Amazon Technologies, Inc.

Aswin Damodar

Jason Roy Rupard

Chetan Hosmani

Dougal Stuart Ballantyne

Rejith George Joseph

James Edward Kinney, Jr

Kiuk Chung

Chris William Ramsey

Brian William Barrett

Xu Yang

Devendra D Chavan

Ujjwal Kamal Kabra

Stephen William Kendrex

SongPerk Sem

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.

Resource allocation and scheduling for batch jobs

Methods, systems, and computer-readable media for dynamic regulation of parallelism for job scheduling are disclosed. A job scheduler sends a resource manager a request to execute a first set of compute jobs using a set of computing resources. The number of jobs corresponds to a first parallelism value. The job scheduler receives a response indicating that the number of computing resources was sufficient or insufficient to schedule the jobs. The job scheduler sends another request to execute another set of compute jobs whose number corresponds to a new parallelism value determined based at least in part on the response. If the number of computing resources was sufficient, the new parallelism value represents an increase over the first parallelism value. If the number of computing resources was insufficient, the new parallelism value represents a decrease from the first parallelism value.

Dynamic regulation of parallelism for job scheduling

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.

Providing an application programming interface (API) including a bulk computing task operation

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Seattle, WA, United States of America

Aswin Damodar