Cisco Technology, Inc.

Shashi Gandham

Navindra Yadav

Shih-Chun Chang

Sunil Gupta

Hai Trong Vu

Varun Sagar Malhotra

Praneeth Vallem

Rohit Chandra Prasad

Hoang Viet Nguyen

Supreeth Rao

Jothi Prakash Prabakaran

Michael Standish Watts

Darshan Shrinath Purandare

Ravi Prasad

Abhishek Ranjan Singh

Xuan Zou

Ali Parandehgheibi

Umamaheswaran Arumugam

Aiyesha Ma

Paul Mach

Janardhanan Radhakrishnan

Duy Nguyen

Umesh Paul Mahindra

Prasannakumar Jobigenahally Malleshaiah

Hoang-Nam Nguyen

Tapan Shrikrishna Patwardhan

Xin Yi Liu

Kai Zhu

Rachita Agasthy

Thanh Trung Ngo

Allen Chen

Xuan Loc Bui

Joseph Daniel Beshay

Duan Tran

Xiaofei Guo

Mohammadreza Alizadeh Attar

Omid Madani

Weifei Zeng

Paul John Lesiak

Sayeed Mohammed Tasnim

Yash Vipul Doshi

Girish Anant Kalele

Akshay Srirangam

Micheal Watts

Thanh Nhan Thi Nguyen

The disclosed technology relates to a network agent for reporting to a network policy system. A network agent includes an agent enforcer and an agent controller. The agent enforcer is configured to implementing network policies on the system, access data associated with the implementation of the network policies on the system, and transmit, via an interprocess communication, the data to the agent controller. The agent controller is configured to generate a report including the data and transmit the report to a network policy system.

Network agent for reporting to a network policy system

Aspects of the subject technology relate to a system configured to receive a set of network snapshot segments from an output stream of a stream processing service, compile the set of network snapshot segments from the set of messages into a first network snapshot and a second network snapshot, and compare the first network snapshot and the second network snapshot to identify a difference between the first network snapshot and the second network snapshot.

Mechanism for identifying differences between network snapshots

This disclosure provides solutions for automatically grouping network devices (e.g., endpoints) into clusters based on device characteristics. In some aspects, the disclosed technology also provides solutions for generating user selectable queries based on cluster characteristics. A process of the disclosed technology can include steps for identifying one or more device characteristics associated with a first network device, identifying one or more cluster characteristics for each of a first cluster and a second cluster, and comparing the device characteristics associated with the first network device with the one or more cluster characteristics for the first cluster and the second cluster. The process can further include steps for adding the first network device to the first cluster based on the cluster characteristics for the first cluster and the device characteristics for the first network device. Systems and machine-readable media are also provided.

Endpoint cluster assignment and query generation

Systems, methods, and computer-readable media for gathering network intrusion counter-intelligence. A system can maintain a decoy network environment at one or more machines. The system can identify a malicious user accessing network services through the network environment. Further, the system can receive network service access requests from the user at one or more machines in the network environment and subsequently direct the network service access requests from the malicious user to the decoy network environment based on an identification of the malicious user. The network services access requests can be satisfied with network service access responses generated in the decoy network environment. Subsequently, the system can maintain malicious user analytics based on the network service access requests of the malicious user that are directed to the decoy network environment.

Network intrusion counter-intelligence

The disclosed technology relates to intent driven network management. A system is configured to maintain an inventory store comprising records for a set of network entities in a network, wherein each network entity in the set of network entities is associated with a record in the inventory store. The system receives a user intent statement comprising an action and a flow filter representing network data flows on which the action is to be applied and queries, based on the flow filter, the inventory store to identify a plurality of network entities in the set of network entities to which the user intent statement applies. The system generates a plurality of network policies that implement the user intent statement based on the plurality of network entities and the action and enforces the plurality network policies.

Intent driven network policy platform

Systems, methods, and computer-readable for defining host functionalities in a computing environment include obtaining two or more snapshots comprising information pertaining to two or more processes executing in two or more hosts, the two or more snapshots being obtained at two or more points in time from the two or more hosts. One or more long-running processes amongst the two or more processes are identified based on one or more criteria associated with long-running processes. One or more priorities associated with the one or more long-running processes and used for defining functionalities for at least a subset of the two or more hosts, where high priorities are assigned to long-running processes, such as web server or database server processes, which are unique to at least the subset of the two or more hosts. Resources may be provisioned based on these host functionalities.

Provisioning resources for monitoring hosts based on defined functionalities of hosts

The disclosed technology relates to a network agent for generating platform specific network policies. A network agent is configured to receive a platform independent network policy from a network policy system, determine implementation characteristics of the network entity, generate platform specific policies from the platform independent network policy based on the implementation characteristics of the network entity, and implement the platform specific policies on the network entity.

Network agent for generating platform specific network policies

Aspects of the disclosed technology provide methods for automatically tuning load-balancer configurations in a network environment. In some implementations, a process of the disclosed technology includes steps for collecting flow records of traffic flow segments at a middle box in a network environment, the traffic flow segments corresponding to one or more traffic flows passing through the middle box, analyzing the flow records to identify one or more traffic patterns in the network environment, and automatically updating a load balancer configuration based on the one or more traffic patterns, wherein updating the load balancer configuration improves at least one traffic flow parameter for at least one of the traffic flows passing through the middle box. Systems and machine-readable media are also provided.

Load balancing configuration based on traffic flow telemetry

Systems, methods, and computer-readable media for flow stitching network traffic flow segments at a middlebox in a network environment. In some embodiments, flow records of traffic flow segments at a middlebox in a network environment are collected. The flow records can include transaction identifiers assigned to the traffic flow segments. Sources and destinations of the traffic flow segments with respect to the middlebox can be identified using the flow records. Further, the traffic flow segments can be stitched together to form a plurality of stitched traffic flows at the middlebox based on the transaction identifiers and the sources and destinations of the traffic flow segments in the network environment with respect to the middlebox. A configuration of the middlebox operating in the network environment can be identified based on the stitched traffic flows at the middlebox in the network environment.

Automatic configuration discovery based on traffic flow data

An example method includes a sensor detecting multiple packets of a flow during a specified total time period (e.g., a reporting time period). The total time period can be subdivided into multiple time periods. The sensor can analyze the detected packets to determine an amount of network utilization for each of the time periods. The sensor can then generate a flow summary based on the network utilization and the flow and send the flow summary to an analytics engine. Multiple other sensors can do similarly for their respective packets and flows. The analytics engine can receive the flow summaries from the various sensors and determine a correspondence between flow with high network utilization at a specific time period and a node or nodes. These nodes that experienced multiple flows with high network utilization for a certain period of time can be identified as experiencing a microburst.

Federated microburst detection

Aspects of the disclosed technology relate to ways to authenticate customer/subscriber access to a policy update stream. A process of the technology can include steps for instantiating a network monitoring device in response to a request, the request comprising one or more configuration parameters for the network monitoring device, and receiving a first certificate from the network monitoring device, wherein the first certificate is based on the one or more configuration parameters. In some aspects, the steps can further include sending the first certificate to a processing pipeline for authentication, wherein the processing pipeline is configured to authenticate the first certificate based on a second certificate received by the processing pipeline from the network monitoring device. Systems and machine readable media are also provided.

Secure publishing for policy updates

Disclosed is a system configured to receive a set of network snapshot segments from an output stream of a stream processing service, compile the set of network snapshot segments from the set of messages into a first network snapshot and a second network snapshot, and compare the first network snapshot and the second network snapshot to identify a difference between the first network snapshot and the second network snapshot.

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Fremont, CA, United States of America

Shashi Gandham