Cisco Technology, Inc.

Andy Sloane

Navindra Yadav

Ashutosh Kulshreshtha

Vimal Jeyakumar

Ali Parandehgheibi

Omid Madani

Shih-Chun Chang

Khawar Deen

Hai Trong Vu

Kai Chang

Oliver Kempe

Uday Krishnaswamy Chettiar

Bharathwaj Sankara Viswanathan

Hiral Shashikant Patel

The present disclosure provides systems, methods, and computer-readable media for implementing security polices at software call stack level. In one example, a method includes generating a call stack classification scheme for an application, detecting a call stack during deployment of the application; using the call stack classification scheme during runtime of the application, classifying the detected call stack as one of an authorized call stack or an unauthorized call stack to yield a classification; and applying a security policy based on the classification.

Security policies for software call stacks

An application and network analytics platform can capture telemetry from servers and network devices operating within a network. The application and network analytics platform can determine an application dependency map (ADM) for an application executing in the network. Using the ADM, the application and network analytics platform can resolve flows into flowlets of various granularities, and determine baseline metrics for the flowlets. The baseline metrics can include transmission times, processing times, and/or data sizes for the flowlets. The application and network analytics platform can compare new flowlets against the baselines to assess availability, load, latency, and other performance metrics for the application. In some implementations, the application and network analytics platform can automate remediation of unavailability, load, latency, and other application performance issues.

Application performance monitoring and management platform with anomalous flowlet resolution

Disclosed herein is a multi-level analysis for determining a root cause of a network problem by performing a first level of the multi-level process that includes collecting data from one or more network components, generating a set of system metrics where each system metric of the set representing a portion of the data, ranking the set of system metrics based on a level of correlation of each system metric to the network problem to yield a ranked set of system metrics, and providing a visual representation of the first level of the multi-level process. A second level of the multi-level process includes receiving an input identifying one or more of the ranked set of system metrics to be excluded from analysis and performing a conditional analysis using only ones of the set of system metrics that are not identified for exclusion.

System and method for network root cause analysis

Flowlet resolution for application performance monitoring and management

The disclosed technology relates to log file processing techniques for root cause analysis of a network fabric. A system may be configured to identify a feature of interest in a log file and calculating an abnormal level for the feature of interest. The system is further configured to detect that a performance event has occurred during a time period, determine whether the feature of interest is at the abnormal level during the time period, and identify a correlation between the feature of interest and the performance event based on the determining.

Log file processing for root cause analysis of a network fabric

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Pleasanton, CA, United States of America

Andy Sloane