Juniper Networks, Inc.

International Business Machines Corporation

Rajneesh Kumar

Peyush Gupta

Vijay Sai Ram Paruchuri

Unni Dilip

Bhaskar Jain

Sanjay Kumar Gupta

Vishal Anand

Vijay S Patil

Sai Sundar Ramamurthy

Sahadev Dey

Amit Patra

Ravi Kumar G V Subrahmanya

Michael A Gaynes

Sushumna Iruvanti

Steven Paul Ostrander

Thomas Edward Lombardi

Sankar Ramamoorthi

Steve Ostrander

Jae-Woong Nah

Jeffrey Donald Gelorme

Prabjit Singh

Eric D Perfecto

Claudius Feger

David Lewis Gardell

Janak G Patel

James N Humenik

William E Bernier

Brian Michael Erwin

Peter Slota, Jr

Randall G Kemink

Marcus E Interrante

Chenzhou Lian

Ijeoma M Nnebe

Bharat Dhaker

John Lawson

Stephen P Ostrander

In some implementations, a network device may determine throughput rate metrics for a plurality of processing units of the network device that are processing network traffic of a network. The network device may maintain the throughput rate metrics in a status table associated with the plurality of processing units. The network device may receive tunnel traffic associated with a particular tunnel of the network. The network device may determine, based on a characteristic of the tunnel traffic, a potential throughput rate associated with processing the tunnel traffic. The network device may direct the tunnel traffic to a particular processing unit, of the plurality of processing units, based on the potential throughput rate and the throughput rate metrics indicated in the status table.

Tunnel processing distribution based on traffic type and learned traffic processing metrics

In an example, a method includes obtaining, for a software-defined wide area network (SD-WAN) system having a plurality of a wide area network (WAN) links for an SD-WAN service, a first service level agreement (SLA) rule that matches a first application, the first SLA rule having a first priority that indicates a priority of the first application; obtaining, for the SD-WAN system, a second SLA rule that matches a second application, the second SLA rule having a second priority that indicates a priority of the second application; assigning, for the SD-WAN system, the first application and the second application to a first WAN link of the plurality of WAN links; and in response to determining that the first WAN link has violated the first SLA rule that matches the first application, assigning, by the SD-WAN system, the second application to a second WAN link of the plurality of WAN links.

Wan link selection for SD-WAN services

A first device may provide, periodically throughout a test session and to neighboring devices that are in a network with the first device, a message request for measuring network performance. The neighboring devices, upon receiving the request message, are to use a relay mechanism to determine network performance indicator (NPI) values. The first device may receive, from the neighboring devices and periodically throughout the test session, a response message that includes the NPI values. The first device may determine additional NPI values that measure the network performance between the first device and the neighboring devices. The first device may determine overall NPI values based on the NPI values and the additional NPI values. The first device may identify a preferred next-hop to one of the neighboring devices based on the overall NPI values, where the preferred next-hop is part of a preferred path through the network.

Network performance monitoring using an active measurement protocol and relay mechanism

In general, the disclosure describes techniques for evaluating application quality of experience metrics over a software-defined wide area network. For instance, a network device may receive an application data packet of a data flow for an application. In response to receiving the application data packet, the network device may assign the data flow to a first link of a plurality of links and initiate a probing process for the data flow on the first link to determine one or more quality of experience (QoE) metrics for the first link. The network device may, at a later time, detect that the data flow is no longer being received. In response to detecting that the data flow is no longer being received, the network device may cease the probing process for the data flow on the first link.

On-demand probing for quality of experience metrics

In general, the disclosure describes techniques for adaptively determining one or more parameters of a service level agreement of an application. For instance, a network device may monitor round-trip times of a plurality of packets of a data flow of an application being transmitted over a link between an application server and a client device. The network device may determine an amount of retransmission of packets occurring during transmission of the plurality of packets of the data flow. The network device may predict, based at least in part on the round-trip times of the plurality of packets of the data flow and the amount of retransmission of packets occurring during transmission of the plurality of packets of the data flow, a round-trip time parameter for a service level agreement associated with the application.

Dynamic prediction and management of application service level agreements

This disclosure describes techniques that include adding information to a network service header in packets being processed by a set of compute nodes in a service chain. The information added to the network service header can be used during selection of the next hop in a service chain, and may be used to help ensure that service level agreements (SLA) are met with respect to one or more metrics. In one example, this disclosure describes a method that includes receiving, by a service complex having a plurality of service nodes, a packet associated with a service chain representing a series of services to be performed on the packet by one or more of the plurality of service nodes; identifying, by the service complex, one or more service chain constraints associated with the service chain; and modifying the packet, by the service complex, to include information about the service chain constraints.

SLA packet steering in network service function chaining

A network device includes a memory and one or more processors in communication with the memory. The one or more processors are configured to configure a proxy server to forward a request for data from a client device to a data server and to forward, from the data server to the client device, a response message that is responsive to the request for data. The one or more processors are further configured to receive an indication of a set of header fields for the response message that indicates a first time specifying when the data server received the request for data and a second time specifying when the response message was sent by the data server and generate a metric for a performance of the data server based on the first time and the second time.

Monitoring server performance using server processing time

This disclosure is related to devices, systems, and techniques for using a Domain Name System (DNS) server to identify one or more network devices capable of operating according to a protocol. For example, a DNS system device includes a memory and one or more processors implemented in circuitry. The one or more processors are configured to receive, from a client device, a DNS query including a specification of a hostname and a request for an MP-TCP capability, determine, using the memory, at least one IP address corresponding to the hostname and corresponding to one of the devices that is MP-TCP capable, and send, to the client device, a DNS response including an indication of the at least one of the IP addresses.

Using DNS to communicate MC-TCP capability of server devices

In general, the disclosure describes techniques for assigning traffic originating from an unknown application to a link based on known application quality of experience metrics. For instance, a network device may receive an application data packet of a data flow for an application and determine an application signature of the application data packet. The network device may determine whether the application signature matches an entry in an application signature database, and if the application signature does not match, the network device may identify a class of the application based on one or more characteristics of the application data packet. The network device may then assign the application data packet of the data flow to a first link of a plurality of links based on the class of the application and quality of experience (QoE) metrics for each link.

Satisfying service level agreement metrics for unknown applications

In general, the disclosure describes techniques for evaluating application quality of experience metrics over a software-defined wide area network. For instance, a network device may receive an application data packet of a data flow for an application and send a first set of probe packets, configured according to an initial probing profile, over each of one or more links. The network device may monitor the data flow to determine one or more characteristics of the data flow and generate an updated probing profile based on the one or more characteristics of the data flow. The network device may then send a second set of one or more probe packets, configured according to the updated probing profile, over each of the one or more links.

Real-time application-driven synthetic probing

An approach is provided for monitoring disk utilization at an object level. At a first time a first size of an object in a System i computing platform is determined by calling an application programming interface (API). At a second time a second size of the object is determined by calling the API. A difference between the first and second sizes is determined. The difference is determined to be greater than a threshold. Based on the difference exceeding the threshold, an alert is sent indicating growth at the object level rather than at an auxiliary storage pool level. The API is called to obtain the sizes of libraries in the System i computing platform. Differences between the sizes of the libraries at a user-entered start date and the current time are determined and presented. A report including the differences is generated and sent.

Disk utilization analysis

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Bengaluru, India

Rajneesh Kumar