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: 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: 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.

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 network strengthening, such as by detecting issues with one or more network components and reconfiguring one or more upstream or downstream network components to preempt issues with the one or more upstream or downstream network components, for instance. Some embodiments are particularly directed to a tool (e.g., strengthening agent) that implements pre-scripted or dynamic hardening of up and downstream dependencies of a network component in response to an issue identified with the network component. In many embodiments, up and downstream components of a network component may be reconfigured while the issue with the network component is being addressed to preempt issues with the up and downstream components.

Abstract: 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.

Abstract: Various embodiments are generally directed to techniques for network strengthening, such as by detecting issues with one or more network components and reconfiguring one or more upstream or downstream network components to preempt issues with the one or more upstream or downstream network components, for instance. Some embodiments are particularly directed to a tool (e.g., strengthening agent) that implements pre-scripted or dynamic hardening of up and downstream dependencies of a network component in response to an issue identified with the network component. In many embodiments, up and downstream components of a network component may be reconfigured while the issue with the network component is being addressed to preempt issues with the up and downstream components.

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: 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: 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.

Abstract: 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.

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: Various embodiments are generally directed to techniques for utilizing disruptions to enterprise systems, such as to test and/or improve the ability of the enterprise system to recover from system failures, for instance. In many embodiments, an enterprise system may include two or more networked components, such as hardware components and software components. Some embodiments are particularly directed to generating a disruption scheme for an enterprise system based on analysis of one or more aspects of the enterprise system. For example, embodiments may include one or more of planning, scheduling, creating, timing, implementing, administering, and/or strengthening against a disruption to an enterprise system in a controlled and monitored manner. In many embodiments, administration of a disruption scheme may be monitored, recorded, and/or analyzed. In many such embodiments, a library of disruption events may be generated based on monitoring, recording, and/or analyzing implementation of the disruption scheme.

Abstract: Various embodiments are generally directed to techniques for network strengthening, such as by detecting issues with one or more network components and reconfiguring one or more upstream or downstream network components to preempt issues with the one or more upstream or downstream network components, for instance. Some embodiments are particularly directed to a tool (e.g., strengthening agent) that implements pre-scripted or dynamic hardening of up and downstream dependencies of a network component in response to an issue identified with the network component. In many embodiments, up and downstream components of a network component may be reconfigured while the issue with the network component is being addressed to preempt issues with the up and downstream components.

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: 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.

Abstract: Various embodiments are generally directed to techniques for utilizing disruptions to enterprise systems, such as to test and/or improve the ability of the enterprise system to recover from system failures, for instance. In many embodiments, an enterprise system may include two or more networked components, such as hardware components and software components. Some embodiments are particularly directed to generating a disruption scheme for an enterprise system based on analysis of one or more aspects of the enterprise system. For example, embodiments may include one or more of planning, scheduling, creating, timing, implementing, administering, and/or strengthening against a disruption to an enterprise system in a controlled and monitored manner. In many embodiments, administration of a disruption scheme may be monitored, recorded, and/or analyzed. In many such embodiments, a library of disruption events may be generated based on monitoring, recording, and/or analyzing implementation of the disruption scheme.