Disclosed are systems, methods, and computer-readable media for assuring tenant forwarding in a network environment. Network assurance can be determined in layer 1, layer 2 and layer 3 of the networked environment including, internal-internal (e.g., inter-fabric) forwarding and internal-external (e.g., outside the fabric) forwarding in the networked environment. The network assurance can be performed using logical configurations, software configurations and/or hardware configurations.

This application provides a network configuration method, apparatus, and system. The method includes: determining, based on a mapping relationship, that a first data node in a first YANG data model corresponds to a second data node in a second YANG data model, where the first data node and the second data node include a same indication operation, and the mapping relationship includes a correspondence between a data node in the first YANG data model and a data node in the second YANG data model; and generating a first packet based on the second data node.

Auto connectivity simulation from the client-side. Workstations/clients are intelligently selected, on a continuous basis, for auto connectivity simulation and probes are communicated to the selected workstations which activate a previously deployed agent that is configured to conduct connectivity simulations to the communication network and, at least, basic utility services provided within the communication network. The comprehensive results of connectivity simulations are analyzed and patterns of connectivity issues are identified. Subsequently, rules are applied to the patterns of connectivity issues to determine appropriate actions, such as reconfiguring the connectivity route, the servers used for connection and/or notifying personnel assigned to address the issues.

A traffic shifting system is described to shift traffic away from one or more network devices or interfaces. The system ensures that traffic can be safely shifted off of a network device before the shifting occurs. The method is described as broken into several phases, such as a discovery phase, a pre-check phase, a shifting phase, and a post-shift phase. Before shifting occurs, the discovery phase is used to obtain network topology and configuration information. In the pre-check phase, that information is interrogated so that a shifting can be performed without negatively impacting the network. If the pre-check phase is passed, then the network shifting can occur through adjustment of configuration parameters, such as a cost parameter associated with an interface on any devices for which traffic is being shifted. Finally, in the post-shift phase, checks are performed to ensure traffic is shifting away from the network device.

A traffic shifting system is described to shift traffic away from one or more network devices or interfaces. The system ensures that traffic can be safely shifted off of a network device before the shifting occurs. The method is described as broken into several phases, such as a discovery phase, a pre-check phase, a shifting phase, and a post-shift phase. Before shifting occurs, the discovery phase is used to obtain network topology and configuration information. In the pre-check phase, that information is interrogated so that a shifting can be performed without negatively impacting the network. If the pre-check phase is passed, then the network shifting can occur through adjustment of configuration parameters, such as a cost parameter associated with an interface on any devices for which traffic is being shifted. Finally, in the post-shift phase, checks are performed to ensure traffic is shifting away from the network device.

Various systems and methods are provided for analyzing the effect(s) that a configuration change to one device has on other connected devices. In one embodiment, the disclosed functionality includes determining connectivity information associated with a data center, where the data center comprises at least a first device and a second device; discovering one or more changes to a configuration of the first device; determining, based at least in part on the connectivity information, that the second device is impacted by the one or more changes to the configuration of the first device; and determining one or more impacts to the second device as a result of the one or more changes, where each of the one or more impacts indicates a positive impact to the second device, a negative impact to the second device, or no impact to the second device.

Various systems and methods are provided for analyzing the effect(s) that a configuration change to one device has on other connected devices. In one embodiment, the disclosed functionality includes determining connectivity information associated with a data center, where the data center comprises at least a first device and a second device; discovering one or more changes to a configuration of the first device; determining, based at least in part on the connectivity information, that the second device is impacted by the one or more changes to the configuration of the first device; and determining one or more impacts to the second device as a result of the one or more changes, where each of the one or more impacts indicates a positive impact to the second device, a negative impact to the second device, or no impact to the second device.

The present technology provides a system, method and computer-readable medium for configuration pattern recognition and inference, directed to a device with an existing configuration, through an extensible policy framework. The policy framework uses a mixture of python template logic and CLI micro-templates as a mask to infer the intent behind an existing device configuration in a bottom-up learning inference process. Unique values for device/network identifiers and addresses as well as other resources are extracted and accounted for. The consistency of devices within the fabric is checked based on the specific policies built into the extensible framework definition. Any inconsistencies found are flagged for user correction or automatically remedied by a network controller. This dynamic configuration pattern recognition ability allows a fabric to grow without being destroyed and re-created, thus new devices with existing configurations may be added and automatically configured to grow a Brownfield fabric.

The present technology provides a system, method and computer-readable medium for configuration pattern recognition and inference, directed to a device with an existing configuration, through an extensible policy framework. The policy framework uses a mixture of python template logic and CLI micro-templates as a mask to infer the intent behind an existing device configuration in a bottom-up learning inference process. Unique values for device/network identifiers and addresses as well as other resources are extracted and accounted for. The consistency of devices within the fabric is checked based on the specific policies built into the extensible framework definition. Any inconsistencies found are flagged for user correction or automatically remedied by a network controller. This dynamic configuration pattern recognition ability allows a fabric to grow without being destroyed and re-created, thus new devices with existing configurations may be added and automatically configured to grow a Brownfield fabric.

Example methods and systems for logical network health check. One example may comprise obtaining network configuration information and network realization information associated with a logical network; processing the network configuration information and the network realization information to determine the following: (a) network configuration health information specifying a network configuration issue and a first remediation action; and (b) network realization health information specifying a network realization issue and a second remediation action; and providing, to a user device, multiple user interfaces (UIs) specifying the first health information and the second health information along with a visualization of the logical network. In response to detecting an instruction initiated by the user device using at least one of the multiple UIs, the first remediation action or the second remediation action may be performed.