Amazon Web Services Apr 1, 2014 - Apr 2016
Senior Manager, Software Development, Amazon Web Services
Google Apr 1, 2014 - Apr 2016
Engineering Manager
Amazon Web Services Mar 2010 - Apr 2014
Software Development Manager, Aws Monitoring
Amazon Jan 2008 - Mar 2010
Software Development Manager, Ec2 Autoscaling
Amazon May 2004 - Dec 2007
Software Development Engineer, Amazon
Education:
The Institute of Chartered Accountants of India
Carnegie Mellon University
Bachelors, Bachelor of Science, Computer Engineering
Carnegie Mellon University
Master of Science, Masters, Computer Engineering
Skills:
Amazon Web Services Distributed Systems Software Development Scalability Cloud Computing Operating Systems Software Engineering Amazon Ec2 Agile Methodologies Perl People Management
Alex Maclinovsky - Bellevue WA, US Blake Meike - Seattle WA, US Chiranjeeb Buragohain - Seattle WA, US Christopher Reddy Kommareddy - Lynnwood WA, US Geoffrey Scott Pare - Seattle WA, US John W. Heitmann - Seattle WA, US Sumit Lohia - Seattle WA, US Liang Chen - Mercer Island WA, US Zachary S. Musgrave - Seattle WA, US
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.
Attributing Causality To Program Execution Capacity Modifications
Alex Maclinovsky - Bellevue WA, US Blake Meike - Seattle WA, US Chiranjeeb Buragohain - Seattle WA, US Christopher Reddy Kommareddy - Lynnwood WA, US Geoffry Scott Pare - Seattle WA, US John W. Heitmann - Seattle WA, US Sumit Lohia - Seattle WA, US Liang Chen - Mercer Island WA, US
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.
Alex Maclinovsky - Bellevue WA, US Blake Meike - Seattle WA, US Chiranjeeb Buragohain - Seattle WA, US Christopher Reddy Kommareddy - Lynnwood WA, US Geoffry Scott Pare - Seattle WA, US John W. Heitmann - Seattle WA, US Sumit Lohia - Seattle WA, US Liang Chen - Mercer Island WA, US Zachary S. Musgrave - Seattle WA, US
International Classification:
G06F 15/16
US Classification:
709203
Abstract:
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.
Elastic Application Framework For Deploying Software
Software is deployed to, and executed at, one or more computing devices in a computing system based on current conditions in the computing system and the capabilities of the different computing devices to handle the software. A request to run a software process calls a manager which determines an optimal place to run the software process. The manager can consider factors such as response time, user demands, bandwidth, processor utilization, storage utilization, security considerations, compatibility considerations and cost. Once a computing device is selected to run the software process, the manager facilitates movement of code and/or data to the computing device.
Elastic Application Framework For Deploying Software
Software is deployed to, and executed at, one or more computing devices in a computing system based on current conditions in the computing system and the capabilities of the different computing devices to handle the software. A request to run a software process calls a manager which determines an optimal place to run the software process. The manager can consider factors such as response time, user demands, bandwidth, processor utilization, storage utilization, security considerations, compatibility considerations and cost. Once a computing device is selected to run the software process, the manager facilitates movement of code and/or data to the computing device.
Elastic Application Framework For Deploying Software
Software is deployed to, and executed at, one or more computing devices in a computing system based on current conditions in the computing system and the capabilities of the different computing devices to handle the software. A request to run a software process calls a manager which determines an optimal place to run the software process. The manager can consider factors such as response time, user demands, bandwidth, processor utilization, storage utilization, security considerations, compatibility considerations and cost. Once a computing device is selected to run the software process, the manager facilitates movement of code and/or data to the computing device.
- Reno NV, US Blake Meike - Seattle WA, US Chiranjeeb Buragohain - Seattle WA, US Christopher Reddy Kommareddy - Lynnwood WA, US Geoffrey Scott Pare - Seattle WA, US John W. Heitmann - Seattle WA, US Sumit Lohia - Seattle WA, US Liang Chen - Mercer Island WA, US Zachary S. Musgrave - Seattle WA, US
International Classification:
G06F 9/50 G06F 9/48
Abstract:
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.
System And Method For Configuration Management Service
- Reno NV, US SUMIT LOHIA - SEATTLE WA, US THOMAS WILLIAM WHITCOMB - SEATTLE WA, US KENNETH L. HAMER - SEATTLE WA, US EVAN MICHAEL MCLAIN - SEATTLE WA, US
Assignee:
Amazon Technologies, Inc. - Reno NV
International Classification:
H04L 12/24 H04L 29/08
Abstract:
System and method for agentless computing system configuration management in networked environments. A configuration management service may be implemented as a service on a network with a standard network interface. A client may communicate with the service to specify a configuration for a target system, for example through a browser interface. The specified configuration may be stored by the service. The service may generate a package according to the specified configuration. The package may be delivered to the target system via the network. The package may then install the configuration, for example, one or more software, data, or other digital components, on the target systems in accordance with the specified configuration. The clients may request that the service verify and/or update the installed configuration on the target system. The service may, in response, generate an update package for the installed configuration. Target systems may include computer systems and virtual machines.