Intel Corporation

Connor Upton

Keith A Ellis

Hugh Martin Carr

David M Boundy

Ronan O'Malley

Joseph Butler

Alexander J Leckey

Katalin Klara Bartfai-Walcott

Slawomir Putyrski

Thijs Metsch

Giovani Estrada

Victor Bayon-Molino

John Kennedy

Grigorios Katsaros

Michael Christopher Woods

Methods, apparatus, systems and articles of manufacture are disclosed to facilitate end-user defined policy management. An example apparatus includes an edge node interface to detect addition of a networked user device to a service gateway, and to extract publish information from the networked user device. The example apparatus also includes a device context manager to identify tag parameters based on the publish information from the networked user device, and a tag manager to prohibit unauthorized disclosure of the networked user device by setting values of the tag parameters based on a user profile associated with a type of the networked user device.

Methods and apparatus to facilitate end-user defined policy management

Techniques for dynamically adapting cloud applications are described. A current value of a Key Performance Indicator (KPI) of an executing cloud service instance of a cloud application is detected. A determination is made as to whether the current value of the KPI is unacceptable (e.g., either it is outside of an acceptable range or is within an adaptation region). If the current value of the KPI is unacceptable, a first application programming interface (API) is invoked to request a cloud service instance monitor to adapt the cloud service instance to operate within an acceptable KPI range. If the cloud service instance monitor was unsuccessful, the unacceptable KPI is escalated to the cloud service monitor for the type of the cloud service instance. If the cloud service monitor is unsuccessful, the unacceptable KPI is escalated to the application monitor.

Dynamically adapting cloud applications

Technologies for datacenter management include one or more computing racks each including a rack controller. The rack controller may receive system, performance, or health metrics for the components of the computing rack. The rack controller generates regression models to predict component lifespan and may predict logical machine lifespans based on the lifespan of the included hardware components. The rack controller may generate notifications or schedule maintenance sessions based on remaining component or logical machine lifespans. The rack controller may compose logical machines using components having similar remaining lifespans. In some embodiments the rack controller may validate a service level agreement prior to executing an application based on the probability of component failure. A management interface may generate an interactive visualization of the system state and optimize the datacenter schedule based on optimization rules derived from human input in response to the visualization. Other embodiments are described and claimed.

Workload optimization, scheduling, and placement for rack-scale architecture computing systems

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County Kildare, Ireland

Connor Upton