Abstract: Various embodiments are generally directed to techniques for dynamic network resiliency, such as by monitoring and controlling the configuration of one or more network components to ensure proper endpoint alignment, for instance. Some embodiments are particularly directed to a tool (e.g., resiliency agent) that can automatically recognize symptoms of issues with a network component, such as autoscaling, latency, traffic spikes, resource utilization spikes, etcetera, and respond appropriately to ensure continued and optimized operation of the network component. In many embodiments, the tool may dynamically reroute endpoint traffic, perform traffic balancing, and/or drive autoscaling to optimize operation of the network component in response to recognizing symptoms.

Abstract: Various embodiments are generally directed to techniques for dynamic network management, such as by monitoring and analyzing network parameters, such as network traffic and network configurations, to enable visualization of network state and improved situational awareness. Some embodiments are particularly directed to providing a graphical user interface (GUI) that utilizes various network parameters to map, characterize, and/or assign attributes to network traffic and resources. In many embodiments, network traffic may be monitored and/or routed based on their attributes.

Abstract: Disclosed are hardware and techniques for testing computer processes in a network system by simulating computer process faults and identifying risk associated with correcting the simulated fault and identifying computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a risk matrix having a risk score and non-functional requirement score. An analysis of the risk score and non-functional requirement score accounts for interdependencies between computer processes and identified corrective actions that may be used to determine an optimal network environment. The optimal network environment may be updated dynamically based on changing computer process interdependencies and the determined risk and robustness scores.

Abstract: Various embodiments are generally directed to techniques for dynamic network resiliency, such as by monitoring and controlling the configuration of one or more network components to ensure proper endpoint alignment, for instance. Some embodiments are particularly directed to a tool (e.g., resiliency agent) that can automatically recognize symptoms of issues with a network component, such as autoscaling, latency, traffic spikes, resource utilization spikes, etcetera, and respond appropriately to ensure continued and optimized operation of the network component. In many embodiments, the tool may dynamically reroute endpoint traffic, perform traffic balancing, and/or drive autoscaling to optimize operation of the network component in response to recognizing symptoms.

Abstract: The present disclosure relates to systems and methods for generating intrinsic matrixed bar codes, such as Quick Response (“QR”) codes. In one implementation, system for generating an intrinsic matrixed bar code may include an image-receiving device, a processor configured to execute instructions, and a memory storing the instructions. The instructions may include instructions to: receive an image using the image-receiving device, generate a registration mark corresponding to the received image, select coordinates on the received image, overlay one or more matrixed bar codes on the selected coordinates, update the registration mark with the selected coordinates, and overlay the registration mark on the received image.

Abstract: Disclosed are hardware and techniques for correcting computer process faults by identifying risk associated with correcting a computer process fault and computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a stream of process break flags from a monitoring component coupled to the network. Each computer process break flag in the stream of computer process break flags indicates a process fault detected by the monitoring component and is correlated to a corrective response. The break flag and the corrective response are assigned a risk. A risk matrix accounts for interdependencies between computer processes and identified corrective actions. A final response strategy that corrects the computer process faults is determined using the assigned risk and computer system interdependence.

Abstract: Various embodiments are generally directed to techniques for dynamic network management, such as by monitoring and analyzing network parameters, such as network traffic and network configurations, to enable visualization of network state and improved situational awareness. Some embodiments are particularly directed to providing a graphical user interface (GUI) that utilizes various network parameters to map, characterize, and/or assign attributes to network traffic and resources. In many embodiments, network traffic may be monitored and/or routed based on their attributes.

Abstract: Disclosed are hardware and techniques for correcting computer process faults by identifying risk associated with correcting a computer process fault and computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a stream of process break flags from a monitoring component coupled to the network. Each computer process break flag in the stream of computer process break flags indicates a process fault detected by the monitoring component and is correlated to a corrective response. The break flag and the corrective response are assigned a risk. A risk matrix accounts for interdependencies between computer processes and identified corrective actions. A final response strategy that corrects the computer process faults is determined using the assigned risk and computer system interdependence.

Abstract: The present disclosure relates to systems and methods for generating intrinsic matrixed bar codes, such as Quick Response (“QR”) codes. In one implementation, system for generating an intrinsic matrixed bar code may include an image-receiving device, a processor configured to execute instructions, and a memory storing the instructions. The instructions may include instructions to: receive an image using the image-receiving device, generate a registration mark corresponding to the received image, select coordinates on the received image, overlay one or more matrixed bar codes on the selected coordinates, update the registration mark with the selected coordinates, and overlay the registration mark on the received image.

Abstract: The present disclosure relates to systems and methods for generating intrinsic matrixed bar codes, such as Quick Response (“QR”) codes. In one implementation, system for generating an intrinsic matrixed bar code may include an image-receiving device, a processor configured to execute instructions, and a memory storing the instructions. The instructions may include instructions to: receive an image using the image-receiving device, generate a registration mark corresponding to the received image, select coordinates on the received image, overlay one or more matrixed bar codes on the selected coordinates, update the registration mark with the selected coordinates, and overlay the registration mark on the received image.

Abstract: A computer-implemented method is disclosed. The method can comprise: monitoring utilization of a cloud architecture component that is being used by a component utilizer; determining, via a machine learning model, a pattern of usage of the cloud architecture component based on the monitoring; determining, based on the pattern of usage, a first time period when the cloud architecture component is excessively used by the component utilizer and a second time period when the cloud resource is scantily used by the component utilizer; and orchestrating, based on the first and second time periods, a scaling of the cloud architecture immediately before a subsequent iteration of the pattern of usage by the component utilizer.

Abstract: Disclosed are hardware and techniques for testing computer processes in a network system by simulating computer process faults and identifying risk associated with correcting the simulated fault and identifying computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a risk matrix having a risk score and non-functional requirement score. An analysis of the risk score and non-functional requirement score accounts for interdependencies between computer processes and identified corrective actions that may be used to determine an optimal network environment. The optimal network environment may be updated dynamically based on changing computer process interdependencies and the determined risk and robustness scores.

Abstract: Disclosed are hardware and techniques for testing computer processes in a network system by simulating computer process faults and identifying risk associated with correcting the simulated fault and identifying computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a risk matrix having a risk score and non-functional requirement score. An analysis of the risk score and non-functional requirement score accounts for interdependencies between computer processes and identified corrective actions that may be used to determine an optimal network environment. The optimal network environment may be updated dynamically based on changing computer process interdependencies and the determined risk and robustness scores.

Abstract: Disclosed are hardware and techniques for correcting computer process faults by identifying risk associated with correcting a computer process fault and computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a stream of process break flags from a monitoring component coupled to the network. Each computer process break flag in the stream of computer process break flags indicates a process fault detected by the monitoring component and is correlated to a corrective response. The break flag and the corrective response are assigned a risk. A risk matrix accounts for interdependencies between computer processes and identified corrective actions. A final response strategy that corrects the computer process faults is determined using the assigned risk and computer system interdependence.

Abstract: Various embodiments are generally directed to techniques for dynamic network management, such as by monitoring and analyzing network parameters, such as network traffic and network configurations, to enable visualization of network state and improved situational awareness. Some embodiments are particularly directed to providing a graphical user interface (GUI) that utilizes various network parameters to map, characterize, and/or assign attributes to network traffic and resources. In many embodiments, network traffic may be monitored and/or routed based on their attributes.

Abstract: Various embodiments are generally directed to techniques for dynamic network resiliency, such as by monitoring and controlling the configuration of one or more network components to ensure proper endpoint alignment, for instance. Some embodiments are particularly directed to a tool (e.g., resiliency agent) that can automatically recognize symptoms of issues with a network component, such as autoscaling, latency, traffic spikes, resource utilization spikes, etcetera, and respond appropriately to ensure continued and optimized operation of the network component. In many embodiments, the tool may dynamically reroute endpoint traffic, perform traffic balancing, and/or drive autoscaling to optimize operation of the network component in response to recognizing symptoms.

Abstract: Disclosed are hardware and techniques for correcting computer process faults by identifying risk associated with correcting a computer process fault and computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a stream of process break flags from a monitoring component coupled to the network. Each computer process break flag in the stream of computer process break flags indicates a process fault detected by the monitoring component and is correlated to a corrective response. The break flag and the corrective response are assigned a risk. A risk matrix accounts for interdependencies between computer processes and identified corrective actions. A final response strategy that corrects the computer process faults is determined using the assigned risk and computer system interdependence.

Abstract: Various embodiments are generally directed to techniques for dynamic network management, such as by monitoring and analyzing network parameters, such as network traffic and network configurations, to enable visualization of network state and improved situational awareness. Some embodiments are particularly directed to providing a graphical user interface (GUI) that utilizes various network parameters to map, characterize, and/or assign attributes to network traffic and resources. In many embodiments, network traffic may be monitored and/or routed based on their attributes.

Abstract: Various embodiments are generally directed to techniques for dynamic network resiliency, such as by monitoring and controlling the configuration of one or more network components to ensure proper endpoint alignment, for instance. Some embodiments are particularly directed to a tool (e.g., resiliency agent) that can automatically recognize symptoms of issues with a network component, such as autoscaling, latency, traffic spikes, resource utilization spikes, etcetera, and respond appropriately to ensure continued and optimized operation of the network component. In many embodiments, the tool may dynamically reroute endpoint traffic, perform traffic balancing, and/or drive autoscaling to optimize operation of the network component in response to recognizing symptoms.

Abstract: The present disclosure relates to systems and methods for generating intrinsic matrixed bar codes, such as Quick Response (“QR”) codes. In one implementation, system for generating an intrinsic matrixed bar code may include an image-receiving device, a processor configured to execute instructions, and a memory storing the instructions. The instructions may include instructions to: receive an image using the image-receiving device, generate a registration mark corresponding to the received image, select coordinates on the received image, overlay one or more matrixed bar codes on the selected coordinates, update the registration mark with the selected coordinates, and overlay the registration mark on the received image.