公开(公告)号：US11503081B1

公开(公告)日：2022-11-15

申请号：US16786868

申请日：2020-02-10

Applicant: Amazon Technologies, Inc.

Inventor： Sriram Venugopal ,  Gary Michael Herndon

IPC: H04L29/06 ,  G06F3/06 ,  G06F9/50 ,  H04L9/40

Abstract: Systems and methods are described for implementing load-dependent encryption mechanism selection in an elastic computing system. The elastic computing system can include a set of host devices configured to implement block storage volumes on behalf of users. Users may desire that such volumes be encrypted prior to storing data. It may be generally preferable for encryption to occur on the same host devices that host the volume, to reduce latency and bandwidth usage needed to encrypt the data. However, encryption of data can utilize significant computational resources, which may not be available on host devices that also have sufficient storage resources to host the volume. The present disclosure describes systems and methods that can account for computational resource availability on host devices, selecting “in-place” encryption only when available resources exist on host devices, and otherwise implementing remote encryption of volume data.

公开(公告)号：US11048554B1

公开(公告)日：2021-06-29

申请号：US16366868

申请日：2019-03-27

Applicant: Amazon Technologies, Inc.

Inventor： Patrick E. Brennan ,  Mitchell Flaherty ,  Christopher Magee Greenwood ,  Wells Lin ,  Sriram Venugopal ,  Linfeng Yu ,  Yilin Guo ,  Alexander R. Yee ,  Gary Michael Herndon

IPC: G06F9/38 ,  G06F9/54 ,  G06F17/15 ,  G06F9/50 ,  H04L29/08

Abstract: Systems and methods are disclosed for handling requests to create multiple volumes with an expected usage correlation on a block storage service. Rather than handling each request to create a volume independently, embodiments described herein can handle the request in bulk. In one embodiment, the service allows for oversubscription of use on hosts, as well as parallelization of placement decisions, by distributing requests among a set of parallelized placement engines. Each engine can distribute its subset of volumes at least partly randomly among a candidate set of volumes, with the size of the candidate set selected based on a total number of volumes. This distribution mechanism can ensure distribution of volumes without requiring centralized placement of the volumes.

公开(公告)号：US11080092B1

公开(公告)日：2021-08-03

申请号：US16366836

申请日：2019-03-27

Applicant: Amazon Technologies, Inc.

Inventor： Yilin Guo ,  Christopher Magee Greenwood ,  Mitchell Flaherty ,  Sriram Venugopal ,  Wells Lin ,  Patrick E. Brennan ,  Linfeng Yu ,  Alexander R. Yee ,  Gary Michael Herndon

IPC: G06F9/46 ,  G06F9/50 ,  G06F9/54 ,  H04L29/08 ,  G06F9/38 ,  G06F17/15

Abstract: Systems and methods are disclosed for handling requests to create multiple volumes with an expected usage correlation on a block storage service. Rather than handling each request to create a volume independently, embodiments described herein can handle the request in bulk, quickly determining whether the request as a whole can be handled at the system. In one embodiment, the service allows for oversubscription of use on hosts, as well as parallelization of placement decisions, by rejecting placement requests when a number of possible hosts for a volume within a requested set falls below a candidate set size, which is determined based on factors such as a number of requested volumes and an expected accuracy of state information for the service at a placement engine within a distributed set of engines.

公开(公告)号：US20190265915A1

公开(公告)日：2019-08-29

申请号：US16410040

申请日：2019-05-13

Applicant: Amazon Technologies, Inc.

Inventor： Christopher Magee Greenwood ,  Gary Michael Herndon

IPC: G06F3/06

Abstract: Data volumes for a customer can be placed on various storage tiers, including different hardware types or storage systems, that are determined to be appropriate for the anticipated usage of those data volumes. The actual usage can be monitored to determine one or more types of workload for the data volume, and a determination made as to whether all, or portions, of the data volume could obtain a significant performance improvement by being migrated to a different storage tier. In some instances the chunks or partitions of a volume can be concurrently distributed across multiple different storage tiers in order to satisfy various performance and/or cost criteria. Once workload information is available for a customer, that information can be used to determine the storage tiers for initial placement of subsequent data volumes.