Abstract: A network analytics system can receive first sensor data, including first network activity and a first timestamp associated with a first clock of a first node, and second sensor data, including second network activity and a second timestamp associated with a second clock of a second node. The system can determine a first delta between the first clock and a third clock based on the first timestamp, and a second delta between the second clock and the third clock. The system can determine a first communication latency associated with a first sensor of the first node, and a second communication latency associated with a second sensor of the second node. The system can generate a report that synchronizes one or more data flows between the first node and the second node based on the first delta, the second delta, the first communication latency, and the second communication latency.

Abstract: This disclosure generally relate to a method and system for network policy simulation in a distributed computing system. The present technology relates techniques that enable simulation of a new network policy with regard to its effects on the network data flow. By enabling a simulation data flow that is parallel and independent from the regular data flow, the present technology can provide optimized network security management with improved efficiency.

Abstract: Described herein are techniques for concurrently visualizing real user's session data with a playback of a user's experience during a session. The disclosed techniques can correlate session data collected in response to interactions with an application during a user's session with session recreation data generated by the application and recorded during the user's session. The correlations between the session data and the recreation data can be used to render and control a recreation of the user's experience during the session concurrently with a visualization of the session data.

Abstract: Described herein are techniques for concurrently visualizing real user's session data with a playback of a user's experience during a session. The disclosed techniques can correlate session data collected in response to interactions with an application during a user's session with session recreation data generated by the application and recorded during the user's session. The correlations between the session data and the recreation data can be used to render and control a recreation of the user's experience during the session concurrently with a visualization of the session data.

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: Techniques, which may be embodied herein as systems, computing devices, methods, algorithms, software, code, computer readable media, or the like, are described herein for comparing a set of metrics generated during a simulated user interaction with a website to metrics generated by observing real user interactions with the website. Simulated user interactions with a website can be used to diagnose a website's performance issues, but it can be difficult to determine whether the simulated interactions reflect the experience of real users. In addition, the simulated user interactions can be challenging to contextualize because the number of observed real user interactions may significantly outnumber the simulated interactions. A graphical user interface can help with the interpretation of these website interactions by using the real user interactions to properly contextualize the simulated results.

Abstract: This disclosure generally relate to a method and system for network policy simulation in a distributed computing system. The present technology relates techniques that enable simulation of a new network policy with regard to its effects on the network data flow. By enabling a simulation data flow that is parallel and independent from the regular data flow, the present technology can provide optimized network security management with improved efficiency.

Abstract: This disclosure generally relate to a method and system for network policy simulation in a distributed computing system. The present technology relates techniques that enable simulation of a new network policy with regard to its effects on the network data flow. By enabling a simulation data flow that is parallel and independent from the regular data flow, the present technology can provide optimized network security management with improved efficiency.

Abstract: Techniques, which may be embodied herein as systems, computing devices, methods, algorithms, software, code, computer readable media, or the like, are described herein for comparing a set of metrics generated during a simulated user interaction with a website to metrics generated by observing real user interactions with the website. Simulated user interactions with a website can be used to diagnose a website's performance issues, but it can be difficult to determine whether the simulated interactions reflect the experience of real users. In addition, the simulated user interactions can be challenging to contextualize because the number of observed real user interactions may significantly outnumber the simulated interactions. A graphical user interface can help with the interpretation of these website interactions by using the real user interactions to properly contextualize the simulated results.

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: An example method according to some embodiments includes receiving flow data for a packet traversing a network. The method continues by determining a source endpoint group and a destination endpoint group for the packet. The method continues by determining that a policy was utilized, the policy being applicable to the endpoint group. Finally, the method includes updating utilization data for the policy based on the flow data.

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, 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: A performance monitoring system (PMS 102) displays a list of example URLs that matched a URL grouping rule used to group URLs. For a rule configured for a customer of the PMS, the example matched URLs are selected by the PMS from a candidate set of URLs identified from data associated with that customer. The PMS receives information identifying a Uniform Resource Locator (URL) grouping rule displayed in a graphical user interface (GUI). The PMS identified a list of candidate URLs occurring in the stored data. The PMS then identifies, from the list of candidate URLs, a set of matched URLs, the set of matched URLs including one or more URLs from the list of candidate URLs that matched the URL grouping rule. The PMS then causes at least one URL from the set of matched URLs to be displayed on the GUI.

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: 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 according to some embodiments includes receiving flow data for a packet traversing a network. The method continues by determining a source endpoint group and a destination endpoint group for the packet. The method continues by determining that a policy was utilized, the policy being applicable to the endpoint group. Finally, the method includes updating utilization data for the policy based on the flow data.

Abstract: A method includes analyzing, via a first capturing agent, packets processed in a first environment associated with a first host to yield first data. The method includes analyzing, via a second capturing agent, packets processed by a second environment associated with a second host to yield second data, collecting the first data and the second data at a collector to yield aggregated data, transmitting the aggregated data to an analysis engine which analyzes the aggregated data to yield an analysis. Based on the analysis, the method includes identifying first packet loss at the first environment and second packet loss at the second environment.

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.