Methods and apparatus to execute a workload in an edge environment are disclosed. An example apparatus includes a node scheduler to accept a task from a workload scheduler, the task including a description of a workload and tokens, a workload executor to execute the workload, the node scheduler to access a result of execution of the workload and provide the result to the workload scheduler, and a controller to access the tokens and distribute at least one of the tokens to at least one provider, the provider to provide a resource to the apparatus to execute the workload.

The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines, each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit to determine an amount of a resource for each of the machines to service the task requirement for each machine, a forward resource market circuit to access a forward resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the forward resource market.

Local management of data stream throttling in data movement operations, such as secondary-copy operations in a storage management system, is disclosed. A local throttling manager may interoperate with co-resident data agents and/or a media agent executing on any given local computing device, whether a client computing device or a secondary storage computing device. The local throttling manager may allocate and manage the available bandwidth for various jobs and their constituent data streams—across the data agents and/or media agent. Bandwidth is allocated and re-allocated to data streams used by ongoing jobs, in response to new jobs starting and old jobs completing, without having to pause and restart ongoing jobs to accommodate bandwidth adjustments. The illustrative embodiment also provides local users with a measure of control over data streams—to suspend, pause, and/or resume them—independently from the centralized storage manager that manages the overall storage system.

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.

Methods, apparatuses and computer program products for implementing dynamic retry of a resource service in a network system are provided. An example method may include: transmitting a first service request to the resource service, determining a first service availability indicator, calculating a first service availability estimate associated with the resource service based on the first service availability indicator, and determining whether to transmit a second service request based on the first service availability estimate. The example method may be repeated by an example apparatus continuously for each transmitted service request.

Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with a local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment. The event can be a threshold or a triggering event within or outside of the local environment.

In one example, the present disclosure describes a device, computer-readable medium, and method for scaling network capacity predictively, based on customer interest. For instance, in one example, a method includes predicting an interest of a first customer in data content that will be available for consumption over a data network at a time in the future, wherein the predicting is based on customer data including at least a search pattern associated with the first customer, flagging the data content when the predicting indicates at least a threshold degree of likelihood that the first customer will be interested in the data content, and scaling an allocation of resources of the data network to the first customer, based on the flagging.

Techniques are provided for allocation of shared computing resources using source code feature extraction and machine learning techniques. An exemplary method comprises obtaining source code for execution in a shared computing environment; extracting a plurality of discriminative features from the source code; obtaining a trained machine learning model; and generating a prediction of an allocation of one or more resources of the shared computing environment needed to satisfy one or more service level agreement requirements for the source code. The generated prediction is optionally adjusted using a statistical analysis of an error curve, based on one or more error boundaries obtained by the trained machine learning model. The trained machine learning model can be trained using a set of discriminative features extracted from training source code and corresponding measurements of metrics of the service level agreement requirements obtained by executing the training source code on a plurality of the resources of the shared computing environment.

A system comprises a plurality of computing devices that are communicatively coupled via a network and have a file system distributed among them, and comprises one or more file system request buffers residing on one or more of the plurality of computing devices. File system choking management circuitry that resides on one or more of the plurality of computing devices is operable to separately control: a first rate at which a first type of file system requests (e.g., one of data requests, data read requests, data write requests, metadata requests, metadata read requests, and metadata write requests) are fetched from the one or more buffers , and a second rate at which a second type of file system requests (e.g., another of data requests, data read requests, data write requests, metadata requests, metadata read requests, and metadata write requests) are fetched from the one or more buffers.

Concepts and technologies directed to agile transport for background traffic in cellular networks are disclosed herein. In various aspects, a system can include a processor and memory storing instructions that, upon execution, cause performance of operations. The operations can include determining a capacity of a communication path that communicatively couples a user equipment to a radio access network cell site. The operations can include identifying, from the radio access network cell site, a queue that is constructed for the user equipment. The operations can include assembling a plurality of probe burst packet sets from a background traffic flow. The operations can include probing the communication path for spare capacity using the plurality of probe burst packet sets and delivering the background traffic flow to the user equipment using the spare capacity while the communication path is not busy.