Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Live migration can be performed for a process executing on an allocated resource for an application session. During a session it might be determined that it is necessary, or would at least be advantageous, to migrate the process to different resource capacity. New capacity such as a new computing instance can be identified, and synchronized with a current instance to reflect current state information. This can include obtaining state data from a serialized file or transaction log, among other such options. The client devices on the session can be caused to connect or direct state data to the new instance, and when ready the new instance can be responsible for the process, such as by taking over as the application server for the session. Once the client devices are utilizing the new instance, the process can be terminated on the old instance and the instance destroyed or reallocated.

Abstract: 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.

Abstract: 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.