Amazon Technologies, Inc.

Harshad Vasant Kulkarni

Colin Watson

Jeffrey Cicero Canton

Conor Patrick Cahill

Jasmeet Chhabra

William Frederick Hingle Kruse

Andrew Paul Mikulski

Dmitry Frenkel

Vikas Dharia

Khaled Salah Sedky

Sharjeel Sohail

Umut Orhan

Carlos Daniel Gasperi

Scott Michael Wiltamuth

Ashish Rangole

Rachit Jain

Rohit Raj

Ian Leung

Prasad Krishnan

Zaid Radi Abu Ziad

Douglas Allen Walter

Jan Gasthaus

Tim Januschowski

Valentin Flunkert

Rahul Tongia

A plurality of metrics records, including some records indicating metrics for which anomaly analysis has been performed, is obtained. Using a training data set which includes the metrics records, a machine learning model is trained to predict an anomaly analysis relevance score for an input record which indicates a metric name. Collection of a particular metric of an application is initiated based at least in part on an anomaly analysis relevance score obtained for the particular metric using a trained version of the model.

Machine learning-based selection of metrics for anomaly detection

A request to add tags (e.g., labels, key-value pairs, or metadata) to resources can be digitally signed by the entity making the request, such that the source can be verified and an authorization determination made for each tag. For a request involving multiple services (or entities) that can each add tags, any tag added by a service can be included in the request and digitally signed by that service. Each service processing the request can also digitally sign the request before forwarding, so that each service signs a version of the request, which includes elements signed by other services earlier in the request chain. When the request is received to a tagging service, the service ensures that every tag was digitally signed by the appropriate authorized entity or service, and validates the signatures to ensure that no data was modified or omitted, before adding the tags to the designated resource(s).

Contribution signatures for tagging

A set of operations is performed to cause a resource accessible to a first set of entities to also be accessible to a member of a second set of entities, where the set of operations, as a result of being executed, causes a processor to create a project to associate with a set of resources, associate a policy that controls access to the set of resources with the projects, associate the resource with the set of resources of the project, and associate the member of the second set of entities with the project. A request is obtained from the member of the second set of entities to access the resource. The member of the second set of entities is determine to be authorized to access the resource based on the policy. The member of the second set of entities is allowed to obtain access to the resource.

Mechanism to manage group of resources using virtual resource containers

Techniques for determining insight are described. An exemplary method includes receiving a request to provide insight into potential abnormal behavior; receiving one or more of anomaly information and event information associated with the potential abnormal behavior; evaluating the received one or more of the anomaly information and event information associated with the abnormal behavior to determine there is insight as to what is causing the potential abnormal behavior and to add to an insight at least two of an indication of a metric involved in the abnormal behavior, a severity for the insight indication, an indication of a relevant event involved in the abnormal behavior, and a recommendation on how to cure the potential abnormal behavior; and providing an insight indication for the generated insight.

Systems, methods, and apparatuses for detecting and creating operation incidents

An authentication system receives authentication information from a user as part of a request to access a web-based service. The authentication system transmits the authentication information to a set of second users authorized to evaluate the authentication information. If a threshold number of the set of second users authenticate the identity of the first user, the authentication system enables the user to access the web-based service.

Threshold-based authentication

A set of parameters for a set of permissions are determined based at least in part on previous requests to access a set of resources by a principal or user. The set of permissions are updated based at least in part on the set of parameters such that the set of parameters cause different requests to have different authentication requirements. The updated set of permissions is enforced to control access to computing resources such as the set of resources.

Adaptive access control policies

Restoring data to a data store that suffered corrupted data over a time period is disclosed. A system may provide an interface to specify a time window and filter conditions for identifying corrupted data in an object in a data store, such as, but not limited to, a corrupted NoSQL table. Corrupted data is identified by applying the filter conditions to change logs for the data object (e.g., the No SQL table) in the data store. Repair operations are determined for individual items identified via the filter conditions. Identified corrupted data for items may be corrected, from change logs or backup data in some instances (e.g., data may be deleted, or updated or replaced with data from a backup of the data store when necessary).

Restoration of a data source

A customer of a computing resource service provider submits a request to a service in a first data region to obtain all customer data stored across all data regions managed by the computing resource service provider. Accordingly, the service may refer to a chatter table that includes a listing of locations wherein customer data may be stored to determine which data regions comprise customer data. Based on the determination, the service may transmit one or more requests to other services within the determined data regions to obtain the customer data while ignoring any data regions that do not comprise customer data. Upon receiving the customer data, the service may aggregate this data and provide the aggregated data to the customer to fulfill the customer request.

Method for aggregating distributed data

In a network-based services platform, customer resources may be automatically associated with a resource creator. Upon receipt of a request to create a computing resource, the computing resource may be created and thereafter executed within the network-based services platform. In response to the request, an entity associated with the request may be identified. In response to the identification of the entity, the computing resource may be automatically associated with the identified entity specifying the entity as the creator of the computing resource. In some embodiments, a cost of operating the resource over a period of time may be calculated, and the cost allocated to the identified entity based at least in part on the creator-to-resource association that was automatically generated upon creation of the resource. In this manner, a usage allocation report may be provided to the customer that shows the cost associated with the entity.

Automated association of computing resources with resource creators for usage allocation

A user of a tag manager utilizes a tag manager to request creation of one or more zonal metadata tags. When the metadata tags are created, the tag manager updates a tag manager database to include information concerning the created metadata tags. Subsequently, the tag manager attempts to update a changes table within a discovery service database to include this information, the changes table usable by a discovery service to support regional and global tag queries. If the update of the changes table is initially unsuccessful, the tag manager may utilize a replicator to synchronize the tag manager database and the changes table when the discovery service database is once again available.

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Bellevue, WA, United States of America

Harshad Vasant Kulkarni