A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying a plurality of asset resources within a data center; monitoring workloads within the data center, the monitoring providing data center workload data, the data center workload data including asset resource utilization data; determining whether certain asset resources are underutilized; presenting a load balance configurator user interface, the load balance configurator user interface enabling allocation of asset resources to target workloads; and, performing a data center asset allocation operation, the data center asset allocation operation reallocating workloads in response to the allocation of asset resources to target workloads.

A device may include a memory storing instructions and a processor configured to execute the instructions to receive an instruction from an administration device; identify a link selector in the instruction that corresponds to a resource attribute of a first resource that specifies how a second resource is to be controlled by the first resource; query a database of contracts between resources to determine that the second resource is available to be controlled by the first resource, based on resource contracts associated with the second resource. The processor may be further configured to generate a resource contract between the first resource and the second resource that indicates the second resource is controlled by the first resource and enable the first resource to communicate with the second resource in accordance with the generated resource contract.

Computing resources are managed in a computing environment comprising a computing service provider and an edge computing network. The edge computing network comprises computing and storage devices configured to extend computing resources of the computing service provider to remote users of the computing service provider. The edge computing network collects capacity and usage data for computing and network resources at the edge computing network. The capacity and usage data is sent to the computing service provider. Based on the capacity and usage data, the computing service provider, using a cost function, determines a distribution of workloads pertaining to a processing pipeline that has been partitioned into the workloads. The workloads can be executed at the computing service provider or the edge computing network.

A durability assessment system may receive a request, from a computing system, for a durability index describing an entity. The durability assessment system may determine the durability index based on information about the resource usage by the entity, such as a resource availability score or a resource allocation score. The durability assessment system may compare the obtained resource availability score and resource allocation score to ranges associated with a set of durability indices. Based on the comparison, the durability assessment system may determine a durability index for the entity. The durability index may indicate an ability of the entity to return accessed resources. In some cases, the durability assessment system may provide the durability index to an allocation computing system that is configured to determine whether to grant access to resources based on the durability index.

Managing hybrid cloud resources by grouping at least a portion of the elements of a data set according to attribute sensitivity into a cluster of elements, computing a resource allocation impact of the cluster of elements, computing an information gain associated with the set of elements, and allocating cloud resources according to the resource allocation impact and information gain.

A system and method for robotically arbitrating cloud computing services utilizes resource parameters, tolerance values, and client system requirements to configure a meta-orchestrator to select a validated compatible service from a service resource pool and employ an orchestrator to migrate a client system to the selected service and utilize block chain technology for logging transactions, storing metadata and data.

Systems and methods are described for enabling quantum computing at an edge node of a network. For example, a machine learning component residing on each of a plurality of edge nodes of the network may be implemented to distribute application processing by network location and processing type, including distribution among classical processing at a central cloud, classical processing at an edge node, and quantum processing at a quantum edge node including a quantum computing device. By distributing certain applications, such as latency-sensitive applications of a higher order of complexity, to an edge node, and particularly a quantum edge node, latency may be reduced and complex application code may be processed more quicky using quantum computations. For applications to be processed using quantum processing, the machine learning component may further identify qubits for the quantum processing and define containers based on the qubits for deployment by the quantum computing device.

Implementations are described herein for automatic deployment of function block application programs (FBAPs) across process automation nodes of a process automation system. In various implementations, one or more constraints associated with execution of a FBAP may be identified. Based on the one or more constraints, a process automation system that includes a plurality of process automation nodes may be analyzed. Based on the analysis, a subset of two or more process automation nodes on which to distributively deploy the FBAP may be selected from the plurality of processing node. In response to selecting the subset, the FBAP may be distributively deployed across the two or more process automation nodes of the subset.

A system is provided for enforcing time-based user access levels in a computing infrastructure of an organization. The system includes a processor and a computer readable medium operably coupled thereto, to perform operations which include executing a synchronization of the time-based user access levels, obtaining a first login identifier (ID) of a plurality of login IDs for a group of employees of the organization, identifying a position ID and an employment status ID for the first login ID, determining a current time and a last login timestamp for the first login ID, determining a time-based access rule for the group of employees, determining whether a time period from the last login timestamp to the current time violates the time-based access rule, and setting, for the synchronization of the first login ID, at least a first access level of the first login ID to computing resources.

Methods, apparatuses, systems, and computer program products for facilitating human intervention in an autonomous device are disclosed. In a particular embodiment, a method of facilitating human intervention in an autonomous device includes a service controller selecting from a first plurality of human interventionists, by a service controller, a first set of human interventionists to respond to a request associated with an autonomous device; transmitting, by the service controller, the request to a first set of interventionist devices, each interventionist device of the first set of interventionist devices associated with a particular human interventionist in the first set of human interventionists; and receiving from the first set of interventionist devices, by the service controller, a first set of interventionist responses to the request.