Amazon Technologies, Inc.

Gaurav Gupta

Timothy Andrew Rath

Omer Ahmed Zaki

Mustafa Ozan Ozen

Gaurav Saxena

Karthik Gurumoorthy Subramanya Bharathy

Lonnie J Princehouse

Kamal Garg

A trained model and/or an edge client running on an edge device may obtain data from a data source (e.g., a security video camera) and determine, based on a result of processing the data using the model, whether to send an indication of an upcoming data/video stream to the provider network (e.g., indicating a bearer modification). The received indication may be used by the provider network to send a request to a serving wireless infrastructure (e.g., telco operator/wireless mobile core) for configuration of one or more resources on behalf of the edge device to process the upcoming data stream. The received indication may be used by the provider network in order to configure one or more resources at the provider network to process the upcoming data stream. The edge device initiates transmission of the data stream from the data source to the provider network via the serving wireless infrastructure.

Edge intelligence-based resource modification for transmitting data streams to a provider network

Methods, systems, and computer-readable media for a scalable architecture for a distributed time-series database are disclosed. Using a fleet of ingestion routers, time-series data generated by a plurality of client devices is stored into a plurality of durable partitions. The time-series data comprises a plurality of time series, and an amount of the ingestion routers is determined based at least in part on an ingestion rate of the time-series data. Using a fleet of stream processors, the time-series data from the durable partitions is stored into a plurality of storage tiers including a first storage tier and a second storage tier. A retention period for the first storage tier differs from a retention period for the second storage tier. An amount of the stream processors is determined based at least in part on the time-series data in the durable partitions.

Scalable architecture for a distributed time-series database

Methods, systems, and computer-readable media for continuous functions in a time-series database are disclosed. A plurality of data points of a time series are stored into one or more storage tiers of a time-series database. The plurality of data points comprise a plurality of discrete measurements at respective timestamps. Using one or more query processors of the time-series database, a query of the time series is initiated. The query indicates a time range. Using the one or more query processors, a continuous function is determined that represents a segment of the time series in the time range. The continuous function is determined based at least in part on the plurality of data points. An operation is performed using the continuous function as an input.

Continuous functions in a time-series database

Growing community of inventors

Sammamish, WA, United States of America

Gaurav Gupta