Abstract:
Systems, methods, and computer-readable media for identifying bogon addresses. A system can obtain an indication of address spaces in a network. The indication can be based on route advertisements transmitted by routers associated with the network. The system can receive a report generated by a capturing agent deployed on a host. The report can identify a flow captured by the capturing agent at the host. The system can identify a network address associated with the flow and, based on the indication of address spaces, the system can determine whether the network address is within the address spaces in the network. When the network address is not within the address spaces in the network, the system can determine that the network address is a bogon address. When the network address is within the address spaces in the network, the system can determine that the network address is not a bogon address.
Abstract:
A monitoring device/module monitors a plurality of nodes in a data center network, and determines one or more latency distributions of response times for messages exchanged between pairs of nodes of the plurality of nodes. The network monitoring device determines a network topology, including one or more communication links interconnecting nodes of the plurality of nodes, consistent with the one or more latency distributions. The network monitoring device also determines a representative response time for each communication link based on the one or more latency distributions, and compares a current response time a message exchanged between one pair of nodes to the representative response time for the communication link interconnecting the one pair of nodes. The network monitoring device identifies a network anomaly when the current response time deviates from the representative response time for the communication link interconnecting the one pair of nodes by a threshold amount.
Abstract:
Systems, methods, and computer-readable media for identifying bogon addresses. A system can obtain an indication of address spaces in a network. The indication can be based on route advertisements transmitted by routers associated with the network. The system can receive a report generated by a capturing agent deployed on a host. The report can identify a flow captured by the capturing agent at the host. The system can identify a network address associated with the flow and, based on the indication of address spaces, the system can determine whether the network address is within the address spaces in the network. When the network address is not within the address spaces in the network, the system can determine that the network address is a bogon address. When the network address is within the address spaces in the network, the system can determine that the network address is not a bogon address.
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 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:
Systems, methods, and computer-readable media for hierarchichal sharding of flows from sensors to collectors. A first collector can receive a first portion of a network flow from a first capturing agent and determine that a second portion of the network flow was not received from the first capturing agent. The first collector can then send the first portion of the network flow to a second collector. A third collector can receive the second portion of the network flow from a second capturing agent and determine that the third collector did not receive the first portion of the network flow. The third collector can then send the second portion of the network flow to the second collector. The second collector can then aggregate the first portion and second portion of the network flow to yield the entire portion of the network flow.
Abstract:
Systems, methods, and computer-readable media for identifying bogon addresses. A system can obtain an indication of address spaces in a network. The indication can be based on route advertisements transmitted by routers associated with the network. The system can receive a report generated by a capturing agent deployed on a host. The report can identify a flow captured by the capturing agent at the host. The system can identify a network address associated with the flow and, based on the indication of address spaces, the system can determine whether the network address is within the address spaces in the network. When the network address is not within the address spaces in the network, the system can determine that the network address is a bogon address. When the network address is within the address spaces in the network, the system can determine that the network address is not a bogon address.
Abstract:
A method provides for receiving network traffic from a host having a host IP address and operating in a data center, and analyzing a malware tracker for IP addresses of hosts having been infected by a malware to yield an analysis. When the analysis indicates that the host IP address has been used to communicate with an external host infected by the malware to yield an indication, the method includes assigning a reputation score, based on the indication, to the host. The method can further include applying a conditional policy associated with using the host based on the reputation score. The reputation score can include a reduced reputation score from a previous reputation score for the host.
Abstract:
Managing a network environment to identify spoofed packets is disclosed. A method includes analyzing, via a first capture agent, packets processed by a first environment in a network associated with a first host, and analyzing, via a second capture agent, packets processed by a second environment in the network associated with a second host. The method includes collecting the first data and the second data at a collector and generating a topological map of the network and a history of network activity associated with the first environment and the second environment. The method includes extracting network data from a packet and comparing the extracted network data with stored network data in the database. When the comparison indicates that the extracted network data does not match the stored network data (i.e., the reported source does not match an expected source for the packet), determining that the packet is a spoofed packet.
Abstract:
An application and network analytics platform can capture comprehensive telemetry from servers and network devices operating within a network. The platform can discover flows running through the network, applications generating the flows, servers hosting the applications, computing resources provisioned and consumed by the applications, and network topology, among other insights. The platform can generate various models relating one set of application and network performance metrics to another. For example, the platform can model application latency as a function of computing resources provisioned to and/or actually used by the application, its host's total resources, and/or the distance of its host relative to other elements of the network. The platform can change the model by moving, removing, or adding elements to predict how the change affects application and network performance. In some situations, the platform can automatically act on predictions to improve application and network performance.