Amazon Technologies, Inc.

Oracle International Corporation

Prashant L Sarma

David R Azari

Monty Vanderbilt

Daniel Lee Osiecki

Caitlyn R Schmidt

Brian Dennehy

Mykyta Synytskyy

Ganesh Viswanathan

Heng Zhe Duan

Systems, methods, and other embodiments associated with implementing access control to time series data are described. In one embodiment, a method includes associating streams of time series data to a group and assigning the group to an access control container. The example method may also include defining an access policy specifying access control rules for authorizing access to the time series data. The example method may also include receiving a request from a requestor to access the time series data of the group through the access control container. The example method may also include executing the access control rules within the access policy to either deny the request or allow implementation of the request.

Computerized methods and systems for implementing access control to time series data

Disclosed are various embodiments for processing and storing mass data, where the data may include metrics generated based on performance of an event in a monitored system. Metrics describing a state of a monitored system may be received, accessed, and aggregated to generate a data model that describes performance of the monitored system. The metrics utilized in generating the data model may be disregarded after the data model has been generated. An output describing the state of the monitored system may be generated based on the data model, and the output may be communicated over a network, for example, to a requesting service.

Storage of mass data for monitoring

Disclosed are various in various embodiments are systems and methods providing for storage of mass data such as metrics. A plurality of data models are generated in the server from a stream of metrics describing a state of a system. Each of the metrics is associated with one of a plurality of consecutive periods of time, and each data model represents the metrics associated with a corresponding one of the consecutive periods of time. The data models are stored in a data store and each of the metrics is discarded after use in generating at least one of the data models.

Disclosed in various embodiments are systems and methods providing for storage of mass data such as metrics. A plurality of data models are generated in the server from a stream of metrics describing a state of a system. Each of the metrics is associated with one of a plurality of consecutive periods of time, and each data model represents the metrics associated with a corresponding one of the consecutive periods of time. The data models are stored in a data store and each of the metrics is discarded after use in generating at least one of the data models.

A plurality of data models are generated in a server from a stream of metrics describing a state of at least one system. Each of the data models represents a time grouping of a subset of the metrics. One or more dimensions are associated with each of the metrics. The data models are stored in association with respective ones of the dimensions in a memory. The dimensions with which the data models are associated in the memory are increased based upon an appearance of at least one previously non-existing dimension associated with a metric in the stream.

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Bellevue, WA, United States of America

Prashant L Sarma