Google Inc.

Amazon Technologies, Inc.

Vishesh Khemani

Arif Abdulhusein Merchant

Atul Adya

Alexander Shraer

Kfir Lev-Ari

Joseph S Beda, Iii

Cristian Petrescu-Prahova

Luis Felipe Cabrera

David R Richardson

John David Cormie

Robert A Horn

Methods, systems, and apparatus for automatic sharding and load balancing in a distributed data processing system. In one aspect, a method includes determining workload distribution for an application across worker computers and in response to determining a load balancing operation is required: selecting a first worker computer having a highest load measure relative to respective load measure of the other work computers; determining one or more move operations for a partition of data assigned to the first worker computer and a weight for each move operation; and selecting the move operation with a highest weight the selected move operation.

Weighted auto-sharing

Weighted auto-sharding

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a global computing interface. One of the methods includes maintaining a global database of virtual machine configuration information, the database including information on cloud computing resources in each of a plurality of regions, wherein each region of the plurality of regions includes one or more datacenters. A virtual machine image is received in a first region. The global database is updated with configuration information about the received virtual machine image that is stored in the first region. A request is received to start one or more virtual machines from the virtual machine image in a second different region, and the virtual machine image is transmitted from the first region to the second region and one or more virtual machines are started from the virtual machine image in a datacenter of the second different region.

Global computing interface

Techniques for facilitating a client's control over use of computing-related resources on the client's behalf. In some situations, a client's control is based on specifying a group of one or more resource usage constraints with a client resource constraint manager service, which provides information about the client-specified constraints to one or more other remote network services with which the client interacts. Those remote services then use that constraint information to determine whether and how to use computing-related resources on the client's behalf. For example, the resource usage constraints specified by a client may relate to one or more particular geographical areas and/or to one or more measures of relative proximity between computing-related resources (e.g., between multiple instances of a single type of computing-related resource provided by a single service, or between multiple distinct types of computing-related resources provided by multiple unaffiliated services).

Determining computing-related resources to use based on client-specified constraints

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing resources in a computing system. A plurality of distributed computing system resources are represented as nodes in a graph. Links between the nodes are defined, where each link in the links representing ownership or usage by a parent node of a respective resource represented by a child node. A message is sent from a source node in the graph to a target node in the graph wherein the source node is linked directly or indirectly to the target node. The message is processed by a message handler task associated with the target node, wherein processing includes allocating or deallocating a respective resource represented by the target node.

Resource management

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Seattle, WA, United States of America

Vishesh Khemani