Amazon Technologies, Inc.

Brian James Schuster

Bruce Erwin Brown

Joseph Richard Thompson

Jonathan Robert Bush

Geoffrey Scott Pare

Mohit Gupta

Christopher David Byskal

Ryan Preston Gantt

Avinash Shripathy Bhat

Alexander Lambertus Eusman

Richard Jeffrey Cole

Adam Julio Villalobos

Martin Paul Zolnieryk

Raj K Kizhakkekalathil

Akshay Gopal Shetty

Xiaohang Miao

Andrew Kyle McWilliams

Dajun Duan

Andrew Bruce Dickinson

Benjamin Aaron Miller

Jeetendra G Mirchandani

Ross Alan Cameron Gardner

Alexis Levasseur

Therapon Skoteiniotis

Llewllyn J Mason

Simon C Vining

Mark Jacobson

Justin Miles

Joshua Joseph Clark

Brian Francis Lee

Xiaoshu Lu

Kenneth Beony Lin

Shashank Senapaty

Karen R Haberkorn

Jeff Curley

Mike Perkowitz

A request to create a game fleet may be received by a game session management service. The game session management service may manage a fixed host fleet type and a non-fixed host fleet type, wherein the fixed host fleet type allows game server execution only on a fixed host topology of a computing service provider affiliated with the game session management service, and wherein the non-fixed host fleet type allows game server execution on any host topology. The request may indicate that the first game fleet has the non-fixed host fleet type. A host registration request to register a host to the first game fleet may be received. A process registration request to register a game server process executing on the host may be received. The game session management service may communicate with the game server process executing on the host via a designated communications interface.

Video game session management on non-fixed computer hosting topologies

A selection to use a customer-generated matchmaking algorithm is received, by a multi-tenant gaming service, from a first customer. Indications of a plurality of video game player matchmaking requests and corresponding player characteristic data are provided, by the multi-tenant gaming service, for processing by the customer-generated matchmaking algorithm. An indication of a first player match determined by the customer-generated matchmaking algorithm, based on the video game player matchmaking requests and the player characteristic data, is received, by the multi-tenant gaming service. The first player match may be between at least a first player and a second player. Execution of a first video game session to which the first player and the second player are connected is hosted, by the multi-tenant gaming service.

Customer-generated video game player matchmaking in a multi-tenant environment

A game-hosting service of a service provider network is configured to place game sessions on fleets of virtual machine (VM) instances using a value-based approach. In order to place a game session on a fleet, the game-hosting service may determine one or more attributes of the game session request, such as player attributes and/or game attributes. The game-hosting service may also determine available fleets of VM instances allocated to a subscriber associated with the game session request, which may be located across disparate geographical regions. A value(s) may be determined based on the attributes of the game session request, and the value(s) may be used to select a fleet of the available fleets for hosting the game session.

Value-based game session placements

A multi-region game server fleet may span a plurality of computing regions including a home computing region and one or more remote computing regions. A fleet management service operating in the home computing region may receive a request to perform a modification to the multi-region game server fleet, such as adding an additional remote computing region, removing an existing remote computing region, or making a configuration change. The modification may be performed, at least in part, by one or more region specific worker processes hosted in the home region. The fleet management service operating in the home computing region may also receive a request to perform an interaction with a specific remote region game server. An instruction corresponding to the interaction may be transmitted, by a region-specific computing function hosted in the home region, to the specific remote region game server.

Cross-region management of game server fleets

Multi-region game server fleets

A matchmaker (e.g., matchmaking software) may be implemented as a number of matchmaker shards, where each shard can potentially run on a different host within a service provider network. Disclosed herein are techniques and systems for dynamically adjusting a shard count associated with a given matchmaker of a subscriber during runtime, the shard count dictating a number of matchmaker shards used for assigning players to matches of a game. Adjustment of the shard count may be based on metrics that are usable to determine whether the current number of matchmaker shards is/are 'overloaded', and, if so, the shard count can be increased, or whether the current number of matchmaker shards are 'underloaded', and, if so, the shard count can be decreased.

Dynamic adjustment of shard count for player matchmaking

A game-streaming service of a service provider network is configured to assign virtual machine (VM) instances to game streaming requests using a value-based approach. In order to assign a VM instance to a game streaming request for streaming a game to a client device of a player associated with the game streaming request, the game-streaming service may determine one or more attributes of the game streaming request, such as player attributes and/or game attributes. The game-streaming service may also determine available VM instances allocated to a subscriber associated with the game streaming request, which may be located across disparate geographical regions. A value(s) may be determined based on the attributes of the game streaming request, and the value(s) may be used to select one of the available VM instances for streaming the game as part of a corresponding game session.

Value-based streaming instance assignment

This disclosure describes techniques for a game-hosting service of a service provider network to dynamically determine a number of processes that are permitted to concurrently execute on an instance based on health values that indicate performances of the processes running on the instance. The game-hosting service may periodically or continuously receive health values from the instance, or multiple instances in a fleet of instances, and determine whether additional processes may be permitted to run, or if less processes may be permitted to run, on the instance based on the performance of the processes that are concurrently running on the instance. In this way, instances may dynamically be permitted to concurrently execute additional processes, or less processes, to help ensure that computing resources are being efficiently utilized, but also while maintaining acceptable performance for processes (e.g., game sessions) that are hosted on the instances.

Dynamic management of processes executing on computing instances

A game-hosting service of a service provider network is configured to dynamically adjust a batching interval used to assign processes to game session requests in batches of processes. The adjustment of the batching interval may be based on a level of contention resulting from operations to assign processes to game session requests. With the batching interval adjusted, the game-hosting service may queue one or more incoming game session requests received during the batching interval, query a data store for available processes after a lapse of the batching interval, assign ones of the available server processes to the game session request(s), and instruct the assigned processes to host corresponding game sessions. Dynamically adjusting the batching interval in this manner allows high volume games to benefit from added throughput, while lower volume games can benefit from quicker latency.

Dynamic batching interval adjustment for game session creation

The present disclosure provides for matching users into user groups based on user attributes. A neural network is trained using training data including user data of users in an observed grouping and various outcomes or optimization parameters associated with the observed grouping. The trained neural network is used to process a set of queried players determine a match quality for the queried players with respect to certain outcomes or optimization parameters based at least in part on the user data associated with the users. The match quality is a measure of how optimized a group containing the queried users is with respect to the optimization parameters and can be compared to a threshold. The queried users may be matched into a group if the match quality meets or exceeds the threshold.

Matching players for networked gaming applications

Techniques for singleton coordination in an actor-based system are described herein. In some examples, one or more actors within an actor based system may be designated as singleton actors. Each singleton actor is permitted to have only a single associated instance in the actor-based system. In some cases, when multiple executing instances (i.e., duplicates) of a singleton actor are detected, the duplicates may be resolved, for example, such that no more than a single instance of the singleton actor is retained. In some examples, one or more singleton coordinators may be responsible for selecting one or more hubs on which to generate new or re-generated singletons, monitoring existing singletons to ensure that they continue to execute, and re-generating existing singletons after termination.

Singleton coordination in an actor-based system

Remote computing resource service providers, including online retailer, provide externally facing computer systems that allow users to interact with the service provider. Furthermore, the service provider may maintain computer systems and service inside an isolated network not exposed to users. Occasionally, service providers may test these externally facing computer systems using one or more external hosts operating on a public network. A coordinator may archive aggregated testing resources located on the isolated network and deploy the testing resources to the one or more external hosts. A database may be used to track the deployment state of the one or more external hosts in order to allow the coordinator to manage the testing process.

State-tracked testing across network boundaries

A quick or limited matching process can be used to quickly get players of a gaming application into an active game session. In order to improve the quality of the match for a subsequent game session, a longer-running match process can be utilized while players are engaged in a current game session. A pool of players likely to be available around the time at which a current game session will end is determined. The longer-running match process can analyze the data for the player pool to determine matches of players for one or more future game sessions. Information for these sessions can be provided to the relevant players, who are then enabled to join in the respective sessions. Such a process provides for more flexibility and accuracy in the matching process without extending the player wait times endured.

Session management for virtual environments

Techniques for debugging of a collection of instructions executed by a computing system including a set of actors are described herein. A first sub-set of actors from the set of actors to be monitored for debugging and one or more error condition associated with the collection of instructions may be identified. A set of indications including indications of messages processed by the actors, indications of associated actor states prior to processing of the messages, and indications of associated actor states subsequent to processing of the messages may be received from the sub-set of actors. It may then be determined that a first actor of the sub-set of actors has satisfied the error condition. Based at least in part on the set of indications, one or more messages associated with satisfaction of the error condition may then be identified, for example for re-processing and debugging.

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Seattle, WA, United States of America

Brian James Schuster