Alyssa R Henry, Age 34Seattle, WA

8396840, Mar 12, 2013

Sep 22, 2010

12/888356

Jason G. McHugh - Seattle WA, US
Eric Yves Theriault - Seattle WA, US
Seth W. Markle - Seattle WA, US
Michael A. Uhlar - Sammamish WA, US
Alyssa H. Henry - Seattle WA, US

Amazon Technologies, Inc. - Reno NV

G06F 17/30

707690, 707689

Embodiments may include a consistency measurement component that utilizes memory-efficient sets (e. g. , Bloom filters) to generate consistency metrics for read operations performed on different replicated data objects of distributed storage system. Based on the consistency metrics, the consistency measurement component may identify a subset of replicated data objects associated with low levels of consistency. The consistency measurement component may target this subset for consistency improvement by generating instructions to improve the consistency of the subset. In other cases, the consistency measurement component may notify a consistency improvement component about the targeted subset. In response, the consistency improvement component may generate instructions to improve the consistency of the targeted subset.

2007005, Mar 8, 2007

Feb 28, 2006

11/364060

Michael Pizzo - Bellevue WA, US
Chris Suver - Seattle WA, US
Pablo Castro - Bellevue WA, US
Alyssa Henry - Sammamish WA, US
Andrew Conrad - Sammamish WA, US
Subramanian Muralidhar - Bellevue WA, US
Benjamin Albahari - Seattle WA, US
Jose Blakeley - Redmond WA, US

Microsoft Corporation - Redmond WA

G06F 7/00

70710300R

The claimed subject matter relates to an architecture that can facilitate an incremental approach to an Object-Relational mapping solution. The architecture can provide a rich data model that is defined at the value layer. The rich data model can expose an interface that conforms with the interfaces exposed by common storage-specific data providers. The architecture can extend common storage-specific data provider to support common command representations, and provide entity services that work in terms of the rich data model as well as object services such as identity management, updating and change tracking.

2014004, Feb 13, 2014

Aug 8, 2012

13/570088

Kestutis Patiejunas - Sammamish WA, US
James R. Hamilton - Seattle WA, US
Colin L. Lazier - Seattle WA, US
Alyssa H. Henry - Seattle WA, US
Mark C. Seigle - Seattle WA, US
Christian L. Claiborn - Seattle WA, US

G06F 17/30

707687

A cost-effective, durable and scalable archival data storage system is provided herein that allow customers to store, retrieve and delete archival data objects, among other operations. For data storage, in an embodiment, the system stores data in a transient data store and provides a data object identifier may be used by subsequent requests. For data retrieval, in an embodiment, the system creates a job corresponding to the data retrieval and provides a job identifier associated with the created job. Once the job is executed, data retrieved is provided in a transient data store to enable customer download. In various embodiments, jobs associated with storage, retrieval and deletion are scheduled and executed using various optimization techniques such as load balancing, batch processed and partitioning. Data is redundantly encoded and stored in self-describing storage entities increasing reliability while reducing storage costs. Data integrity is ensured by integrity checks along data paths.

2014032, Oct 30, 2014

Apr 25, 2013

13/870772

AMAZON TECHNOLOGIES, INC. - RENO NV, US
ALYSSA H. HENRY - SEATTLE WA, US

AMAZON TECHNOLOGIES, INC. - RENO NV

G06F 17/30

707812

A method for grouping and storing objects across different storage solutions in storage systems according to analysis of multiple dimensions of information may be implemented as or in a storage management module. The module collects information about objects (e.g., data objects) in a storage system (e.g., a data storage system). The objects may be objects already stored in the storage system or may be new objects to be stored in the storage system. The module analyzes the collected information across multiple dimensions to determine groupings of the objects, and determines a storage solution for each determined grouping. The module may then direct storage of the objects in the groupings according to the determined storage solutions. Upon obtaining new information about object(s) in the storage system, the module may direct movement of the object(s) from one storage solution to another storage solution according to an analysis including the new information.