Amazon Technologies, Inc.

Colin Laird Lazier

Bryan James Donlan

Kestutis Patiejunas

Paul David Franklin

Mark Christopher Seigle

James Christopher Sorenson

James Caleb Kirschner

Christian L Claiborn

Marco Argenti

Adam Frederick Brock

Jeremiah David Brazeau

Ryan Justin Snodgrass

James Raymond Allard

William J Vass

David Levy

Samuel Rubin Barrett

Brent James Lutz

Jeffrey Allen Dzado

Paul G Nordstrom

Claire Elizabeth Suver

Andrew Brenden Tinka

Brian J Deen

Marcin Piotr Kowalski

Atle Normann Jorgensen

Seth William Markle

Matteo Frigo

Leon Thrane

Masataka Kubo

Claire E Suver Weir

Stefano Stefani

James Robert Hamilton

Akshat Vig

Yosseff Levanoni

Frank Charles Paterra

Somasundaram Perianayagam

Maximiliano Maccanti

Kamran Tirdad

Alyssa H Henry

Jeffrey Arthur Johnson

Evelina Colleen Babcock

Weixiang Sun

Andrew Brendan Tinka

Claire E Suver

James Christopher Sorenson Iii

An application programming interface for a data storage service provides a convenient mechanism for clients of the data storage service to access its various capabilities. An API call may be made to initiate a job and in response a job identifier may be provided. A separate API call specifying the job identifier may be made and a response providing information related to the job may result. Various API calls may be used to store data, retrieve data, obtain an inventory of stored data, and to obtain other information relating to stored data.

Data storage application programming interface

A system receives a request to retrieve a data object from a data storage device associated with an asynchronous-access data storage service. For data object retrieval, the system identifies the data storage device and creates a job corresponding to the data object retrieval. Once the job is executed, the data object is retrieved to satisfy the request without having to restore the data object and further provided to a data storage device associated with a synchronous-access data storage service to satisfy subsequent requests synchronously.

Synchronous get copy for asynchronous storage

A database system may associate functions with a database table. A request to associate a function with a table in a database system may be received. An association between the table and the function may be created. The function may include parameters that are determined from values within the table which are then invoked by a request to perform the function. The associated function may cause the collection of the values prior to performance of the function.

Associating a function with a table in a database system

A network-attachable data transfer device housed within a shippable enclosure that incorporates an updateable electronic display for displaying shipping destination information is disclosed. The device may be initialized (e.g., prepared to receive data, and the updateable electronic shipping display set to the shipping destination) by a service provider and shipped, in accordance with the displayed destination address, as a self-contained shipping unit. The device may be installed onto a network at the destination and loaded with data. The display may also be updated with the next destination address such that the device is shipped to the updated destination address (e.g., back to the service provider, or onto other destinations before being send back to the service provider). When the device is received back at the service provider, the data is transferred from the device to a service provider storage facility, wiped of data, and prepared to be sent out again.

Shippable network-attached data storage device with updateable electronic display

A system stores data, such as sensor data or other operational data, on a plurality of storage volumes in a sequence so as to allow for interpolations or other approximations of the data using a subset of the storage volumes in response to a request for information regarding that data. For example, a plurality of devices connect to the system to provide operational data, which is then stored in a specified sequence on a specified set of volumes. In response to a request for operational information regarding some or all of the devices, the system reads at least one of the volumes, and approximates the values of the data over a specified period of time. In some embodiments, the data may be buffered prior to storage, and a jitter analyzer determines whether the incoming data is anomalous relative to a baseline, which may be determined using related data sets.

Techniques and systems for storage and processing of operational data

A hub device or edge device implements adaptive data compression. The model training service analyzes the received data. A machine learning model of the hub device receives time-series data from one or more data sources and classifies respective portions of the time-series data as respective patterns. A data compressor at the hub device generates compressed data by applying different compression techniques to the respective portions of the time-series data according to a mapping of the compression techniques to the respective patterns. The hub device then transmits the compressed data to an endpoint for processing (e.g., another device that uses the compressed data). The hub device receives feedback for the compressed data. In response to the feedback, the hub device changes one or more of the compression techniques that are mapped to the respective patterns.

Using feedback for adaptive data compression

A device such as a network-attachable data transfer device may be configured to operate in a cluster to coordinate the storage of data. A first manifest may be generated inventorying a first set of data successfully transferred to the data transfer device from a data source. A second manifest may be generated inventorying a second set of data successfully transferred from the data transfer device to a data destination. The first manifest may be compared with the second manifest to determine a transfer status of one or more data objects. The transfer status may indicate one or more data objects successfully transferred to the data destination from the data source. The one or more objects may be processed according to the transfer status.

Migration of information via storage devices

Techniques for encrypting data using a randomly selected data block from a set of data are described herein. An index indicates a subset of data within a data object. The data block is selected based at least in part on the index, an input to a cryptographic operation is generated from the data block, and the input to the cryptographic operation is provided to the cryptographic operation.

Encryption using indexed data from large data pads

A data transfer device is used to augment the capabilities of a data storage system. The data transfer device may be capable of persistently storing data for an indeterminate amount of time, and may be configured to store a portion of a bundle of redundancy coded shards that span between the data transfer device and a data storage system configured to store the remainder of the bundle. Data stored on the data transfer device may be read from and written directly to the data transfer device without transfer of data to the data storage system. If the data transfer device is not available, the remaining shards of the bundle may provide a regenerated, original form of the data.

Local storage clustering for redundancy coded data storage system

Techniques and methods for generating and implementing multiple layers of redundancy coded data are disclosed. For example, a redundancy coding scheme may include data elements that include data that is unencoded relative to the input, yet may still fully participate in providing redundancy to any data element in a given set. In a layered scheme, the input may include a bundle or group of encoded (or unencoded) data elements, thereby nesting two or more layers of redundancy coding. The specific amount of redundancy generated by such a scheme may be adjusted and adapted to failure characteristics of the entity on which the data elements are stored.

Adaptive data loss mitigation for redundancy coding systems

In response to receiving a request from a client to store an object, a key-durable storage system may assign the object to a volume in its data store, generate a key for the object (e.g., an opaque identifier that encodes information for locating the object in the data store), store the object on one disk in the assigned volume, store the key redundantly in the assigned volume (e.g., using a replication or erasure coding technique), and may return the key to the client. To retrieve the object, the client may send a request including the key, and the system may return the object to the client. If a disk fails, the system may determine which objects were lost, and may return the corresponding keys to the appropriate clients in a notification. The system may be used to back up a more expensive object-redundant storage system.

Object loss reporting in a data storage system

Migration techniques are described. In an example, a computing system sends instructions associated with operational computing hardware to a client device. The instructions are sent based on a client request for relocating the operational computing hardware from a client location. This hardware is configured to provide client compute operations and store client data. The computing system provisions a private network within a data center of a provider. Based on an arrival of the portable enclosure with the operational computing hardware from the client location to a provider location associated with the data center, the computing system establishes a network connection between the private network and the operational computing hardware stored in the portable enclosure. The computing system provides remote access to the operational computing hardware via the private network based at least in part on the network connection.

Migration of operational computing hardware to a data center

Techniques and systems for storing and retrieving data storage devices of a data storage system are disclosed. In some embodiments, inventory holders are used to store data storage devices used by a data storage system. When data is to be transacted with the data storage devices, mobile drive units locate appropriate inventory holders and transport them to a device reading station, where an appropriate device retrieval unit transacts the data. After the data has been transacted, the data storage devices are returned to the appropriate inventory holders, and the inventory holders are placed by the mobile drive units in locations where they may be accessed in response to further data transactions.

Optimization of data request processing for data storage systems

Techniques for maintaining versioning of data objects as a result of policy-based changes to the data objects are described herein. Metadata associated with a data object is updated as a result of an operation that is specified in a data policy associated with the data object. The metadata associated with the data object is updated based on a version key that is associated with the data object that is an identifier that identifies the data storage object in a plurality of data storage classes.

Policy-driven multiple storage class representation in versioned storage

A service provider system may provide virtualized computing services to clients, including encapsulating services that call other (encapsulated) services. Once configured to delegate parameters to encapsulated services, an encapsulating service (and its API) may not need to be modified when an encapsulated service (or its API) is modified to support more, fewer, or different features or corresponding arguments. For example, an encapsulating service may receive a service request call from a client that includes arguments for an encapsulated service (e.g., as header information, or as an opaque block or uninterpreted key-value dictionary) and may call the encapsulated service, blindly passing along those arguments. An encapsulating service may access stored policy-based arguments or obtain arguments from a central service. Arguments passed to an encapsulated service may override default parameters of the service. An encapsulating service may blindly proxy responses received from an encapsulated service to a client.

Parameter delegation for encapsulated services

Growing community of inventors

Seattle, WA, United States of America

Colin Laird Lazier