Amazon Technologies, Inc.

Derek Steven Manwaring

Timothy Allen Wagner

Sean Philip Reque

Dylan Chandler Thomas

Xin Zhao

Marc John Brooker

Ajay Nair

Mikhail Danilov

Osman Surkatty

Bradley Nathaniel Burkett

Peter Martin McDonnell

Stefan Schneider

Peter Martin Mcdonnell

Systems and methods are described for providing secure storage of data sets while enabling efficient deduplication of data. Each data set can be divided into fixed-length blocks. The plaintext of each block can be convergently encrypted, such as by using a hash of the plaintext as an encryption key, to result in block-level ciphertext that can be stored. If two data sets share blocks, the resulting block-level ciphertext can be expected to overlap, and thus duplicative block-level ciphertexts need not be stored. A manifest can be created to facilitate re-creation of the data set, which manifest identifies the block-level ciphertexts of the data set and a key by which each block-level ciphertext was encrypted. By use of block-level encryption, nearly identical data sets can be largely deduplicated, even if they are not perfectly identical.

Efficient deduplication using block-based convergent encryption

Systems and methods are described for providing storage of encrypted data sets, deduplication of such data sets, and control of the redundancy of those data sets. A form of modified convergent encryption can be employed, whereby an encryption key for a data set is selected based on a combination of the plaintext of the data set and a salt value, with the salt value being selected from a number of permutations corresponding to a desired redundancy of the data set in a storage system. Accordingly, a given data set can result in a number of ciphertexts equal to the desired redundancy, and deduplication can occur by removing duplicative instances of individual ciphertexts. Salt values can be selected according to a variety of criteria, including user-based, time-based, and location-based criteria.

Redundancy controls in convergent encryption using dynamic salt values

A system for providing automatic resource resizing is provided. The system may be configured to maintain a plurality of virtual machine instances. The system may be further configured to receive a request to execute a program code and allocate computing resources for executing the program code on one of the virtual machine instances. The amount of resources allocated for executing the program code may be specified by the request and adjusted as needed.

Automatic determination of resource sizing

A system for providing automatic management of low latency computational capacity is provided. The system may be configured to maintain a plurality of virtual machine instances. The system may be further configured to identify a trend in incoming code execution requests to execute program code on a virtual compute system, determine, based on the identified trend, that the plurality of virtual machine instances should be adjusted, and adjust the plurality of virtual machine instances based on the identified trend.

Automatic management of low latency computational capacity

A system for routing requests to execute user code based on how frequently the user code is executed is provided. The system may be configured to receive a request to execute user code on a virtual compute system, where the virtual compute system comprises multiple fleets of virtual machine instances. The system may be further configured to determine whether the user code associated with the request satisfies one or more usage criteria, and based on the determination, route the request to the appropriate fleet of virtual machine instances.

Message-based computation request scheduling

A system for providing dynamic code deployment and versioning is provided. The system may be configured to receive a first request to execute a newer program code on a virtual compute system, determine, based on the first request, that the newer program code is a newer version of an older program code loaded onto an existing container on a virtual machine instance on the virtual compute system, initiate a download of the newer program code onto a second container on the same virtual machine instance, and causing the first request to be processed with the older program code in the existing container.

Dynamic code deployment and versioning

Systems and methods are described for managing cross-account access to tasks on an on-demand code execution environment or other distributed code execution environment. Such environments utilize pre-initialized virtual machine instances to enable execution of user-specified code in a rapid manner, without delays typically caused by initialization of the virtual machine instances. However, to ensure security, the code of different users is generally maintained separately, and executed on separate virtual machines. Embodiments described herein enable users of a first account to execute code of a second account, without gaining access to the code itself and while maintaining the privacy and security of each account. Specifically, aliases for a task of a first account can be created on a task of a second account, and used to invoke that task on behalf of the first account. Aliases may also allow users to customize how the task is executed.

On-demand network code execution with cross-account aliases

Systems and methods are described for utilizing cross-account access to tasks on an on-demand code execution environment or other distributed code execution environment to implement an application programming interface (API) on a network-accessible service. An on-demand code execution environment can utilize pre-initialized virtual machine instances to enable execution of user-specified code in a rapid manner, without delays typically caused by initialization of the virtual machine instances. While users may generally execute their own code, the present application enables code of a first user to be executed by a second user, while maintaining the privacy and security of the code and associated accounts. Further, the present application enables a set of tasks to be grouped together as an API, enabling any user to create an API for a service, while the on-demand code execution environment manages execution of the tasks and allocation of underlying computing resources.

Growing community of inventors

Lynnwood, WA, United States of America

Derek Steven Manwaring