Amazon Technologies, Inc.

Blake Meike

Geoffrey Scott Pare

Chiranjeeb Buragohain

Sumit Lohia

John Walter Heitmann

Christopher Reddy Kommareddy

Alex Maclinovsky

Liang Chen

Zachary S Musgrave

Reto Kramer

Venkates Paramasivam Balakrishnan

Christopher Whitaker

Daniel Lee Osiecki

Nishanth Shankaran

Geoffry Scott Pare

Venkates P Balakrishnan

Techniques are described for managing program execution capacity, such as for a group of computing nodes that are provided for executing one or more programs for a user. In some situations, dynamic program execution capacity modifications for a computing node group that is in use may be performed periodically or otherwise in a recurrent manner, such as to aggregate multiple modifications that are requested or otherwise determined to be made during a period of time, and with the aggregation of multiple determined modifications being able to be performed in various manners. Modifications may be requested or otherwise determined in various manners, including based on dynamic instructions specified by the user, and on satisfaction of triggers that are previously defined by the user. In some situations, the techniques are used in conjunction with a fee-based program execution service that executes multiple programs on behalf of multiple users of the service.

Dynamically modifying program execution capacity

A resource provisioning service allows users to provision multiple, different network resources in an atomic manner and with a single call to a resource provisioning service. In some instances, the multiple, different network resources comprise individual types of resources that form a portion of one or more cloud-computing platforms. For instance, one or more entities may host and operate a cloud-computing platform that includes different types of network resources, such a storage service, a load balancing service, a compute service, a security service, or any other similar or different type of network-accessible service.

Provisioning multiple network resources

Techniques are described for managing program execution capacity, such as for a group of computing nodes that are provided for executing one or more programs for a user. In some situations, dynamic program execution capacity modifications for a computing node group that is in use may be performed periodically or otherwise in a recurrent manner, such as to aggregate multiple modifications that are requested or otherwise determined to be made during a period of time. In addition, various operations may be performed to attribute causality information or other responsibility for particular program execution capacity modifications that are performed, including by attributing a single event as causing one capacity modification, and a combination of multiple events as possible causes for another capacity modification. The techniques may in some situations be used in conjunction with a fee-based program execution service that executes multiple programs on behalf of multiple users of the service.

Attributing causality to program execution capacity modifications

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Seattle, WA, United States of America

Blake Meike