Abstract:
This disclosure generally relate to a method and system for mapping network information. The present technology relates techniques that enable full-scale, dynamic network mapping of a network system. By collecting network and computing data using built-in sensors, the present technology can provide network information for system monitoring and maintenance. According to some embodiments, the present technology enables generating and displaying of network connections and data processing statistics related to numerous nodes in a network. The present technology provides useful insights and actionable knowledge for network monitoring, security, and maintenance, via intelligently summarizing and effectively displaying the complex network communications and processes of a network.
Abstract:
Application dependency mapping can be automated in a network. The network can capture traffic data for flows passing through the network using a sensor network that provides multiple perspectives for the traffic. The network can analyze the traffic data to identify endpoints of the network. The network can also identify particular network configurations from the traffic data, such as a load balancing schema or a subnetting schema. The network can partition the endpoints based on the network configuration(s) and perform similarity measurements of endpoints in each partition to determine clusters of each partition. The clusters can make up nodes of an application dependency map, and relationships between and among the clusters can make up edges of the application dependency map.
Abstract:
Flow data can be augmented with features or attributes from other domains, such as attributes from a source host and/or destination host of a flow, a process initiating the flow, and/or a process owner or user. A network can be configured to capture network or packet header attributes of a first flow and determine additional attributes of the first flow using a sensor network. The sensor network can include sensors for networking devices (e.g., routers, switches, network appliances), physical servers, hypervisors or container engines, and virtual partitions (e.g., virtual machines or containers). The network can calculate a feature vector including the packet header attributes and additional attributes to represent the first flow. The network can compare the feature vector of the first flow to respective feature vectors of other flows to determine an applicable policy, and enforce that policy for subsequent flows.
Abstract:
An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.
Abstract:
This disclosure generally relate to a method and system for mapping network information. The present technology relates techniques that enable full-scale, dynamic network mapping of a network system. By collecting network and computing data using built-in sensors, the present technology can provide network information for system monitoring and maintenance. According to some embodiments, the present technology enables generating and displaying of network connections and data processing statistics related to numerous nodes in a network. The present technology provides useful insights and actionable knowledge for network monitoring, security, and maintenance, via intelligently summarizing and effectively displaying the complex network communications and processes of a network.
Abstract:
An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.
Abstract:
An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.
Abstract:
Systems and methods are provided for automatically discovering applications/clusters in a network and mapping dependencies between the applications/clusters. A network monitoring system can capture network flow data using sensors executing on physical and/or virtual servers of the network and sensors executing on networking devices connected to the servers. The system can determine a graph including nodes, representing at least the servers, and edges, between pairs of the nodes of the graph indicating the network flow data includes one or more observed flows between pairs of the servers represented by the pairs of the nodes. The system can determine a dependency map, including representations of clusters of the servers and representations of dependencies between the clusters, based on the graph. The system can display a first representation of a first cluster of the dependency map and information indicating a confidence level of identifying the first cluster.
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 example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.