Abstract: Methods and systems for provisioning resources includes classifying a request for a virtual server instance (VSI) according to resources specified in the request. Dependent resources that the VSI will use are predicted based on the specified resources. A provisioning plan is generated, including timing and configuration information, based on the specified resources and the dependent resources. Resources for the VSI are provisioned according to the provisioning plan, including allocating hardware resources on a computing system.

Abstract: Methods and systems for provisioning resources includes classifying a request for a virtual server instance (VSI) according to resources specified in the request. Dependent resources that the VSI will use are predicted based on the specified resources. A provisioning plan is generated, including timing and configuration information, based on the specified resources and the dependent resources. Resources for the VSI are provisioned according to the provisioning plan, including allocating hardware resources on a computing system.

Abstract: Embodiments of the invention provide a computer system that includes a central processing unit (CPU) associated with a host computer. The CPU includes CPU functionality and on-board enhanced CPU functionality. The CPU further includes a virtualized first instance of the CPU comprising an enabled virtualized first instance of the CPU functionality; and a non-enabled virtualized first instance of the on-chip enhanced CPU functionality. The CPU further includes a virtualized second instance of the CPU comprising an enabled virtualized second instance of the CPU functionality; and an enabled virtualized second instance of the on-chip enhanced CPU functionality.

Abstract: A method, system and computer program product for processing metrics data with graph data context analysis. Graph data representing one or more devices or sensors is stored into a first database, and metrics data generated by the devices or sensors is stored in a second database. The metrics data is then applied to the graph data for the context analysis, wherein the context analysis reflects the relationships of the devices or sensors in the graph data to the metrics data generated by the devices or sensors. The graph data comprises nodes for representing the devices or sensors, edges for representing a topology of the devices or sensors, and properties for storing the metrics data associated with the nodes and edges; and the metrics data comprises time-series data that is logged by the devices and sensors.

Abstract: A processor initiates a run of a target container in a distributed computing environment. A processor detects at least one error occurring during the initiation of the target container. A processor determines at least one fix image based on the at least one error. A processor performs an error recovery of the target container based on the at least one fix image. A processor runs, in response to successfully performing the error recovery of the target container, the target container in the distributed computing environment.

Abstract: A processor initiates a run of a target container in a distributed computing environment. A processor detects at least one error occurring during the initiation of the target container. A processor determines at least one fix image based on the at least one error. A processor performs an error recovery of the target container based on the at least one fix image. A processor runs, in response to successfully performing the error recovery of the target container, the target container in the distributed computing environment.

Abstract: A method, system and computer program product for processing metrics data with graph data context analysis. Graph data representing one or more devices or sensors is stored into a first database, and metrics data generated by the devices or sensors is stored in a second database. The metrics data is then applied to the graph data for the context analysis, wherein the context analysis reflects the relationships of the devices or sensors in the graph data to the metrics data generated by the devices or sensors. The graph data comprises nodes for representing the devices or sensors, edges for representing a topology of the devices or sensors, and properties for storing the metrics data associated with the nodes and edges; and the metrics data comprises time-series data that is logged by the devices and sensors.

Abstract: An approach for recommending activating a safety feature on a mobile device in a vehicle. The approach includes collecting sound characteristics. Furthermore, determining if the mobile device is moving faster than a predetermined velocity and invoking grouping service on a server. The approach determines the number of the mobile device in the vehicle and determines which one of the one or more of the mobile devices belongs to the user operating the vehicle and activating a safe drive mode feature on the mobile device belonging to the user of the vehicle.