Virtual application and desktop delivery may be optimized by supplying application metadata and user intent to the device between a client and a server hosting resources for the delivery. The data packets used to deliver the virtual application or desktop may be also tagged with references to the application. By supplying the metadata and tagging packets with the metadata, an intermediary network device may provide streams of data packets at the target QoS. In addition, the device may apply network resource allocation rules (e.g., firewalls and QoS configuration) for redirected content retrieved by the client out of band relative to a virtual channel such as the Internet. The network resource allocation rules may differ for different types of resources accessed. The device may also control a delivery agent on the server to modify communication sessions established through the virtual channels based on network conditions.

The present disclosure envisages optimization of a time-sensitive fog network deployed in an industrial environment. The time-sensitive fog network comprises a plurality of fog nodes communicably coupled to a plurality of industrial equipments referenced as endpoints. Each fog node is embodied with a plurality of computer-based resources including computational resources, storage resources, security resources, network resources, application-specific resources, and device-specific resources. The resource constraints that warrant the endpoints to cooperate with specific fog nodes to access specific resources are manifested as a compute profile, a storage profile, a security profile, a network profile, an application-specific profile, and a device-specific profile. The endpoints are optimally provisioned to cooperate with the fog nodes and consume the computer-based resources embodied therein, based on a deployment model that optimally and deterministically correlates the plurality of computer-based resources embodied in each of the fog nodes to the resource profiles attributed to each of the endpoints.

Systems and methods of vertical auto-scaling a networking stack by adjusting the number of packet engines executing on a device are provided. A device intermediary to clients and servers executes first packet engines to process network traffic of a first set of connections. The device determines to adjust the number of packet engines executing on the device based on trigger parameters. The device activates second packet engines to process network traffic for a second set of connections. The device mirrors the network traffic from the first and second set of connections. The first packet engines reject the traffic from the second connections, and the second packet engines reject the traffic from the first connections. The device deactivates the first packet engines when the first connections timeout.

Traffic flow across a backbone network can be determined even though flow data may not be available from all network devices. Flow data can be observed using types of backbone devices, such as aggregation and transit devices. An algorithm can be applied to determine which data to utilize for flow analysis, where this algorithm can be based at least in part upon rules to prevent duplicate accounting of traffic being observed by multiple devices in the backbone network. Such an algorithm can use information such as source address, destination address, and region information to determine which flow data to utilize. In some embodiments, address mapping may be used to attribute this traffic to various services or entities. The data can then be analyzed to provide information about the flow of traffic across the backbone network, which can be useful for purposes such as network optimization and usage allocation.

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.

In one embodiment, an illustrative method herein may comprise: determining, by a device, that a request for an online resource has not yet provisioned the online resource; determining, by the device, one or more errors responsible for the online resource not yet being provisioned; determining, by the device, whether the one or more errors have since been resolved; retrying, by the device and in response to the one or more errors having since been resolved, the request for the online resource to be provisioned; and deferring, by the device and in response to the one or more errors remaining unresolved, an attempt to request that the online resource be provisioned.

A computer-implemented for allocating resources is disclosed. The method includes: receiving, from a client device associated with an entity, input including a selection of a first operation; obtaining a threshold quantity of resources associated with the first operation; allocating a first quantity of resources associated with the entity to the first operation; detecting a trigger condition for obtaining resources associated with the first operation; and in response to detecting the trigger condition for obtaining resources associated with the first operation: determining a second quantity of resources associated with the entity for allocation to the first operation based on a difference between the threshold quantity of resources associated with the first operation and the first quantity of resources; and transmitting, to the client device, a signal representing a message indicating the second quantity of resources.

Disclosed herein are guidance/supervision systems that may utilize guidance and supervision policies from various stakeholders, such as resource owner(s) and service owner(s), to provide guidance, supervision, and introspective analysis for an autonomous system that configures a group of shared resources. The system includes determining, based on predefined preferences associated with shared resources, a set of policies to guide an autonomous system in determining a set of configuration parameters for sharing the shared resources. The system also includes providing the set of policies to the autonomous system to configure the shared resources according to the set of configuration parameters.

A request may be identified having one or more constraints for accessing disaggregated resources in a computing environment. One or more resources in a plurality of disaggregated resources may be identified based on the request. Computing server instances may be dynamically orchestrated using the one or more resources in the plurality of disaggregated resources based on the one or more constraints.

Computing systems, devices, and associated methods of allocating computing resources in a distributed computing system to user requests are disclosed herein. In one example, a method includes when none of unallocated computing resources satisfy a constraint on a physical attribute in a received request for the computing resource, identifying one of the allocated resources in the distributed computing system that satisfies the constraint on the physical attribute and recursively determining whether one of the other allocated or unallocated resources in the distributed computing system that satisfies a constraint of a prior request. In response to determining that none of the allocated or unallocated resources satisfies the constraint of the prior request, assignment of the identified one of the allocated resources to the prior request is maintained.