The present disclosure is directed to systems and methods for transport resource allocation using a centralized control policy, the methods including the steps of receiving node characteristics associated with a plurality of nodes; receiving a centralized policy configuration associated with at least one control policy to be applied based on a set of match conditions; identifying a one or more nodes from the plurality of nodes that satisfy, or that are associated with one or more tunnels that satisfy, the set of match conditions; and applying the at least one control policy to the one or more nodes that satisfy, or to the one or more tunnels that satisfy, the set of match conditions, wherein the at least one control policy is configured to override at least one locally-configured bidirectional forwarding detection (BFD) timer; and/or set a maximum number of tunnels for provisioning at the identified one or more nodes.

Aspects of the disclosure relate to application mapping and alerting based on data dependencies in business and technology logic. In some embodiments, a computing platform may receive a request to map enterprise technology resources. Then, the computing platform may generate a business capability model. Next, the computing platform may cause a user computing device to display a graphical user interface comprising selectable graphical representations of applications associated with the enterprise technology resources. Then, the computing platform may receive a user input identifying an occurrence of a technology incident by selecting one of the graphical representations. In response to the selection, the computing platform may trace, using the generated business capability model, upstream or downstream impacts of the technology incident. Then, the computing platform may cause a visual representation of data dependencies indicating upstream or downstream impacts of the technology incident to be displayed on the user computing device.

A plurality of serverless function invocations are received. A quantity of serverless function invocations of the plurality of serverless function invocations that corresponds to a particular type of serverless function invocation are determined. A number of serverless functions are scaled at a determined rate in view of the quantity of serverless function invocations corresponding to the particular type of serverless function invocation.

A method of determining trigger conditions for scaling a scalable unit of network function comprising identifying a primary set of metrics associated with usage of an instance of the unit of network function as a primary indicator of occurrence of a load state thereof, and determining usage points when the primary indicator indicates that the load state occurs. Deriving a secondary set of the metrics, different to the primary set, as a secondary indicator of occurrence of the load state of the instance at each of a group of one or more of the usage points when the primary indicator indicates that the load state occurs, and measured data corresponding to values of the metrics in the secondary set of metrics at each of the group of usage points. Storing a trigger condition for scaling the unit of network function based on the secondary set and the measured data.

A method and request router (RR) are provided for dynamically pooling resources in a Content Delivery Network (CDN), for efficient delivery of live and on-demand content. The method comprises receiving, at the RR, a request for a content from a client, determining a content type associated with the request for the content, the content type being one of: live content and on-demand content. The method also comprises, based on the determined content type, dynamically electing, at the RR, delivery nodes at edge, region or core for content delivery and grouping the dynamically elected nodes into a resource pool, selecting a delivery node within the resource pool for delivering the content and sending a response to the client including an address of the delivery node selected within the resource pool to be used to get the requested content.

Methods, systems, and computer programs are presented for managing resources to deliver a network service in a distributed configuration. A method includes an operation for identifying resources for delivering a network service, the resources being classified by geographic area. Further, the method includes operations for selecting service agents to configure the identified resources, each service agent to manage service pools for delivering the network service across at least one geographic area, the service agents being selected to provide configurability for the service pools. The method further includes operations for sending configuration rules, to the service agents, configured to establish service pools for delivering the network service across the geographic areas. Service traffic information is collected from the service agents, and the resources are adjusted based on the collected service traffic information. Updated respective configuration rules are sent to each determined service agent based on the adjusting.

A vehicle monitoring apparatus (300) transmits transmission data obtained from each appliance (200) and the amount of transmission data to a data processing apparatus (500). First, the data processing apparatus calculates the amount of used resources that is the amount of resources used in processing the transmission data, in the amount of resources of computer resources, on the basis of the amount of transmission data. Next, the data processing apparatus increases or decreases, to the amount of used resources, the amount of secured resources that is the amount of resources secured in the amount of resources of the computer resources. Then, the data processing apparatus processes the transmission data by using the amount of secured resources in the amount of resources of the computer resources.

In one embodiment, a method includes calculating ideal resource apportionments from a current set of consumable resources for each of a plurality of reservations. Each reservation corresponds to one of a plurality of customers. The method further includes running an apportionment process relative to the plurality of reservations. The running includes attempting to apportion to each reservation its ideal resource apportionment. The running yields an actual resource apportionment for each reservation. Each customer's actual resource apportionment comprises a sum of the actual resource apportionments for the customer's reservations. In addition, the method includes, responsive to an indication of unapportioned resources following the running, performing a first optimization to increase resource utilization by at least one needy customer.

Methods and apparatus for improving performance of a system including a first computing system are disclosed. In one embodiment, the first computing system receives a request via a network from a client device. The first computing system determines whether a second computing system is available to respond to requests from the first system. The first computing system obtains a response to the request received from the client device based, at least in part, on one or more estimated values maintained by the first computing system according to whether the second computing system is available to respond to requests from the first computing system. The first computing system transmits the response to the client device.

Techniques to utilize excess resources in a cloud system, such as by enabling an auxiliary resource utilizer to use resources while they are not needed to support primary resource utilizers, are described herein. Some embodiments are directed to identifying and allocating excess capacity of resources in a cloud system to auxiliary resource utilizers based on one or more policies. In various embodiments, excess resources in one or more of the set of resources in the cloud system, or cloud resources, may be determined based on monitoring utilization of the cloud resources by the primary resource utilizers. In many embodiments, an auxiliary resource utilizer that is in compliance with a set of utilization policies may be identified and the excess resources may be allocated to the auxiliary resource utilizer.