volume characteristics for a block storage volume. The volume characteristics may include a durability or a performance consistency for a particular volume. A computing device can obtain a set of workload parameters indicating a workload associated with a particular block storage volume. Based on the set of workload parameters, the computing device can determine a workload classification that links the set of workload parameters to a set of volume characteristics. The computing device can further compare the set of volume characteristics with the current set of volume characteristics for the block storage volume. Based on comparing the sets of volume characteristics, the computing device may determine a recommendation for a user. The computing device can dynamically modify the block storage volume based on the recommendation.
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公开(公告)号：US11360795B2
公开(公告)日：2022-06-14
申请号：US16367768
申请日：2019-03-28
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , Leslie Johann Lamprecht , John Merrill Phillips , Umesh Chandani , Roberto Pentz De Faria , Hou Liu , Ladan Mahabadi , Letian Feng
Abstract: Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
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公开(公告)号：US11138049B1
公开(公告)日：2021-10-05
申请号：US16449949
申请日：2019-06-24
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , John Merrill Phillips , Leslie Johann Lamprecht , Roberto Pentz De Faria , Hou Liu , Umesh Chandani , Ladan Mahabadi , Letian Feng
Abstract: Techniques for an optimization service of a service provider network to provide users with machine-generated narratives that include human-intelligible, credible, and transparent recommendations and rationales for recommended VM instance types. The optimization service may gather various information or data about the workload, such as utilization characteristics of the underlying computing resources, and decompose the workloads through a number of dimensions that can be used to describe the workload. Further, the optimization service may analyze the utilization characteristics and/or other data to determine more optimized VM instance types for the workloads that are to be recommended to the users, and also rationales that describes why each recommendation is an appropriate fit for the workload being assessed. Using this information, the optimization service may generate narratives that include a description of the workload behaviors and utilization patterns, a set of recommendations, and supporting narrative or rationales for each of the recommendations.
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Patent Agency Ranking
6.发明授权公开(公告)号：US12135980B2
公开(公告)日：2024-11-05
申请号：US17861795
申请日：2022-07-11
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , Leslie Johann Lamprecht , John Merrill Phillips , Umesh Chandani , Roberto Pentz De Faria , Hou Liu , Ladan Mahabadi , Letian Feng
Abstract: Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
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公开(公告)号：US12045664B1
公开(公告)日：2024-07-23
申请号：US17206562
申请日：2021-03-19
Applicant: Amazon Technologies, Inc.
Inventor： Siyu Wang , Chia-Yu Kao , Leslie Johann Lamprecht , Qijia Chen , Letian Feng
CPC classification number: G06F9/5077 , G06F9/45558 , G06F2009/4557 , G06F2009/45595
Abstract: Techniques for a cloud-based workload optimization service to identify customer workloads that are optimized to run on burstable instance types. The techniques include identifying workloads that are successfully running on burstable instance types, and using historical-utilization data for those workloads to train classification models. The optimization service can extract feature data from the historical-utilization data, where the feature data represents utilization characteristics that are indicative of burstable workloads. The feature data is then used to train classification models to receive utilization data for candidate workloads, and determine whether the candidate workloads would be optimized for burstable instance types. The optimization service can then migrate suitable workloads to burstable instance types, and/or provide users with recommendations that their workloads are optimized or suitable for burstable instance types.
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公开(公告)号：US11194688B1
公开(公告)日：2021-12-07
申请号：US16406354
申请日：2019-05-08
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , Jacob Adam Gabrielson , Kai Fan Tang , John Merrill Phillips , Leslie Johann Lamprecht , Letian Feng , Roberto Pentz De Faria
Abstract: Techniques for an optimization service of a service provider network to generate an architecture diagram that represents an architecture of a web-based application. The optimization service may use the architecture diagram to determine modifications or changes to make to the application. For example, the optimization service may compare the architecture diagram with optimized architecture diagrams that represent application best practices, and determine the modifications or change to make to the application to optimize the application and bring the application in-line with best practices. Further, the optimization service may use the architecture diagram to generate a visualization, and provide the user account with the visualization of the architecture diagram to show users their application architecture.
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9.发明申请公开(公告)号：US20200310876A1
公开(公告)日：2020-10-01
申请号：US16368072
申请日：2019-03-28
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , Leslie Johann Lamprecht , John Merrill Phillips , Umesh Chandani , Roberto Pentz De Faria , Hou Liu , Ladan Mahabadi , Letian Feng
Abstract: Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
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公开(公告)号：US20200310851A1
公开(公告)日：2020-10-01
申请号：US16367768
申请日：2019-03-28
Applicant: Amazon Technologies, Inc.
Inventor： Malcolm Featonby , Leslie Johann Lamprecht , John Merrill Phillips , Umesh Chandani , Roberto Pentz De Faria , Hou Liu , Ladan Mahabadi , Letian Feng
Abstract: Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
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