Amazon Technologies, Inc.

Gabriel Mastey

Ali Baghani

Adam Alexander Emerson Wong

Patrick MacLaine Compton

Andrew Katz

Maury Richard Sponchia

Scott Matthew King

Justin Wayne Callison

Diego Raphael Pedroza Santiviago

Daniel James Ronald

Feng Qiu

Jalandip Lepcha

Russell William Mackenzie

System and methods are provided for dynamically parallelized large data set processing. A workflow includes a distributed map state. A set of steps in the distributed map state are run for each item in a collection of items or for each batch. Execution of the distributed map state is dynamically parallelized such that the system creates as many parallel workflows as there are items in the collection at run time (or batches). The items in the collection are dynamically determined by the workflow system, as defined by a resource in the distributed map state.

Dynamically parallelized workflow processing

Computer systems and methods are disclosed to implement a role manager that automatically analyzes code accessing various resources to generate a role with the necessary resource permissions to execute the code. In embodiments, the role manager may be implemented as part of a workflow orchestration or resource provisioning system that employs code requiring access to different types of resources. In embodiments, the role manager may analyze a code segment to identify the different resources accessed by the code segment and the permissions needed for each access, and generate a role that has the needed permissions. In embodiments, the role manager may automatically manage these roles based on changes to associated code segments. Advantageously, the disclosed role manager removes the need to manually create roles need by code segments ahead of time, and creates roles with minimal privileges required for the code, thereby simplifying achievement of system security.

Automated role management for resource accessing code

Growing community of inventors

Vancouver, Canada

Gabriel Mastey