In general, the embodiments relate to systems and methods for receiving and processing network traffic data units (NTDUs) by one or more edge devices in order to generate a global ordering of NTDU. The methods include receiving, at an aggregator, a first set of locally ordered NTDUs from a first edge device, receiving, at the aggregator, a second set of locally ordered NTDUs from a second edge device, generating a globally ordered sequence of NTDUs using the first set of locally ordered NTDUs and the second set of locally ordered NTDUs; and transmitting the globally ordered sequence of NTDUs to a destination.

A method for managing data transmission comprising making a bandwidth on a network resource available to at least one requestor for transmitting or receiving data according to a first request of a first type, the first type have a prescribed quality of service guarantee; transmitting first data in accordance with the first type to or from the at least one requestor on the network resource using a first portion of the bandwidth, if the first data are available to be transferred to or from the at least one requestor; transmitting second data according to a second request of a second type on the network resource to or from the at least one requestor or a second requestor, the second data transmitted without a quality of service guarantee using a second portion of the bandwidth, if the first portion of the prescribed bandwidth is less than the entire bandwidth.

Information may be dynamically disseminated to network devices. In some embodiments, a data structure may be populated with first-type values and second-type values, a first delay time may be assigned to a first value of the first-type values based on the first value being associated with a first priority and a second delay time may be assigned to a second value of the first-type values based on the second value being associated with a second priority, and data structure information may be obtained from the data structure. The data structure information may be delivered such that the delivery of the data structure information to a first network device associated with the first value reflects the first delay time and the delivery of the data structure information to a second network device associated with the second value reflects the second delay time.

Systems and methods for allocating resources. The system includes a communications module, a processor, and a memory. The memory stores a data record and instructions that, when executed, configure the processor to obtain a data record and transmit an existing score indication corresponding to the data record for display at the client device; receive a first time parameter and an action indicator associated with a shared resource and, in response, determine a first provisional score corresponding to the data record based on the existing score indication, the action indicator, and the first time parameter to provide a first provisional score indication; transmit the first provisional score indication and a selectable option associated with the action indicator for display at the client device while the first provisional score indication is displayed; and in response to receiving a resource transfer instruction, allocate the shared resource associated with the action indicator.

A computer-implemented method of adjusting a resource credit configuration for cloud resources that includes collecting a resource credit inventory and attributing metadata related to resources from one or more cloud resources. An expected resource demand is determined. A plurality of resource credit configurations is determined that matches the determined expected resource demand. An improved resource credit benefit based on the resource credit inventory and on the plurality of credit configurations is determined that matches the determined expected resource demand. A modified attribute metadata based on the determined improved resource credit benefit is then determined.

A DDoS attack handling technology is provided in which even when a plurality of IP addresses are attacked at the same time, resource load distribution between sites can be achieved while an increase in delay of target-addressed communications due to the handling of DDoS attacks is prevented. A DDoS handling apparatus 100 includes a load distribution determination unit 112 that determines whether load distribution processing is necessary, a processability determination unit 113 that determines whether load distribution processing is capable of being performed within a desired time, a grouping processing unit 115 that groups target-addressed communications into a plurality of groups, a load distribution processing unit 116 that determines, for each group, a mitigation site to be used to handle the target-addressed communications from among a plurality of mitigation sites, and an attack handling setting unit 117 that performs route control of the target-addressed communications. The DDoS handling apparatus 100 further includes a load distribution target reduction unit 114 that reduces the number of the target-addressed communications that are targets of the load distribution processing.

A multi-cloud framework is provided for microservice-based applications. An exemplary method comprises maintaining a structural state of an application comprising a plurality of microservices hosted in a plurality of distinct cloud environments. The structural state of the application is maintained over time and comprises, for each microservice, an indication of the cloud environment that hosts the respective microservice. A source code is maintained for each of the plurality of microservices of the application and deployment instructions are maintained for each of the plurality of distinct cloud environments. The plurality of microservices of the application are deployed using the structural state of the application, the source code for each of the plurality of microservices and the deployment instructions for each of the plurality of distinct cloud environments.

A device may receive historical cloud data associated with resources of a cloud computing environment, and may receive historical customer data associated with requested resource usage by customers of the cloud computing environment. The device may determine a usage growth profile based on the historical cloud data and the historical customer data, and may determine, based on the historical cloud data and the historical customer data, usage deviation data indicating deviations between actual and planned resource usage. The device may train a model, with the usage growth profile and the usage deviation data, to generate a trained model, and may receive a request for new resource usage by a customer associated with the cloud computing environment. The device may process the request for the new resource usage, with the trained model, to generate projected resource usage data, and may perform actions based on the projected resource usage data.

A controller is provided for use with a CD, a WAN, and a service provider server, the HNC includes: a memory; and a processor configured to execute instructions stored on memory to cause the HNC to: establish a priority time period; associate the priority time period with a first application; establish a first service flow queue having a first QoS during priority period; establish a second service flow queue having a second QoS; receive first upstream packets and second upstream packets; assign the first upstream packets to a first upstream queue during the priority time period; assign the second upstream packets to a second upstream queue; receive first downstream packets and second downstream packets; assign the first downstream packets to a first downstream queue during the priority time period; and assign the second downstream packets to a second downstream queue.

A maintenance recommendation for containerized services can find a time to perform maintenance on a particular service based on resource usage patterns such that the maintenance will have a reduced impact on dependent services. The dependent services can be determined for the particular service based on network interactions between the services.