Abstract:
Techniques are described for providing client computing nodes with enhanced access to remote network-accessible services, such as by providing local capabilities specific to the remote services. In at least some situations, access to remote services by a client computing node may be enhanced by automatically locally performing some activities of the remote services, such as to improve the efficiency of communications that are sent between the client computing node and the remote service and/or to improve the efficiency by the remote service of processing communications from the client computing node. As one example, a node manager system local to a client computing node may perform authentication of communications sent by the client computing node to a remote service and/or may perform other activities specific to the remote service, so that the remote service does not need to perform the authentication and/or other performed activities for the communications.
Abstract:
Intelligent content delivery enables content to be delivered to different devices in formats appropriate for those devices based on the capabilities of those devices. A user might access the same piece of content on two different devices, and can automatically receive a higher quality format on a device capable of playing that higher quality format. The user can purchase rights to content in any format, such that as new formats emerge or the user upgrades to devices with enhanced capabilities, the user can receive the improved formats automatically without having to repurchase the content. Further, the user can pause and resume content between devices even when those devices utilize different formats, and can access content on devices not otherwise associated with the user, receiving content in formats that are appropriate for those unknown devices even if the user has not previously accessed content in those formats.
Abstract:
Techniques are described for managing distributed execution of programs. In at least some situations, the techniques include decomposing or otherwise separating the execution of a program into multiple distinct execution jobs that may each be executed on a distinct computing node, such as in a parallel manner with each execution job using a distinct subset of input data for the program. In addition, the techniques may include temporarily terminating and later resuming execution of at least some execution jobs, such as by persistently storing an intermediate state of the partial execution of an execution job, and later retrieving and using the stored intermediate state to resume execution of the execution job from the intermediate state. Furthermore, the techniques may be used in conjunction with a distributed program execution service that executes multiple programs on behalf of multiple customers or other users of the service.
Abstract:
Techniques are described for managing distributed execution of programs. In some situations, the techniques include dynamically modifying the distributed program execution in various manners, such as based on monitored status information. The dynamic modifying of the distributed program execution may include adding and/or removing computing nodes from a cluster that is executing the program, modifying the amount of computing resources that are available for the distributed program execution, terminating or temporarily suspending execution of the program (e.g., if an insufficient quantity of computing nodes of the cluster are available to perform execution), etc.
Abstract:
A system that implements a scalable data storage service may maintain tables in a non-relational data store on behalf of clients. The system may provide a Web services interface through which service requests are received, and an API usable to request that a table be created, deleted, or described; that an item be stored, retrieved, deleted, or its attributes modified; or that a table be queried (or scanned) with filtered items and/or their attributes returned. An asynchronous workflow may be invoked to create or delete a table. Items stored in tables may be partitioned and indexed using a simple or composite primary key. The system may not impose pre-defined limits on table size, and may employ a flexible schema. The service may provide a best-effort or committed throughput model. The system may automatically scale and/or re-partition tables in response to detecting workload changes, node failures, or other conditions or anomalies.
Abstract:
A set of techniques is described for monitoring and analyzing crashes and other malfunctions in a multi-tenant computing environment (e.g. cloud computing environment). The computing environment may host many applications that are executed on different computing resource combinations. The combinations may include varying types and versions of hardware or software resources. A monitoring service is deployed to gather statistical data about the failures occurring in the computing environment. The statistical data is then analyzed to identify abnormally high failure patterns. The failure patterns may be associated with particular computing resource combinations being used to execute particular types of applications. Based on these failure patterns, suggestions can be issued to a user to execute the application using a different computing resource combination. Alternatively, the failure patterns may be used to modify or update the various resources in order to correct the potential malfunctions caused by the resource.
Abstract:
Techniques are described for managing distributed execution of programs. In at least some situations, the techniques include decomposing or otherwise separating the execution of a program into multiple distinct execution jobs that may each be executed on a distinct computing node, such as in a parallel manner with each execution job using a distinct subset of input data for the program. In addition, the techniques may include temporarily terminating and later resuming execution of at least some execution jobs, such as by persistently storing an intermediate state of the partial execution of an execution job, and later retrieving and using the stored intermediate state to resume execution of the execution job from the intermediate state. Furthermore, the techniques may be used in conjunction with a distributed program execution service that executes multiple programs on behalf of multiple customers or other users of the service.
Abstract:
Techniques are described for providing client computing nodes with enhanced access to data from remote locations, such as by providing and using local capabilities specific to the remote locations. In at least some situations, the access of a client computing node to data from a remote location may be enhanced by automatically performing activities local to the client computing node that improve the efficiency of communications sent between the client computing node and the remote location. As one example, access to data from a remote service may be enhanced by locally performing activities specific to the remote service, such as by using information about the remote service's internal mechanisms to cause the desired data to be provided from internal storage devices of the remote service without passing through front-end or other intermediate devices of the remote service while traveling to the client computing node.
Abstract:
A system that implements a scalable data storage service may maintain tables in a non-relational data store on behalf of clients. The system may provide a Web services interface through which service requests are received, and an API usable to request that a table be created, deleted, or described; that an item be stored, retrieved, deleted, or its attributes modified; or that a table be queried (or scanned) with filtered items and/or their attributes returned. An asynchronous workflow may be invoked to create or delete a table. Items stored in tables may be partitioned and indexed using a simple or composite primary key. The system may not impose pre-defined limits on table size, and may employ a flexible schema. The service may provide a best-effort or committed throughput model. The system may automatically scale and/or re-partition tables in response to detecting workload changes, node failures, or other conditions or anomalies.
Abstract:
A system that implements a scalable data storage service may maintain tables in a non-relational data store on behalf of clients. The system may provide a Web services interface through which service requests are received, and an API usable to request that a table be created, deleted, or described; that an item be stored, retrieved, deleted, or its attributes modified; or that a table be queried (or scanned) with filtered items and/or their attributes returned. An asynchronous workflow may be invoked to create or delete a table. Items stored in tables may be partitioned and indexed using a simple or composite primary key. The system may not impose pre-defined limits on table size, and may employ a flexible schema. The service may provide a best-effort or committed throughput model. The system may automatically scale and/or re-partition tables in response to detecting workload changes, node failures, or other conditions or anomalies.