Abstract: A method, computer-readable medium, and system for provisioning computing resources across multiple cloud providers and/or data centers are disclosed. A graphical user interface is used to select a plurality of computing resources and at least one cloud provider and/or at least one data center for providing the plurality of computing resources. Scripts associated with the at least one cloud provider and/or at least one data center are accessed, where each script is capable of automatically setting up a computing resource on an associated cloud provider or associated data center. The scripts are then used to automatically allocate and/or configure the computing resources on the at least one cloud provider and/or at least one data center. As such, computing resources can be automatically provisioned using a generic graphical user interface and without a user having skills or credentials specific to each cloud provider and/or data center.

Abstract: A method, computer-readable medium, and system for provisioning computing resources across multiple cloud providers and/or data centers are disclosed. A graphical user interface is used to select a plurality of computing resources and at least one cloud provider and/or at least one data center for providing the plurality of computing resources. Scripts associated with the at least one cloud provider and/or at least one data center are accessed, where each script is capable of automatically setting up a computing resource on an associated cloud provider or associated data center. The scripts are then used to automatically allocate and/or configure the computing resources on the at least one cloud provider and/or at least one data center. As such, computing resources can be automatically provisioned using a generic graphical user interface and without a user having skills or credentials specific to each cloud provider and/or data center.

Abstract: A method, computer-readable medium, and system for monitoring usage of computing resources provisioned across multiple cloud providers and/or data centers are disclosed. Events associated with usage of a plurality of computing resources may be accessed, where the plurality of computing resources may implement a virtual machine, a plurality of virtual machines of a cloud computing environment, etc. The events may be associated with a start, a stop, a status change, etc., of the plurality of computing resources. The events may be used to generate usage data for the plurality of computing resources. The usage data may include historical data associated with previous usage of the plurality of computing resources. Additionally, the usage data may be displayed using a graphical user interface, thereby enabling monitoring and/or tracking of usage of computing resources provisioned across at least one cloud provider and/or at least one data center.

Abstract: A method, computer-readable medium, and system for provisioning computing resources across multiple cloud providers and/or data centers are disclosed. A graphical user interface is used to select a plurality of computing resources and at least one cloud provider and/or at least one data center for providing the plurality of computing resources. Scripts associated with the at least one cloud provider and/or at least one data center are accessed, where each script is capable of automatically setting up a computing resource on an associated cloud provider or associated data center. The scripts are then used to automatically allocate and/or configure the computing resources on the at least one cloud provider and/or at least one data center. As such, computing resources can be automatically provisioned using a generic graphical user interface and without a user having skills or credentials specific to each cloud provider and/or data center.

Abstract: A method, computer-readable medium, and system for provisioning computing resources across multiple cloud providers and/or data centers are disclosed. A graphical user interface is used to select a plurality of computing resources and at least one cloud provider and/or at least one data center for providing the plurality of computing resources. Scripts associated with the at least one cloud provider and/or at least one data center are accessed, where each script is capable of automatically setting up a computing resource on an associated cloud provider or associated data center. The scripts are then used to automatically allocate and/or configure the computing resources on the at least one cloud provider and/or at least one data center. As such, computing resources can be automatically provisioned using a generic graphical user interface and without a user having skills or credentials specific to each cloud provider and/or data center.

Abstract: A method, computer-readable medium, and system for provisioning computing resources across multiple cloud providers and/or data centers are disclosed. A graphical user interface is used to select a plurality of computing resources and at least one cloud provider and/or at least one data center for providing the plurality of computing resources. Scripts associated with the at least one cloud provider and/or at least one data center are accessed, where each script is capable of automatically setting up a computing resource on an associated cloud provider or associated data center. The scripts are then used to automatically allocate and/or configure the computing resources on the at least one cloud provider and/or at least one data center. As such, computing resources can be automatically provisioned using a generic graphical user interface and without a user having skills or credentials specific to each cloud provider and/or data center.

Abstract: The distributed metering and monitoring service (DMMS) system provides a way to gather and maintain metrics data which remains distributed, until requested. The DMMS system uses messaging queues to scale the number of servers that may be monitored and metered to a hyperscale of greater than 10,000 servers. The DMMS system determines how many servers (nodes) to assign to a cluster, and uses a metric aggregator to collect and store metrics data for the nodes. The DMMS system creates message queues for the instances, injects instance identifiers into the cluster state data and metrics data, listens for request messages for metering information for instances, retrieves the metrics data for users identified by the instance identifiers stored locally at the nodes, and calculates the metering information for the instance.

Abstract: A method, computer-readable medium, and system for monitoring usage of computing resources provisioned across multiple cloud providers and/or data centers are disclosed. Events associated with usage of a plurality of computing resources may be accessed, where the plurality of computing resources may implement a virtual machine, a plurality of virtual machines of a cloud computing environment, etc. The events may be associated with a start, a stop, a status change, etc., of the plurality of computing resources. The events may be used to generate usage data for the plurality of computing resources. The usage data may include historical data associated with previous usage of the plurality of computing resources. Additionally, the usage data may be displayed using a graphical user interface, thereby enabling monitoring and/or tracking of usage of computing resources provisioned across at least one cloud provider and/or at least one data center.

Abstract: The distributed metering and monitoring service (DMMS) system provides a way to gather and maintain metrics data which remains distributed, until requested. The DMMS system uses messaging queues to scale the number of servers that may be monitored and metered to a hyperscale of greater than 10,000 servers. The DMMS system determines how many servers (nodes) to assign to a cluster, and uses a metric aggregator to collect and store metrics data for the nodes. The DMMS system creates message queues for the instances, injects instance identifiers into the cluster state data and metrics data, listens for request messages for metering information for instances, retrieves the metrics data for users identified by the instance identifiers stored locally at the nodes, and calculates the metering information for the instance.

Abstract: A method, computer-readable medium, and system for monitoring usage of computing resources provisioned across multiple cloud providers and/or data centers are disclosed. Events associated with usage of a plurality of computing resources may be accessed, where the plurality of computing resources may implement a virtual machine, a plurality of virtual machines of a cloud computing environment, etc. The events may be associated with a start, a stop, a status change, etc., of the plurality of computing resources. The events may be used to generate usage data for the plurality of computing resources. The usage data may include historical data associated with previous usage of the plurality of computing resources. Additionally, the usage data may be displayed using a graphical user interface, thereby enabling monitoring and/or tracking of usage of computing resources provisioned across at least one cloud provider and/or at least one data center.

Abstract: The distributed metering and monitoring service (DMMS) system provides a way to gather and maintain metrics data which remains distributed, until requested. The DMMS system uses messaging queues to scale the number of servers that may be monitored and metered to a hyperscale of greater than 10,000 servers. The DMMS system determines how many servers (nodes) to assign to a cluster, and uses a metric aggregator to collect and store metrics data for the nodes. The DMMS system creates message queues for the instances, injects instance identifiers into the cluster state data and metrics data, listens for request messages for metering information for instances, retrieves the metrics data for users identified by the instance identifiers stored locally at the nodes, and calculates the metering information for the instance.

Abstract: A graphical user interface may be used to display a plurality of computing resources which are provisioned across at least one cloud provider and/or at least one data center, where the plurality of computing resources may implement a virtual machine, a plurality of virtual machines of a cloud computing environment, etc. In response to a selection of the computing resources using the graphical user interface, the plurality of computing resources may be launched and/or configured on the at least one cloud provider and/or at least one data center which provide the computing resources. Access to the plurality of computing resources may then be provided using the graphical user interface.

Abstract: A method, computer-readable medium, and system for provisioning computing resources across multiple cloud providers and/or data centers are disclosed. A graphical user interface is used to select a plurality of computing resources and at least one cloud provider and/or at least one data center for providing the plurality of computing resources. Scripts associated with the at least one cloud provider and/or at least one data center are accessed, where each script is capable of automatically setting up a computing resource on an associated cloud provider or associated data center. The scripts are then used to automatically allocate and/or configure the computing resources on the at least one cloud provider and/or at least one data center. As such, computing resources can be automatically provisioned using a generic graphical user interface and without a user having skills or credentials specific to each cloud provider and/or data center.

Abstract: A method, computer-readable medium, and system for provisioning computing resources across multiple cloud providers and/or data centers are disclosed. A graphical user interface is used to select a plurality of computing resources and at least one cloud provider and/or at least one data center for providing the plurality of computing resources. Scripts associated with the at least one cloud provider and/or at least one data center are accessed, where each script is capable of automatically setting up a computing resource on an associated cloud provider or associated data center. The scripts are then used to automatically allocate and/or configure the computing resources on the at least one cloud provider and/or at least one data center. As such, computing resources can be automatically provisioned using a generic graphical user interface and without a user having skills or credentials specific to each cloud provider and/or data center.

Abstract: A method, computer-readable medium, and system for monitoring usage of computing resources provisioned across multiple cloud providers and/or data centers are disclosed. Events associated with usage of a plurality of computing resources may be accessed, where the plurality of computing resources may implement a virtual machine, a plurality of virtual machines of a cloud computing environment, etc. The events may be associated with a start, a stop, a status change, etc., of the plurality of computing resources. The events may be used to generate usage data for the plurality of computing resources. The usage data may include historical data associated with previous usage of the plurality of computing resources. Additionally, the usage data may be displayed using a graphical user interface, thereby enabling monitoring and/or tracking of usage of computing resources provisioned across at least one cloud provider and/or at least one data center.

Abstract: The distributed computing backup and recovery (DCBR) system and method provide backup and recovery for distributed computing models (e.g., NoSQL). The DCBR system extends the protections from server node-level failure and introduces persistence in time so that the evolving data set may be stored and recovered to a past point in time. The DCBR system, instead of performing backup and recovery for an entire dataset, may be configured to apply to a subset of data. Instead of keeping or recovering snapshots of the entire dataset which requires the entire cluster, the DCBR system identifies the particular nodes and/or archive files where the dataset resides so that backup or recovery may be done with a much smaller number of nodes.

Abstract: A method, computer-readable medium, and system for monitoring usage of computing resources provisioned across multiple cloud providers and/or data centers are disclosed. Events associated with usage of a plurality of computing resources may be accessed, where the plurality of computing resources may implement a virtual machine, a plurality of virtual machines of a cloud computing environment, etc. The events may be associated with a start, a stop, a status change, etc., of the plurality of computing resources. The events may be used to generate usage data for the plurality of computing resources. The usage data may include historical data associated with previous usage of the plurality of computing resources. Additionally, the usage data may be displayed using a graphical user interface, thereby enabling monitoring and/or tracking of usage of computing resources provisioned across at least one cloud provider and/or at least one data center.

Abstract: Methods, systems, and apparatus, including computer program products, for generating feedback. In one aspect, a method includes receiving sensor data from a plurality of sensors, wherein at least one of the plurality of sensors is associated with a mobile device of a user; aggregating the received sensor data to generate aggregated sensor data; processing the aggregated sensor data to determine an aggregated metric; comparing the aggregated metric to a target associated with the user to determine a measure of performance; and generating feedback based on the determined measure of performance. Further, the mobile device can comprise a mobile personal services device that includes one or more of an audio sensor, a video sensor, an environmental sensor, a biometric sensor, a location sensor, an activity detector, and a health monitor. The feedback can be displayed on the mobile personal services device. The feedback also can be displayed in near real-time.

Abstract: The distributed computing backup and recovery (DCBR) system and method provide backup and recovery for distributed computing models (e.g., NoSQL). The DCBR system extends the protections from server node-level failure and introduces persistence in time so that the evolving data set may be stored and recovered to a past point in time. The DCBR system, instead of performing backup and recovery for an entire dataset, may be configured to apply to a subset of data. Instead of keeping or recovering snapshots of the entire dataset which requires the entire cluster, the DCBR system identifies the particular nodes and/or archive files where the dataset resides so that backup or recovery may be done with a much smaller number of nodes.

Abstract: The distributed metering and monitoring service (DMMS) system provides a way to gather and maintain metrics data which remains distributed, until requested. The DMMS system uses messaging queues to scale the number of servers that may be monitored and metered to a hyperscale of greater than 10,000 servers. The DMMS system determines how many servers (nodes) to assign to a cluster, and uses a metric aggregator to collect and store metrics data for the nodes. The DMMS system creates message queues for the instances, injects instance identifiers into the cluster state data and metrics data, listens for request messages for metering information for instances, retrieves the metrics data for users identified by the instance identifiers stored locally at the nodes, and calculates the metering information for the instance.