Abstract: In an approach for ensuring data protection and control in a distributed hybrid multi-cloud environment with Kubernetes clusters, a processor determines whether a respective quorum of the set of clusters are online. A processor, responsive to determining that a respective quorum of the set of clusters are online, determines whether one or more applications of the cluster are running on another cluster of the set of clusters. A processor, responsive to determining the one or more applications of the cluster are not running on another cluster of the set of clusters, determines whether the cluster is designated as a highest priority cluster. A processor, responsive to determining the cluster is designated as the highest priority cluster, determines whether a main cluster of the set of clusters is online. A processor, responsive to determining the main cluster is online, scales a new custom resource to one (1).

Abstract: A method, system, and computer program product for context relevant data migration to a cloud server with job rescheduling are provided. The method identifies a contextual situation associated with at least a portion of data sets available for migration to a cloud server by a set of data sources. The method identifies an application associated with the contextual situation. A set of use characteristics are determined for the data sets based on the contextual situation and the application. Bandwidths are determined for one or more data sources. One or more data sets are selected for prioritization based on a contextual relevance, the set of use characteristics, and the bandwidths for the one or more data sources. The method schedules a job processing sequence of the selected one or more data sets based, at least in part, on the contextual relevancy, the set of use characteristics, and the bandwidths.

Abstract: In an approach for ensuring data protection and control in a distributed hybrid multi-cloud environment with Kubernetes clusters, a processor determines whether a respective quorum of the set of clusters are online. A processor, responsive to determining that a respective quorum of the set of clusters are online, determines whether one or more applications of the cluster are running on another cluster of the set of clusters. A processor, responsive to determining the one or more applications of the cluster are not running on another cluster of the set of clusters, determines whether the cluster is designated as a highest priority cluster. A processor, responsive to determining the cluster is designated as the highest priority cluster, determines whether a main cluster of the set of clusters is online. A processor, responsive to determining the main cluster is online, scales a new custom resource to one (1).

Abstract: In an approach to improve mobile computation while traveling by dynamically generating one or more routes base on computing resource requirements of one or more endpoint devices. Embodiments identify, in real time, a plurality of autonomous vehicles, wherein the plurality of autonomous vehicles are traveling along a common route. Further embodiments, adjust, in real time, relative positions and speeds of the plurality of autonomous vehicles to maintain the plurality of autonomous vehicles within a predetermined geographic area while traveling along the common route, and wherein the predetermined geographic area is sufficient to collectively provide an amount of edge computing resources to satisfy one or more computing resource requirements of the one or more endpoint devices located within a first autonomous vehicle. Additionally, embodiments adjust, in real time, a route of the first autonomous vehicle based on the common route of the plurality of autonomous vehicles providing the edge computing resources.

Abstract: A computer resource disparity is detected. The computer resource disparity is related to performing a computing task. The computer resource disparity is located proximate to a first location. A set of one or more autonomous vehicles capable of being adjacent to the first location is identified. An autonomous vehicle computing inquiry is generated. The inquiry is generated based on the first location and based on the computer resource disparity. The autonomous vehicle computing inquiry is transmitted based on the first location. An autonomous vehicle status is received in response to the autonomous vehicle computing inquiry that includes a set of one or more computing resources of the set of autonomous vehicles. A first autonomous vehicle of the set of autonomous vehicles is assigned to perform the computing task. The assignment is based on the set of computing resources of the set of autonomous vehicles.

Abstract: An apparatus for generating electricity in a computer rack includes a plurality of thermoelectric generator modules secured in a planar assembly having a first side and a second side, wherein each thermoelectric generator module has a first thermally conductive substrate exposed on the first side of the planar assembly and a second thermally conductive substrate exposed on the second side of the planar assembly, and wherein the plurality of thermoelectric generator modules are operatively coupled in a circuit to supply electrical current. The apparatus further comprises a first duct for directing a first fluid stream across the first side of the planar assembly to supply heat to the first thermally conductive substrate, and a second duct for directing a second fluid stream across the second side of the planar assembly to withdraw heat from the second thermally conductive substrate.