Abstract: A scheduler of a batch job management service determines that a set of resources a client is insufficient to execute one or more jobs. The scheduler prepares a multi-dimensional statistical representation of resource requirements of the jobs, and transmits it to a resource controller. The resource controller uses the multi-dimensional representation and resource usage state information to make resource allocation change decisions.

Abstract: Techniques are described for providing an application programming interface (API) that includes a bulk computing task operation. A bulk computing task operation enables users to request performance of any number of computing tasks using a single API request. To submit a bulk task request, a user generates or causes the generation of bulk task data describing a plurality of computing tasks to be executed by an application or service, and causes the bulk task data to be stored at an accessible storage location. A single bulk task API request can be generated that includes an identifier of the storage location at which the corresponding bulk task data is stored. The submission of a bulk task API request results in a synchronous response to the requesting client including an identifier of the request that can be used to request status updates, while processing the request can occur asynchronously using backend resources.

Abstract: Methods, systems, and computer-readable media for event-driven scheduling using directed acyclic graphs are disclosed. A directed acyclic graph is generated that comprises a plurality of nodes and a plurality of edges. The nodes represent jobs, and the edges represent dependency relationships between individual jobs. Based (at least in part) on one or more events, a job scheduler determines that one of the nodes represents a runnable job. One or more of the dependency relationships for the runnable job are satisfied by the one or more events. An execution schedule is determined for the runnable job. Based (at least in part) on the execution schedule, execution of the runnable job is initiated using one or more computing resources.

Abstract: A scheduler of a batch job management service determines that a set of resources a client is insufficient to execute one or more jobs. The scheduler prepares a multi-dimensional statistical representation of resource requirements of the jobs, and transmits it to a resource controller. The resource controller uses the multi-dimensional representation and resource usage state information to make resource allocation change decisions.

Abstract: A scheduler of a batch job management service determines that a set of resources a client is insufficient to execute one or more jobs. The scheduler prepares a multi-dimensional statistical representation of resource requirements of the jobs, and transmits it to a resource controller. The resource controller uses the multi-dimensional representation and resource usage state information to make resource allocation change decisions.

Abstract: Methods, systems, and computer-readable media for event-driven scheduling using directed acyclic graphs are disclosed. A directed acyclic graph is generated that comprises a plurality of nodes and a plurality of edges. The nodes represent jobs, and the edges represent dependency relationships between individual jobs. Based (at least in part) on one or more events, a job scheduler determines that one of the nodes represents a runnable job. One or more of the dependency relationships for the runnable job are satisfied by the one or more events. An execution schedule is determined for the runnable job. Based (at least in part) on the execution schedule, execution of the runnable job is initiated using one or more computing resources.

Abstract: A scheduler of a batch job management service determines that a set of resources a client is insufficient to execute one or more jobs. The scheduler prepares a multi-dimensional statistical representation of resource requirements of the jobs, and transmits it to a resource controller. The resource controller uses the multi-dimensional representation and resource usage state information to make resource allocation change decisions.