Providing users with smooth and reliable applications in a cloud based setting is a desirable goal. An approach to pre-allocating cloud computing resources may be provided to improve user experience. A user device may monitor an environment for individual user behaviors with visual and/or audio sensors. Based on data from the visual and/or audio sensors individual behaviors may be identified. Individual behaviors may be identified and associated with a cloud computing resource request. Computing resources in the cloud may be reserved or pre-allocated based on the cloud computing resource request. The pre-allocated computing resources can improve user experience through reduced wait time and improve initial cloud-based application response.

Methods and systems are disclosed for improvements in cloud services by sharing estimated and actual usage data of cloud services recipients with the cloud services provider. The sharing of this data allows the cloud services provider to better apportion cloud resources between multiple cloud services recipients. By analyzing information included in the shared data (e.g., information about one or more applications that use the cloud resources), the cloud services provider may categorize the applications and/or the functions of those applications into authorized and unauthorized uses, the determination of which, is used to further efficiently apportion the cloud services resources.

Cloud infrastructure planning systems and methods can utilize artificial intelligence/machine learning agents for developing a plan of demand, plan of record, plan of execution, and plan of availability for developing cloud infrastructure plans that are more precise and accurate, and that learn from previous planning and deployments. Some agents include one or more of supervised, unsupervised, and reinforcement machine learning to develop accurate predictions and perform self-tuning alone or in conjunction with other agents.

Modifying quality of service treatment for data flows A method of transmitting a data flow via a network is disclosed where the network supports transmission of data in accordance with a plurality of Quality of Service, QoS, models. Prior to transmission of the data flow, a client system configures a first class of service for the data flow based on a first QoS model, and a first portion of the data flow is transmitted through the network in accordance with the first class of service. In response to detecting a renegotiation condition, the network communicates with the client system to configure a second class of service for the data flow based on a second QoS model, and a subsequent portion of the data flow is transmitted through the network using the second class of service.

Technologies for managing configuration-free platform firmware include a compute device, which further includes a management controller. The management controller is to receive a system configuration request to access a system configuration parameter of the compute device and access the system configuration parameter in response to a receipt of the system configuration request.

A RAN node may determine an aggregate signal-to-noise ratio (SNR) of each resource block of a plurality of resource blocks, where the aggregate SNR of a given resource block of the plurality of resource blocks is based on SNRs of subcarrier frequencies of the given resource block. The RAN node may determine, based on a type of network traffic on each network slice of a plurality of network slices, an index value of each network slice of the plurality of network slices. The RAN node may map, based on the aggregate SNR of each resource block, based on the index value of each network slice, and for each resource block of the plurality of resource blocks, a resource block of the plurality of resource blocks to a network slice of the plurality of network slices.

Computer systems and methods for managing resources are described. In an aspect, a method includes: providing, to a client device associated with an authenticated entity, an intraday transfer interface, the intraday transfer interface including a selectable option to issue a future-dated borrowed resource reservation request to set aside an amount of borrowed resources; receiving, from the client device, a signal representing the future-dated borrowed resource reservation request, the future-dated borrowed resource reservation request associated with an amount of borrowed resources to set aside and a date of release of such borrowed resources; detecting a trigger condition, the trigger condition including an end-of-day reconciliation of resource tracking data and, in response to detecting the trigger condition, evaluating the future-dated borrowed resource reservation request based on a current amount of borrowed resources; and when the evaluation of the future-dated borrowed resource reservation request indicates that the future-dated borrowed resource reservation request cannot be implemented, generating an error by sending an error message to a computing device and rejecting the future-dated borrowed resource reservation request.

In a computing environment, a set of executing processes each having associated resources are provided. Aggregate resources for the computing environment include multiple different types of resources. A utilization level for each of the resources within the computing environment is evaluated to determine an unconsumed capacity for each of the resources below a utilization threshold. The utilization threshold is resource-dependent. An indication of at least a portion of unconsumed capacity for each of the resources below the utilization threshold is gathered. The unconsumed portion for each of the resources below the utilization threshold is exposed for consumption by other executing processes.

A method for method for managing a computer network is proposed, which comprises: performing data collection configuration for at least one network node of the computer network belonging to a set of one or more network nodes corresponding to a first depth level of a routing tree, the data collection configuration comprising: receiving respective first configuration data from at least one child node in the routing tree of the at least one network node of the computer network, wherein the at least child node corresponds to a second depth level of the routing tree which immediately follows the first depth level in a sequence of depth levels of the routing tree, and generating second configuration data based on the received first configuration data.

A technique is directed toward controlling placement of workloads of an application within an application environment. The technique involves, while a first placement of workloads of the application is in a first deployment of resources within the application environment, generating a set of resource deployment changes that accommodates a predicted change in demand on the application. The technique further involves adjusting the first deployment of resources within the application environment to form a second deployment of resources within the application environment, the second deployment of resources being different from the first deployment of resources. The technique further involves providing a second placement of workloads of the application in the second deployment of resources to accommodate the predicted change in demand on the application, the second placement of workloads being different from the first placement of workloads.