Amazon Technologies, Inc.

Jacob Andreas Kjelstrup

Conor Patrick Cahill

Khaled Salah Sedky

Ajith Harshana Ranabahu

Bharath Mukkati Prakash

Brigid Ann Johnson

Kai Zhao

Benjamin Elliott Pew

Ujjwal Rajkumar Pugalia

M Christopher Wenneman

Michael E Bundy

Michael Thomas Seifert

Jacob Frank Lucas

William P Templeton

Methods, systems, and computer-readable media for auto-tuning permissions using a learning mode are disclosed. A plurality of access requests to a plurality of services and resources by an application are determined during execution of the application in a learning mode in a pre-production environment. The plurality of services and resources are hosted in a multi-tenant provider network. A subset of the services and resources that were used by the application during the learning mode are determined. An access control policy is generated that permits access to the subset of the services and resources used by the application during the learning mode. The access control policy is attached to a role associated with the application to permit access to the subset of the services and resources in a production environment.

Auto-tuning permissions using a learning mode

A system and method for generating a policy entitlement map usable to provide a visualization of policies based at least in part on a set of resources of a service of a computing resource service provider, a set of actions that can be taken with the set of resources, or one or more identities. The policy entitlement map may be generated to reflect a set of actions performable by identities of the one or more identities, a set of resources accessible by the identities, or a set of actions that may be performed on the resources.

Entitlement map for policy simulation

Growing community of inventors

Burien, WA, United States of America

Jacob Andreas Kjelstrup