Amazon Technologies, Inc.

Zynga Inc.

Joshua Marc Burgin

Jacob Adam Gabrielson

Joby Sky Lafky

Derek Solomon Pai

Anupama Sharma

Diwakar Gupta

Simon Asselin

Kai Fan Tang

Dmitry Pushkarev

Brad Bonnett

Peter Sven Vosshall

Christoph Saalfeld

Stephen Alden Elliott

Aniruddha Shriram Daptardar

Jesper Mikael Johansson

Marvin Michael Theimer

Allan Henry Vermeulen

Peter F Hill

Matthew Scott Garman

Rebecca Claire Weiss

Joseph Elmar Magerramov

Brad Eugene Marshall

Arun Sundaram

Kurt Kufeld

Elton Victor Pinto

Asem Rustum

Deepthi Chelupati

Abhijeet Pradeep Tirthgirikar

Aleksei Besogonov

Boyd Lachlan McGeachie

Andrei Prislopski

Lawrence Wheeless

Aniruddha Shrlram Daptardar

A system and method for managing a computer-implemented online game provides dynamically variable rewards to incentivize player interaction with sponsored content presented within the game. The particular reward offered to incentivize player interaction with particular sponsored content (e.g., a particular advertisement) can be dynamically variable based on the attributes of the player, thus providing user-specific custom rewards for interaction with sponsored content. Properties of incentive rewards that may be dynamically variable can include a custom type of in-game asset or resource, and/or a custom amount of a particular in-game asset or resource.

Dynamically variable advertising incentive rewards in online games

Systems and methods permit customers of a service provider network to specify various constraints on a desired fleet of virtual machine instances without having to specify the hardware types of instances to be included in the fleet. Instead, the customer can specify per-instance hardware constraints (number of CPUs, amount of memory, etc.) and job constraints (e.g., deadline, budget, application type, etc.). A provisioning service accesses an internal database containing instance cost data, instance availability data, and mappings between application type and fleet configurations to propose a fleet of instances that complies with the customer-specified per-instance hardware and job constraints, thereby freeing the customer from having to be conversant in the particular instances offered by the service provider.

Computing resource provisioning

Techniques are described for enabling users of a cloud provider network to request the conditional termination of computing resources based on a forecasted availability of replacement capacity at a specified time or range of time in the future. A cloud provider network provides an application programming interface that can be used to make such requests, where the computing resources are hosted by the cloud provider network as part of a capacity pool shared by tenants of the cloud provider network. This type of request can be generated, for example, by a user desiring to terminate the use of some number of unproductive computing resources only if the user can be reasonably assured by the cloud provider network that capacity will be available at a future time when the user will likely need the capacity again.

Enabling conditional computing resource terminations based on forecasted capacity availability

Techniques are described for providing a multi-service storage layer in a cloud provider network for applications and workloads that are highly sensitive to outages affecting 'mission critical' data or other resources. A multi-service storage layer is designed to provide additional resiliency against various types of correlated failures among existing geographic regions by enabling the storage of data using a plurality of separate storage services and storage resource types and across a plurality of regions of the cloud-provider network. A multi-service storage layer provides an application programming interface (API) with actions for storing, retrieving, and querying data stored in a highly available storage resource across a selection of underlying storage services. The ability to store critical data and other resources using a multi-service storage layer provides additional resiliency while also providing a single interface that applications can use to interact with the data stored across any number of underlying storage services.

Multi-service storage layer for storing application-critical data

Techniques are described that enable a cloud provider network to provide specialized regions that can be used to achieve greater availability assurance for workloads highly sensitive to downtime or outages. Cloud provider network users may use specialized regions to complement the use of provider network services offered in other geographic regions defined by the cloud provider network, either to host redundant computing resources or for failover purposes, where the operation of a specialized region is designed to provide additional resiliency against various types of correlated failures among the geographic regions. As one example, a cloud provider network may stage deployments of software updates to the web services provided by the cloud provider network in a manner that ensures that specialized regions receive such updates last and over a relatively long period of time, thereby helping to ensure that any software defects are detected in an earlier deployment of the update.

Specialized cloud provider regions for availability-sensitive workloads

Techniques are described for optimizing the allocation of computing resources provided by a service provider network&#x2014;for example, compute resources such as virtual machine (VM) instances, containers, standalone servers, and possibly other types of computing resources&#x2014;among computing workloads associated with a user or group of users of the service provider network. A service provider network provides various tools and interfaces to help businesses and other organizations optimize the utilization of computing resource pools obtained by the organizations from the service provider network, including the ability to efficiently schedule use of the resources among workloads having varying resource demands, usage patterns, relative priorities, execution deadlines, or combinations thereof. A service provider network further provides various graphical user interfaces (GUIs) to help users visualize and manage the historical and scheduled uses of computing resources by users' workloads according to user preferences.

Coordinated predictive autoscaling of virtualized resource groups

Interactive GUI for bin-packing virtual machine workloads based on predicted availability of compute instances and scheduled use of the compute instances

Bin-packing virtual machine workloads using forecasted capacity usage

A computing resource service provider provides computing resources to customers, for example, computer system instances supported by server computer systems. These computer system instances may include logical volumes to support execution of the computer system instance. In addition, these instances may be terminated from time to time for various reasons. A stop signal transmitted to computing resource supporting a particular computer system instance may indicate that the particular computer system instance is to be terminated. In response to termination, the particular computer system instance may operate in accordance to a particular behavior.

User and system initiated instance hibernation

A collection of fault categories, including faults associated with internal resources at a provider network, is presented via an interface of a fault injection service. A fault injection mode, selected from a set which comprises a non-randomized mode, to be used to inject faults into a target environment is determined. Fault injection agents introduce faults into the target environment in accordance with the fault injection mode.

Fault injection service

A method for launching a plurality of computing instances may include obtaining a request to launch a plurality of computing instances. The request may indicate a first number and a target number of compute instances that is larger than the first number. The method may further include verifying that there is sufficient capacity, for example of a compute instance service, to launch at least the first number of compute instances. The request may be fulfilled by at least launching at least the first number of compute instances in a way that bypasses a rate limit that limits a rate at which compute instances can be launched. In some cases, the method may additionally include launching additional compute instances, as they become available, until the target number has been reached.

Large scale compute instance launching

A computing resource service provider may provide customer with access to computing resources which may be utilized by the customer to execute a variety of applications and/or tasks. A provisioning service of the computing resource service provider may obtain application information from the customer and determine a set of computing resource configurations suitable for executing the customer's application based at least in part on the application information obtained from the customer. The customer may select a particular computing resource configuration to execute the customer application.

Application focused provisioning system

Systems, methods, and computer-readable media related to configuration of multiple browser applications to control the functionality of the browser application as at least some content is accessed are provided. The configuration of a server-based browser application and a client-based browser application can be controlled programmatically such that browser configuration can be validated and controlled by at least some content providers. Additionally, the configuration and subsequent processing of content provided by an authenticating content provider can be implemented in a manner to limit content access functionality.

Network browser configuration

Growing community of inventors

Seattle, WA, United States of America

Joshua Marc Burgin