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公开(公告)号:US20160344651A1
公开(公告)日:2016-11-24
申请号:US15231398
申请日:2016-08-08
Applicant: Amazon Technologies, Inc.
Inventor: Norbert P. Kusters , Kerry Q. Lee , Raghav Vijay Pisolkar , Tate Andrew Certain
IPC: H04L12/923 , H04L12/24 , H04L29/08
Abstract: An opportunistic throttling approach can be used for customers of shared resources in a multi-tenant environment. Each customer can have a respective token bucket with a guaranteed fill rate. When a request is received for an amount of work to be performed by a resource, the corresponding number of tokens are obtained from, or charged against, a global token bucket. If the global bucket has enough tokens, and if the customer has not exceeded a maximum work rate or other such metric, the customer can charge less than the full number of tokens against the customer's token bucket, in order to reduce the number of tokens that need to be taken from the customer bucket. Such an approach can enable the customer to do more work and enable the customer's bucket to fill more quickly as fewer tokens are charged against the customer bucket for the same amount of work.
Abstract translation: 可以在多租户环境中为共享资源的客户使用机会主义的节制方法。 每个客户可以有一个具有保证填充率的相应令牌桶。 当接收到要由资源执行的工作量的请求时,相应数量的令牌从全局令牌桶中获取或收取。 如果全局桶具有足够的令牌,并且如果客户没有超过最大工作率或其他此类度量,则客户可以针对客户的令牌桶向所有的令牌收取少量令牌,以便减少令牌数量 需要从客户桶中取出。 这样一种方法可以使客户能够进行更多的工作,并使得客户的桶可以更快地填充,因为对于相同数量的工作,较少的令牌被针对客户桶收取。
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公开(公告)号:US09906598B1
公开(公告)日:2018-02-27
申请号:US15354904
申请日:2016-11-17
Applicant: Amazon Technologies, Inc.
Inventor: Marc J. Brooker , Madhuvanesh Parthasarathy , Tate Andrew Certain , Kerry Q. Lee
CPC classification number: H04L67/1097 , G06F3/061 , G06F3/0617 , G06F3/0662 , G06F3/067 , G06F9/45558 , G06F17/30194 , G06F17/30233 , G06F17/30283 , H04L67/02 , H04L67/32 , H04L67/42
Abstract: A storage controller is implemented for controlling a storage system. The storage controller may be implemented using a distributed computer system and may include components for servicing client data requests based on the characteristics of the distributed computer system, the client, or the data requests. The storage controller is scalable independently of the storage system it controls. All components of the storage controller, as well as the client, may be virtual or hardware-based instances of a distributed computer system.
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公开(公告)号:US09413680B1
公开(公告)日:2016-08-09
申请号:US13627278
申请日:2012-09-26
Applicant: Amazon Technologies, Inc.
Inventor: Norbert P. Kusters , Kerry Q. Lee , Raghav Vijay Pisolkar , Tate Andrew Certain
IPC: G06F15/173 , H04L12/923
CPC classification number: H04L47/762 , H04L12/1403 , H04L41/08 , H04L63/10 , H04L67/146 , H04L69/321 , H04L69/325 , H04M15/765 , H04M15/7652 , H04M15/7655 , H04M15/83 , H04M15/85 , H04M15/853 , H04M15/854
Abstract: An opportunistic throttling approach can be used for customers of shared resources in a multi-tenant environment. Each customer can have a respective token bucket with a guaranteed fill rate. When a request is received for an amount of work to be performed by a resource, the corresponding number of tokens are obtained from, or charged against, a global token bucket. If the global bucket has enough tokens, and if the customer has not exceeded a maximum work rate or other such metric, the customer can charge less than the full number of tokens against the customer's token bucket, in order to reduce the number of tokens that need to be taken from the customer bucket. Such an approach can enable the customer to do more work and enable the customer's bucket to fill more quickly as fewer tokens are charged against the customer bucket for the same amount of work.
Abstract translation: 可以在多租户环境中为共享资源的客户使用机会主义的节制方法。 每个客户可以有一个具有保证填充率的相应令牌桶。 当接收到要由资源执行的工作量的请求时,相应数量的令牌从全局令牌桶中获取或收取。 如果全局桶具有足够的令牌,并且如果客户没有超过最大工作率或其他此类度量,则客户可以针对客户的令牌桶收取少于令牌的全部令牌,以便减少令牌数量 需要从客户桶中取出。 这样一种方法可以使客户能够进行更多的工作,并使得客户的桶可以更快地填充,因为对于相同数量的工作,较少的令牌被针对客户桶收取。
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公开(公告)号:US09405815B1
公开(公告)日:2016-08-02
申请号:US13633612
申请日:2012-10-02
Applicant: Amazon Technologies, Inc.
Inventor: Danny Wei , Lakshmi N. Pallikila , James Andrew Trenton Lipscomb , Yan V. Leshinsky , Tarun Goyal , Kerry Q. Lee
CPC classification number: G06F17/30578
Abstract: A computing system recovers volumes in a distributed computing environment while reducing downtime of storage servers. In an embodiment, a storage server contacts a control plane after a storage failure has occurred. If the storage server hosts an authoritative copy of an offline volume, the storage server is requested to restore the volume. Non-authoritative volumes are removed from the storage server and the storage server provides read access to the restored volume while resuming storage services.
Abstract translation: 计算系统在分布式计算环境中恢复卷,同时减少存储服务器的停机时间。 在一个实施例中,存储服务器在发生存储故障之后接触控制平面。 如果存储服务器托管脱机卷的授权副本,则请求存储服务器还原卷。 非权威卷从存储服务器中删除,存储服务器在恢复存储服务时提供对已还原卷的读取访问。
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公开(公告)号:US11314444B1
公开(公告)日:2022-04-26
申请号:US14594965
申请日:2015-01-12
Applicant: Amazon Technologies, Inc.
Inventor: Marc J. Brooker , Madhuvanesh Parthasarathy , Tate Andrew Certain , Kerry Q. Lee
IPC: G06F16/11 , G06F16/182 , G06F16/176 , G06F16/185 , G06F16/188 , G06F16/21 , G06F3/06 , G06F21/62 , G06F16/13 , G06F16/27
Abstract: A storage controller is implemented for controlling a storage system. The storage controller may be implemented using a distributed computer system and may include components for servicing client data requests based on the characteristics of the distributed computer system, the client, or the data requests. The storage controller is scalable independently of the storage system it controls. All components of the storage controller, as well as the client, may be virtual or hardware-based instances of a distributed computer system.
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公开(公告)号:US09531809B1
公开(公告)日:2016-12-27
申请号:US14456979
申请日:2014-08-11
Applicant: Amazon Technologies, Inc.
Inventor: Marc J. Brooker , Madhuvanesh Parthasarathy , Tate Andrew Certain , Kerry Q. Lee
CPC classification number: H04L67/1097 , G06F3/061 , G06F3/0617 , G06F3/0662 , G06F3/067 , G06F9/45558 , G06F17/30194 , G06F17/30233 , G06F17/30283 , H04L67/02 , H04L67/32 , H04L67/42
Abstract: A storage controller is implemented for controlling a storage system. The storage controller may be implemented using a distributed computer system and may include components for servicing client data requests based on the characteristics of the distributed computer system, the client, or the data requests. The storage controller is scalable independently of the storage system it controls. All components of the storage controller, as well as the client, may be virtual or hardware-based instances of a distributed computer system.
Abstract translation: 实现存储控制器以控制存储系统。 可以使用分布式计算机系统来实现存储控制器,并且可以包括基于分布式计算机系统,客户机或数据请求的特性来服务客户端数据请求的组件。 存储控制器可独立于其控制的存储系统进行扩展。 存储控制器以及客户端的所有组件可以是分布式计算机系统的基于虚拟或基于硬件的实例。
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公开(公告)号:US10402377B1
公开(公告)日:2019-09-03
申请号:US15224444
申请日:2016-07-29
Applicant: Amazon Technologies, Inc.
Inventor: Danny Wei , Lakshmi N. Pallikila , James Andrew Trenton Lipscomb , Yan V. Leshinsky , Tarun Goyal , Kerry Q. Lee
IPC: G06F16/182 , G06F16/27 , G06F16/11 , G06F11/14
Abstract: A computing system recovers volumes in a distributed computing environment while reducing downtime of storage servers. In an embodiment, a storage server contacts a control plane after a storage failure has occurred. If the storage server hosts an authoritative copy of an offline volume, the storage server is requested to restore the volume. Non-authoritative volumes are removed from the storage server and the storage server provides read access to the restored volume while resuming storage services.
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公开(公告)号:US10366010B1
公开(公告)日:2019-07-30
申请号:US14957474
申请日:2015-12-02
Applicant: Amazon Technologies, Inc.
Inventor: Anand S. Gupta , Kerry Q. Lee , Varun Marupadi
IPC: G06F12/0888 , G06F12/06 , G06F3/06
Abstract: A caching system and methodology for data in a memory for faster access to commonly-used data by other applications and computer devices on a network. The memory can include a solid-state drive (SSD) array for the cache memory that has read-bias, in addition to a magnetic hard drive array. The system uses a logical set of slots to hold identifiers for specific groups of data that can be placed into cache memory and each identifier has a usage attribute that changes based upon the usage of the specific group of data and causes the identifier to move within the set of slots and potentially into cache memory.
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