Cisco Technology, Inc.

Pavan Mamillapalli

Shadab Nazar

Gaurav Gupta

Chetan Narsude

Azeem Suleman

Sundar Iyer

Jagdev Singh Tur

Ramana Rao Kompella

Chandra Nagarajan

Ayas Pani

Praveen Tammana

Navjyoti Sharma

Navneet Yadav

John Thomas Monk

Sravya Boggavarapu

Jose Delgado

Aspects of the technology provide solutions for determining a time period ('epoch') required to monitor or analyze a tenant network. Some implementations of the technology include a process for making automatic epoch determinations, which includes steps for identifying one or more network parameters for a tenant network, analyzing the tenant network using the network parameters to discover one or more configuration settings of the tenant network, and determining a first epoch for the tenant network, the first epoch corresponding with a period of time to complete analysis of the tenant network using the network parameters. In some aspects, the process can further include steps for generating a tenant profile for the tenant network, the tenant profile based on the network parameters, the first epoch, and the one or more configuration settings of the tenant network. Systems and machine-readable media are also provided.

Automatically determining an optimal amount of time for analyzing a distributed network environment

Systems, methods, and computer-readable media for detecting and reporting anomalies in a network environment for providing network assurance. In some embodiments, a system can determine confidence scores for at least one value of parameters of a network environment defining network events occurring in the network environment. The confidences scores can indicate a frequency that the defined network events have a specific event state. The confidence scores can be monitored to detect an anomaly in the network environment. In response to detecting the anomaly in the network environment, the system can determine a relevant network state of the network environment. The relevant network state of the network environment and the anomaly in the network environment can be presented to a user.

Anomaly detection and reporting in a network assurance appliance

Aspects of the technology provide methods for simulating a failure in a tenant network. In some aspects, a monitoring appliance of the disclosed technology can be configured to carry out operations for receiving packets at a virtual device in the monitoring appliance, from a corresponding network device in the tenant network, and instantiating a firewall at the virtual device, wherein the firewall is configured to selectively block traffic routed from the network device to the virtual device in the monitoring appliance. The monitoring appliance can simulate failure of the network device by blocking traffic from the network device to the virtual device using the firewall, and analyze the tenant network to determine a predicted impact a failure of the network device would have on the tenant network. Systems and machine-readable media are also provided.

Controlled micro fault injection on a distributed appliance

Systems, methods, and computer-readable media for localizing faults in a network policy are disclosed. In some examples, a system or method can obtain TCAM rules across a network and use the TCAM rules to perform an equivalency check between the logical model and the hardware model of the network policy. One or more risk models are annotated with output from the equivalency check and the risk models are used to identify a set of policy objects of the network policy that are likely responsible for the faults. The identified set of policy objects are correlated with various logs of the network. Based on the correlation, specific policy objects of the set of policy objects that are associated with physical-level causes of the fault.

Associating network policy objects with specific faults corresponding to fault localizations in large-scale network deployment

Systems, methods, and computer-readable media for localizing faults in a network policy are disclosed. In some examples, a system or method can obtain TCAM rules across a network and use the TCAM rules to perform an equivalency check between the logical model and the hardware model of the network policy. One or more risk models are annotated with output from the equivalency check and the risk models are used to identify a set of policy objects of the network policy that are likely responsible for the faults.

Fault localization in large-scale network policy deployment

Aspects of the technology provide methods for aggregating error log data between multiple devices in a network monitoring appliance. A method of the technology can include steps for identifying a plurality of operators running in a network monitoring appliance, instantiating a plurality of sensors, wherein each of the plurality of sensors is associated with a respective one of the plurality of operators, and wherein each sensor is configured to capture error log data of its corresponding operator. In some aspects, the method can further include steps for aggregating error log data from two or more of the plurality of sensors. Systems and machine-readable media are also provided.

Self diagnosing distributed appliance

Systems, methods, and computer-readable media for aggregating and presenting network events in a network environment. In some embodiments, a system can maintain event correlation rules for aggregating \network events occurring in a network based on characteristics of previously occurring network events. Network events occurring in the specific network environment can be identified. The network events can be aggregated to form an aggregated network event using the event correlation rules maintained based on the characteristics of previously occurring network events. The aggregated network event can subsequently be presented to a user.

Network assurance event aggregator

Aspects of the technology provide systems and methods for interleaving a processing task in a network monitoring appliance. A process of the technology could include steps for identifying operators in the network monitoring appliance, wherein the operators are sequentially arranged to form a processing pipeline, determining an epoch for the processing pipeline, wherein the epoch corresponds with a time duration required for a processing task to traverse the pipeline, and determining a time window in which a supplemental processing task can be interleaved into the processing pipeline, wherein the time window is based on the epoch. Machine-readable media are also provided.

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San Ramon, CA, United States of America

Pavan Mamillapalli