Abstract: Systems and methods are described for enabling graceful recovery of network connections in a virtual machine instance that has been migrated or temporarily halted. To prevent the virtual machine instance from attempting to reuse open connections, which might fail due to migration or halting, a host device identifies open connections just prior to halting the virtual machine instance on the host, and transmits to the virtual machine instance termination signals for the open connections. The host device may further transmit termination signals to the other parties to such connections. Each termination signal may be formatted so as to appear to originate from the other party to the connection, causing both parties to synchronize their knowledge of the connection. On reactivation, the virtual machine instance can recovery the connections without errors associated with attempted utilization of broken connections.

Abstract: Systems and methods are described for providing updating of disk images supporting serverless code execution and controlled deployment of updated disk images. A disk image can be defined as a set of layers that represent a file system include code of a serverless function and other data used by the code. A function owner can designate one layer as containing software or other data subject to update. When a new version of the layer is obtained at a serverless compute system, the system can generate a new disk image containing the updated layer. The system can then gradually transition the function to the new disk image, by dividing calls to the function among two versions of the function—one using the prior disk image, and one using the new disk image. Performance data gained from the new version of the function can be used to control the gradual transition.

Abstract: Systems and methods are described for simulated data object storage on a data storage system. The system may allow clients to store computed data objects, which are generated from a source data object based on a user-defined transformation. For example, computed data objects may be thumbnail images generated based on a full resolution image. When a request to store a computed data object is received, the system can predict a timing of a next request for the data object. If expected resource consumption associated with storing the data object until a next request exceeds expected resource consumption associated with generating the data object in response to the next request, the system can acknowledge the request to store the data object, but not actually store the data object. Instead, the system may generate the data object in response to the next request.

Abstract: Systems and methods are described for providing performance-based hardware emulation in an on-demand network code execution system. A user may generate a task on the system by submitting code. The system may determine, based on the code or its execution, that the code executes more efficiently if certain functionality is available, such as an extension to a processor's instruction set. The system may further determine that it can provide the needed functionality using various computing resources, which may include physical hardware, emulated hardware (e.g., a virtual machine), or combinations thereof. The system may then determine and provide a set of computing resources to use when executing the user-submitted code, which may be based on factors such as availability, cost, estimated performance, desired performance, or other criteria. The system may also migrate code from one set of computing resources to another, and may analyze demand and project future computing resource needs.

Abstract: Systems and methods are described for providing performance-based hardware emulation in an on-demand network code execution system. A user may generate a task on the system by submitting code. The system may determine, based on the code or its execution, that the code executes more efficiently if certain functionality is available, such as an extension to a processor's instruction set. The system may further determine that it can provide the needed functionality using various computing resources, which may include physical hardware, emulated hardware (e.g., a virtual machine), or combinations thereof. The system may then determine and provide a set of computing resources to use when executing the user-submitted code, which may be based on factors such as availability, cost, estimated performance, desired performance, or other criteria. The system may also migrate code from one set of computing resources to another, and may analyze demand and project future computing resource needs.