Intel Corporation

Alexander J Leckey

Joseph Butler

Giovani Estrada

Thijs Metsch

John Kennedy

Katalin Klara Bartfai-Walcott

Slawomir Putyrski

Vincenzo Mario Riccobene

Annie Ibrahim Rana

Connor Upton

Chris Woods

Chris MacNamara

Stephen T Palermo

Niall D McDonnell

Tomasz Kantecki

Pierre Laurent

Patrick Fleming

Michael J McGrath

Andrew Cunningham

Mark D Gray

Victor Bayon-Molino

David Fleming

Ivan P Harrow

Dermot E Honan

Grigorios Katsaros

Michael Christopher Woods

Edward Shogulin

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

An input/output (I/O) device arranged to receive an information element including a payload, determine control information from the information element, classify the information element based on the control information, and issue a write to one of a plurality of computer-readable media based on the classification of the information element, the write to cause the payload to be written to the one of the plurality of computer-readable media.

Techniques for cache delivery

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

One embodiment provides an apparatus. The apparatus includes ranker logic. The ranker logic is to rank each of a plurality of compute nodes in a data center based, at least in part, on a respective node score. Each node score is determined based, at least in part, on a utilization (U), a saturation parameter (S) and a capacity factor (C). The capacity factor is determined based, at least in part, on a sold capacity (C) related to the compute node. The ranker logic is further to select one compute node with a highest node score for placement of a received workload.

Ranking system

A system comprises a scoring engine comprising at least one processor and memory. The scoring engine is to generate, based on telemetry information obtained from a plurality of nodes of a computing infrastructure, a first availability score for a first node of the plurality of computing infrastructure nodes and a second availability score for a second node of the plurality of computing infrastructure nodes. The scoring engine is further to generate, based on the first availability score of the first computing infrastructure node and the second availability score of the second computing infrastructure node, an edge tension score for a link between the first node and the second node.

Computing infrastructure optimizations based on tension levels between computing infrastructure nodes

Examples may include techniques for allocating configurable computing resources from a pool of configurable computing resources to a logical server or virtual machine. The logical server or virtual machine may use allocated configurable computing resources to implement, execute or run a workload.

Techniques to allocate configurable computing resources

Examples are described for computing resource discovery and management for a system of configurable computing resources that may include disaggregate physical elements such as central processing units, storage devices, memory devices, network input/output devices or network switches. In some examples, these disaggregate physical elements may be located within one or more racks of a data center.

Techniques for computing resource discovery and management in a data center

An embodiment includes an automatic policy managed password management system. One embodiment manages changing the password (with little to no user interaction) every set number of days. Also, password changes can be made within a set amount of time from the password being viewed by a user. Further, an embodiment includes a web service that contains an 'insert record' method to insert a password management record into a managed machine and/or database with no 'pre-work' required to use the web service. For example, no record needs to be created on a database and/or managed machines in advance of deploying passwords via the web service. The web service can be pushed to various machines and when the web service starts up, it may insert its own record into a database or managed client. This allows for scalability. Other embodiments are described herein.

Automated password management

Methods and apparatus for peer-to-peer services are disclosed. The apparatus and methods may include presenting at the client a link pointing to a file that resides at a first location represented by the link, receiving an indication that the link has been selected and receiving a representation of the first location. The methods and apparatus may also include determining if a second location stores a copy of the file stored at the first location, receiving a representation of the second location if the copy is stored in the second location, in response to receiving the representation of the second location, requesting download of the copy from the second location and if the copy is not stored in the second location, requesting download of the file from the first location.

Methods and apparatus for peer-to-peer services

Growing community of inventors

Lucan, Ireland

Alexander J Leckey