Amazon Technologies, Inc.

Hans-Philipp Anton Hussels

Marc John Brooker

Timothy Allen Wagner

Surya Prakash Dhoolam

Mustafa Ugur Torun

James Paul Kardos

Cecilia Deng

Bradley Nathaniel Burkett

Jonathan Patrick Lim

Alireza Sahraei

Kaili Xu

Gyanendra Mishra

A computing resource monitoring service obtains a request from a third-party partner system to generate a first bus. In response to the request, the computing resource monitoring service updates an account associated with a customer of a remote service to indicate presence of the first bus. The computing resource monitoring service activates the first bus to establish an association with a second bus, obtain a set of events generated by a resource of the third-party partner system, and provides the set of events to the first bus. The computing resource monitoring service publishes the set of events to cause the second bus to distribute the set of events to another remote service.

Hybrid system event processing

Systems and methods are described for providing an implementation of the MapReduce programming model utilizing tasks executing on an on-demand code execution system, utilizing a stream data processing system as an intermediary between map and reduce function. A map task implementing a map function can process portions of a data set, to generate outputs associated with different values for a measured attribute of the data set. Executions of the map task can publish outputs to a data stream on the stream data processing system, which stream is configured to utilize the measured attribute as a partition key for the stream. Based on the partition key, the stream data processing system can divide the stream into sub-streams, each containing a relevant subset of the outputs. The on-demand code execution system can execute a reduce task to apply the reduce function to the outputs of each sub-stream, thereby completing the MapReduce process.

Mapreduce implementation in an on-demand network code execution system and stream data processing system

Systems and methods are described for providing maintaining state information during processing of data sets via execution of code on an on-demand code execution system. Rather than requiring that execution environments of such a system to maintain state, an intermediary device is disclosed which retrieves calls to the system from a call queue and iteratively submits the calls to the system. Each call within the queue corresponds to a data item of the data set to be analyzed. As calls are submitted to the system, the intermediary device submits state information within the call reflecting a state of processing the data set. A response to the call includes state information updated based on processing of a data item in the call. Thus, state information is maintained for processing the data set, without requiring persistence of state information within individual execution environments.

Efficient state maintenance for execution environments in an on-demand code execution system

A polling resource management system and methodology for facilitating the management of polling resources for polling message queues. A user interacts with customer applications within a web services system. A polling manager within the web services system utilizes polling resources, such as polling threads, polling assignments, and polling workers to access and implement messages in the message queues. A polling resource manager automatically scales the polling assignments, polling threads, and invoke threads to better utilize the polling resources and to reduce latency experienced by the user when interacting with the customer applications.

Polling resource management system

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North Bend, WA, United States of America

Hans-Philipp Anton Hussels