Intel Corporation

John Kennedy

Joseph Butler

Giovani Estrada

Alexander J Leckey

Katalin Klara Bartfai-Walcott

Slawomir Putyrski

Thijs Metsch

Chris Woods

Michael J McGrath

Victor Bayon-Molino

Connor Upton

Vincenzo Mario Riccobene

Enrique G Castro-Leon

Michael Christopher Woods

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

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

Servers, storage medium and methods associated with control of power management services of remote servers of a remote computing service are disclosed herein. In embodiments, a storage medium may have instructions to enable a local server to query a remote computing service having one or more remote servers. The instructions may enable the local server to receive a record from the remote computing service in response to the query. The record may include information related to power management services available from the one or more remote servers. The instructions may enable the local server to transmit power management commands, based on the information, to the remote computing service to at least partially control power consumption by the one or more remote servers. Other embodiments may be disclosed or claimed.

Power management control of remote servers

Growing community of inventors

Clane, Ireland

John Kennedy