RICHARD REX COLE
Pilots at Roy St, Seattle, WA

8321558, Nov 27, 2012

Mar 31, 2009

12/415773

Peter Sirota - Seattle WA, US
Richendra Khanna - Seattle WA, US
Ian P. Nowland - Seattle WA, US
Richard J. Cole - Seattle WA, US
Jai Vasanth - Bellevue WA, US
Andrew J. Hitchcock - Seattle WA, US
Luis Felipe Cabrera - Bellevue WA, US

Amazon Technologies, Inc. - Reno NV

G06F 15/16

709224, 709201, 709221, 718 1, 718100

Techniques are described for managing distributed execution of programs. In some situations, the techniques include dynamically monitoring the ongoing distributed execution of a program on a cluster of multiple computing nodes, and may include automatically determining the status of execution of the program on each of the multiple computing nodes and/or automatically determining the aggregate usage of one or more types of computing resources across the cluster of multiple computing nodes by the distributed program execution. The information obtained from the dynamic monitoring may be used in various manners, including to facilitate dynamically modifying the ongoing distributed program execution in various manners, such as to temporarily throttle usage of computing resources by the distributed program execution (e. g. , to remove or reduce one or more bottlenecks).

8296419, Oct 23, 2012

Mar 31, 2009

12/415725

Richendra Khanna - Seattle WA, US
Peter Sirota - Seattle WA, US
Ian P. Nowland - Seattle WA, US
Richard J. Cole - Seattle WA, US
Jai Vasanth - Bellevue WA, US
Andrew J. Hitchcock - Seattle WA, US
Luis Felipe Cabrera - Bellevue WA, US

Amazon Technologies, Inc. - Reno NV

G06F 15/16

709224, 709201, 709221, 718 1, 718100

Techniques are described for managing distributed execution of programs. In some situations, the techniques include dynamically modifying the distributed program execution in various manners, such as based on monitored status information. The dynamic modifying of the distributed program execution may include adding and/or removing computing nodes from a cluster that is executing the program, modifying the amount of computing resources that are available for the distributed program execution, terminating or temporarily suspending execution of the program (e. g. , if an insufficient quantity of computing nodes of the cluster are available to perform execution), etc.

8260840, Sep 4, 2012

Jun 28, 2010

12/825073

Peter Sirota - Seattle WA, US
Richard J. Cole - Seattle WA, US
Vaibhav Aggarwal - Seattle WA, US
Andrew J. Hitchcock - Seattle WA, US
Jai Vasanth - Bellevue WA, US

Amazon Technologies, Inc. - Reno NV

G06F 15/16

709201, 709225, 709209, 709204, 709202, 709219, 709224, 370216, 370397, 370409, 370218, 725 93, 725 94, 725 97, 718100, 718105, 705 64, 705 75

Techniques are described for managing distributed execution of programs, including by dynamically scaling a cluster of multiple computing nodes used to perform ongoing distributed execution of a program, such as to increase and/or decrease the quantity of computing nodes in the cluster at various times and for various reasons. An architecture may be used that facilitates the dynamic scaling of a cluster, including by having at least some of the computing nodes act as core nodes that each participate in a distributed storage system for the distributed program execution, and having one or more other computing nodes that act as auxiliary nodes that do not participate in the distributed storage system. If computing nodes are selected to be removed from the cluster during ongoing distributed execution of a program, one or more nodes of the auxiliary computing node type may be selected for the removal.

2013021, Aug 15, 2013

Feb 14, 2012

13/396479

James P. Bartlett - Seattle WA, US
Richard J. Cole - Seattle WA, US
Adam D. Gray - Seattle WA, US
Peter Sirota - Seattle WA, US

G06F 15/177

709220

Techniques are described for providing clients with access to functionality for creating, configuring and executing defined workflows that manipulate source data in defined manners, such as under the control of a configurable workflow service that is available to multiple remote clients over one or more public networks. A defined workflow for a client may, for example, include multiple interconnected workflow components that are specified by the client and that each are configured to perform one or more types of data manipulation operations on a specified type of input data. The configurable workflow service may further execute the defined workflow at one or more times and in one or more manners, such as in some situations by provisioning multiple computing nodes provided by the configurable workflow service to each implement at least one of the workflow components for the defined workflow.

2013019, Jul 25, 2013

Jan 9, 2013

13/737815

Amazon Technologies, Inc. - Reno NV, US
Ian P. Nowland - Seattle WA, US
Richard J. Cole - Seattle WA, US
Richendra Khanna - Seattle WA, US
Luis Felipe Cabrera - Bellevue WA, US

Amazon Technologies, Inc. - Reno NV

G06F 9/48

718108

Techniques are described for managing distributed execution of programs. In at least some situations, the techniques include decomposing or otherwise separating the execution of a program into multiple distinct execution jobs that may each be executed on a distinct computing node, such as in a parallel manner with each execution job using a distinct subset of input data for the program. In addition, the techniques may include temporarily terminating and later resuming execution of at least some execution jobs, such as by persistently storing an intermediate state of the partial execution of an execution job, and later retrieving and using the stored intermediate state to resume execution of the execution job from the intermediate state. Furthermore, the techniques may be used in conjunction with a distributed program execution service that executes multiple programs on behalf of multiple customers or other users of the service.