Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Systems, methods, and computer-readable for identifying known vulnerabilities in a software product include determining a set of one or more processed words based on applying text classification to one or more names associated with a product, where the text classification is based on analyzing a database of names associated with a database of products Similarity scores are determined between the set of one or more processed words and names associated with one or more known vulnerabilities maintained in a database of known vulnerabilities in products. Equivalence mapping is performed between the one or more names associated with the product and the one or more known vulnerabilities, based on the similarity scores. Known vulnerabilities in the product are identified based on the equivalence mapping.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.