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Network Working Group                                       H. Song, Ed.
Internet-Draft                                                   T. Zhou
Intended status: Informational                                     Z. Li
Expires: September 2, 2018                                        Huawei
                                                           March 1, 2018

                  Toward a Network Telemetry Framework


   This document suggests the necessity of a framework of network
   telemetry and articulates the categories and components of such a
   framework.  The requirement, challenges, existing solutions, and
   future directions are discussed for each category of the framework.
   The framework for network telemetry helps to set a common ground for
   the collection of related works and put future developments into

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in RFC 2119 [RFC2119].

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
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   Drafts is at https://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
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   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on September 2, 2018.

Copyright Notice

   Copyright (c) 2018 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of
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Table of Contents

   1.  Motivation  . . . . . . . . . . . . . . . . . . . . . . . . .   2
     1.1.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.2.  Terminology and Abbreviations . . . . . . . . . . . . . .   4
     1.3.  Network Telemetry . . . . . . . . . . . . . . . . . . . .   5
     1.4.  The Necessity of a Network Telemetry Framework  . . . . .   6
   2.  Network Telemetry Framework . . . . . . . . . . . . . . . . .   7
     2.1.  Existing Works Mapped in the Framework  . . . . . . . . .   9
     2.2.  Management Plane Telemetry  . . . . . . . . . . . . . . .  10
       2.2.1.  Requirements and Challenges . . . . . . . . . . . . .  10
       2.2.2.  Push Extensions for NETCONF . . . . . . . . . . . . .  11
       2.2.3.  gRPC Network Management Interface . . . . . . . . . .  11
     2.3.  Control Plane Telemetry . . . . . . . . . . . . . . . . .  12
       2.3.1.  Requirements and Challenges . . . . . . . . . . . . .  12
       2.3.2.  BGP Monitoring Protocol . . . . . . . . . . . . . . .  12
     2.4.  Data Plane Telemetry  . . . . . . . . . . . . . . . . . .  12
       2.4.1.  Requirements and Challenges . . . . . . . . . . . . .  12
       2.4.2.  Dynamic Network Probe . . . . . . . . . . . . . . . .  13
       2.4.3.  IP Flow Information Export (IPFIX) protocol . . . . .  13
       2.4.4.  In-Situ OAM . . . . . . . . . . . . . . . . . . . . .  13
   3.  Security Considerations . . . . . . . . . . . . . . . . . . .  14
   4.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  14
   5.  Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  14
   6.  Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .  14
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  14
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .  14
     7.2.  Informative References  . . . . . . . . . . . . . . . . .  15
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  16

1.  Motivation

   Intent-based automatic network is the logical next step of network
   evolution, aiming to reduce human labor, make the most efficient use
   of network resources, and provide better services.  Tools based on
   machine learning technologies and big data analytics are powerful for
   faults, anomaly, pattern, and policy violation detection.  Some tools
   can even predict future events based on history data.  The

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   observation and inference from the network data can guide the network
   policy updates for planning, intrusion prevention, optimization, and
   self-healing.  A closed control loop is therefore achieved.

   Network OAM provides necessary visibilities to a network.  It plays
   an important role in Intend-based Networks (IBN).

1.1.  Use Cases

   Specifically, we have identified a few key network OAM use cases that
   service providers need the most.  All these use cases involves the
   data extracted from the network data plane and sometimes from the
   network control plane and management plane:

   Policy Compliance:  Network policies are the rules that constraint
      the services for network access.  For example, a service function
      chain is a policy that requires the selected flows to pass through
      a set of network functions in order.  While a policy is enforced,
      the compliance needs to be monitored continuously.

   SLA Compliance:  A service-level agreement defines the level of
      service a user expects from a service provider, which include the
      metrics for the service measurement and remedy/penalty procedures
      when the service level misses the agreement.  Users need to check
      if they get the service as promised and service providers need to
      evaluate how they can deliver the services that can meet the
      Service Level Agreement (SLA).

   Root Cause Analysis:  Network failure often involves a sequence of
      chain events and the source of the failure is not straightforward
      to identify, especially when t:0he failure is sporadic.  While
      machine learning or other data analytics technologies can be used
      for root cause analysis, it up to the network to provide all the
      relevant data for analysis.

   Load Balancing and Traffic Engineering:  Service providers are
      motivated to optimize their network utilization for better ROI or
      lower CAPEX.  The first step is to know the real-time network
      condition before applying policies to steer the user traffic or
      adjust the load balancing algorithm.  In some cases the network
      micro-bursts need to be detected in a very short time-frame so
      does the fine grained traffic control can be applied to avoid the
      possible network congestion.

   Packet Drop Detection:  Sporadic packet drops in networks are
      notoriously hard to locate and debug.  Network operators are
      plagued by the lack of tools that can identify the packet drop

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      locations and reasons.  Both active and passive measurements are
      not very effective in solving this problem.

   These use cases show that the conventional OAM techniques are not
   enough for the following reasons:

   o  Most use cases need to continuously monitor the network and
      dynamically refine the data collection in real-time.  The poll-
      based low-frequency data collection is ill-suited for these
      applications.  Streaming data directly pushed from the data source
      is preferred.

   o  Various data are needed from any place ranging from the packet
      processing engine to the QoS traffic manager.  Traditional data
      plane devices cannot provide the necessary probes.  An open and
      programmable data plane is therefore needed.

   o  Many application scenarios need to correlate data from multiple
      sources (e.g., from distributed nodes or from different network
      plane).  A piecemeal solution is often lack of the capability to
      consolidate the data from multiple sources.  The composition of a
      complete solution can be guided by a comprehensive framework.

   o  The passive measurement techniques can either consume too much
      network resources and render too much redundant data, or lead to
      inaccurate results.  The active measurement techniques are
      indirect, and they can interfere with the user traffic.  We need
      techniques that can collect direct and on-demand data from user

1.2.  Terminology and Abbreviations

   AI:  Artificial Intelligence.  Use machine-learning based
      technologies to automate network operation.

   BMP:  BGP Monitoring Protocol

   DNP:  Dynamic Network Probe

   gNMI:  gPRC Network Managment Interface

   gRPC:  gRPC Remote Procesure Call

   IBN:  Intent-Based Network

   IPFIX:  IP Flow Information Export Protocol

   IPFPM:  IP Flow Performance Measurement

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   IOAM:  In-situ OAM

   NETCONF:  Network Configuration Protocol

   Network Telemetry:  A general term for techniques to gain network
      visibility, through network data collection for analysis and

   NMS:  Network Management System

   OAM:  Operations, Administration, and Maintenance.  A group of
      network management functions that provide network fault
      indication, fault localization, performance information, and data
      and diagnosis functions.

   SNMP:  Simple Network Managment Protocol

   YANG:  A data modeling language for NETCONF

   YANG FSM:  A YANG model to define device side finite state machine

   YANG PUSH:  A method to subscribe pushed data from remote YANG

1.3.  Network Telemetry

   For a long time, network OAM applications rely on protocols such as
   SNMP [RFC1157] to monitor the networks.  SNMP can only provide
   limited information about the network.  Since SNMP is poll-based, it
   incurs low data rate and high processing overhead.  Such drawbacks
   make SNMP unsuitable for today's automatic network applications.

   Network telemetry has emerged as a mainstream technical term to refer
   to the newer technologies of data collection and consumption in the
   IBN paradigm, distinguishing itself form the convention technologies
   for network OAM.  It is expected that the network telemetry can
   provide the necessary network visibility for automated network OAM,
   address the shortcomings of the conventional technologies, and allow
   the emergence of new technologies.

   Although the network telemetry technologies continue evolving,
   several defining characteristics of network telemetry have been well

   o  Instead of polling data from the network devices, the telemetry
      collector subscribes the streaming data pushed from the data
      source in network devices.

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   o  The data is normalized and encoded efficiently for export.

   o  The data is model-based which allows applications to configure and
      consume data with ease.

   In addition, we believe the ideal network telemetry should also
   support the following features:

   o  The data can be customized at runtime to cater the specific need
      of applications.  This needs the support of a programmable data
      plane which allows probes to be deployed at flexible locations.

   o  The data for a single application can come from multiple data
      sources (e.g., cross domain, cross device, and cross layer) and
      need to be correlated to take effect.

1.4.  The Necessity of a Network Telemetry Framework

   Big data analytics and machine-learning based AI technologies are
   applied for network OAM, relying on abundant data from networks.  The
   single-sourced and static data acquisition cannot meet the data
   requirements.  It is desired to have a framework that integrates
   multiple telemetry approaches from different layers and angels, and
   allows flexible combinations for different applications.  The
   framework will benefit the application development for the following

   o  Network visibility presents multiple viewpoints.  For example, the
      device viewpoint takes the network infrastructure as the
      monitoring object from which the network topology and device
      status can be acquired; the traffic viewpoint takes the flows or
      packets as the monitoring object from which the traffic quality
      and path can be acquired.  An application may need to switch its
      viewpoint during operation.  It may also need to correlate a
      service and its network experience to acquire the comprehensive

   o  Applications require the network telemetry to be elastic in order
      to efficiently use the network resource and reduce the performance
      impact.  The routine network monitoring covers the entire network
      with low data sampling rate.  When issues arise or trends emerge,
      the telemetry data source can be refocused and the data rate can
      be boosted.

   o  Efficient data fusion is critical for applications to reduce the
      overall quantity of data and improve the accuracy of analysis.

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   So far, some telemetry related works have been done within IETF.
   However, these works are fragmented and scattered in different
   working groups.  The lack of coherence makes it difficult to assemble
   a comprehensive network telemetry system and causes repetitive and
   redundant works.

   A formal network telemetry framework is needed for constructing a
   working system.  The framework should cover the concepts and
   components from the standardization perspective.  This document
   clarifies the layers on which the telemetry is exerted and decomposes
   the telemetry system into a set of distinct components that the
   existing and future works can easily map to.

2.  Network Telemetry Framework

   The telemetry can be applied on the data plane, the control plane,
   and the management plane in a network, as shown in Figure 1.

                   |                              |
                   |      OAM Applications        |
                   |                              |
                        ^      ^           ^
                        |      |           |
                        V      |           V
                   |           |   |              |
                   | Control Pl|ane|              |
                   | Telemetry | <--->            |
                   |           |   |              |
                   |      ^    V   |  Management  |
                   +------|--------+  Plane       |
                   |      V        |  Telemetry   |
                   |               |              |
                   | Data Plane  <--->            |
                   | Telemetry     |              |
                   |               |              |

        Figure 1: Layer Category of the Network Telemetry Framework

   Note that the interaction with OAM applications can be indirect.  For
   example, in the management plane telemetry, the management plane may
   need to acquire data from the data plane.  On the other hand, an OAM
   application may involve more than one plane simultaneously.  For

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   example, an SLA compliance application may require both the data
   plane telemetry and the control plane telemetry.

   At each plane, the telemetry can be further partitioned into five
   distinct components:

   Data Source:  Determine where the original data is acquired.  The
      data source usually just provide raw data which needs further
      processing.  A data source can be considered a probe.  A probe can
      be statically installed or dynamically installed.

   Data Subscription:  Determine the protocol and channel for
      applications to acquire desired data.  Data subscription is also
      responsible to define the desired data that might not directly
      available form data sources.  The subscribe data can be described
      by a model.  The model can be statically installed or dynamically

   Data Generation:  The original data needs to be processed, encoded,
      and formatted in network devices to meet application subscription
      requirements.  This may involve in-network computing and
      processing on either the fast path or the slow path in network

   Data Export:  Determine how the ready data are delivered to

   Data Analysis:  In this final step, data is consumed by applications.
      Data analysis can be interactive.  It may initiate further data

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                   |                              |
                   |      Data Analysis           |
                   |                              |
                           |               ^
                           |               |
                           V               |
                   |               |              |
                   | Data          | Data         |
                   | Subscription  | Export       |
                   |               |              |
                   |                              |
                   |       Data Generation        |
                   |                              |
                   |                              |
                   |       Data Source            |
                   |                              |

          Figure 2: Components in the Network Telemetry Framework

   Since most existing standard-related works belong to the first four
   components, in the remaining of the document, we focus on these
   components only.

2.1.  Existing Works Mapped in the Framework

   The following table provides a non-exhaustive list of existing works
   (mainly published in IETF and with the emphasis on the latest new
   technologies) and shows their positions in the framework.

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            |           | Management   | Control       | Data         |
            |           | Plane        | Plane         | Plane        |
            |           | YANG Data    | Control Proto.| Flow/Packet  |
            | Data      | Store        | Network State | Statistics   |
            | Source    |              |               | States       |
            |           |              |               |              |
            |           | gPRC         | NETCONF/YANG  | NETCONF/YANG |
            | Data      | YANG PUSH    | BGP           | YANG FSM     |
            | Subscribe |              |               |              |
            |           |              |               |              |
            |           | Soft DNP     | Soft DNP      | In-situ OAM  |
            | Data      |              |               | IPFPM        |
            | Generation|              |               | Hard DNP     |
            |           |              |               |              |
            |           | gRPC         | BMP           | IPFIX        |
            | Data      | YANG PUSH    |               | UDP          |
            | Export    | UDP          |               |              |
            |           |              |               |              |

                         Figure 3: Existing Works

2.2.  Management Plane Telemetry

2.2.1.  Requirements and Challenges

   The management plane of the network element interacts with the
   Network Management System (NMS), and provides information such as
   performance data, network logging data, network warning and defects
   data, and network statistics and state data.  Some legacy protocols
   are widely used for the management plane, such as SNMP and Syslog,
   but these protocols do not meet the requirements of the automatic
   network OAM applications.

   New management plane telemetry protocols should consider the
   following requirements:

   Convenient Data Subscription:  An application should have the freedom
      to choose the data export means such as the data types and the
      export frequency.

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   Structured Data:  For automatic network OAM, machine will replace
      human for network data comprehension.  The schema languages such
      as YANG can efficiently describe structured data and normalize
      data encoding and transformation.

   High Speed Data Transport:  In order to retain the information, a
      server need to send a large amount of data at high frequency.
      Compact encoding format is needed to compress the data and improve
      the data transport efficiency.  The push mode, by replacing the
      poll mode, can also reduce the interactions between clients and
      servers, which help to improve the server's efficiency.

2.2.2.  Push Extensions for NETCONF

   NETCONF [RFC6241] is one popular network management protocol, which
   is also recommended by IETF.  Although it can be used for data
   collection, NETCONF is good at configurations.  YANG Push
   [I-D.ietf-netconf-yang-push] extends NETCONF and enables subscriber
   applications to request a continuous, customized stream of updates
   from a YANG datastore.  Providing such visibility into changes made
   upon YANG configuration and operational objects enables new
   capabilities based on the remote mirroring of configuration and
   operational state.  Moreover, distributed data collection mechanism
   [I-D.zhou-netconf-multi-stream-originators] via UDP based publication
   channel [I-D.ietf-netconf-udp-pub-channel] provides enhanced
   efficiency for the NETCONF based telemetry.

2.2.3.  gRPC Network Management Interface

   gRPC Network Management Interface (gNMI)
   [I-D.openconfig-rtgwg-gnmi-spec] is a network management protocol
   based on the gRPC [I-D.kumar-rtgwg-grpc-protocol] RPC (Remote
   Procedure Call) framework.  With a single gRPC service definition,
   both configuration and telemetry can be covered. gRPC is an HTTP/2
   [RFC7540] based open source micro service communication framework.
   It provides a number of capabilities that makes it well-suited for
   network telemetry, including:

   o  Full-duplex streaming transporting model combined with a binary
      encoding mechanism provided further improved telemetry efficiency.

   o  gRPC provides higher-level features consistency across platforms
      that common HTTP/2 libraries typically do not.  This
      characteristic is especially valuable for the fact that telemetry
      data collectors are normally resides on a large variety of

   o  The build in load balancing and failover mechanism.

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2.3.  Control Plane Telemetry

2.3.1.  Requirements and Challenges

   The control plane runs the routing protocol (e.g., BGP, OSPF, and IS-
   IS) to calculate the routing table for a network device.  The control
   plane telemetry monitors the routing protocols to ensure they are
   working properly.

2.3.2.  BGP Monitoring Protocol

   BGP Monitoring Protocol (BMP) [RFC7854] is used to monitor BGP
   sessions and intended to provide a convenient interface for obtaining
   route views.  The data is collected from the Adjacency-RIB-In routing
   tables, which are the pre-policy tables, meaning that the routes in
   these tables have not been filtered or modified by routing policies.
   So the monitoring station can receive all routes, not just the active

2.4.  Data Plane Telemetry

2.4.1.  Requirements and Challenges

   An effective data plane telemetry system relies on the data that the
   network device can expose.  The data's quality, quantity, and
   timeliness must meet some stringent requirements.  This raises some
   challenges to the network data plane devices where the first hand
   data originate.

   o  A data plane device's main function is user traffic processing and
      forwarding.  While supporting network visibility is important, the
      telemetry is just an auxiliary function and it should not impede
      normal traffic processing and forwarding (i.e., the performance is
      not lowered and the behavior is not altered due to the telemetry

   o  The network OAM applications requires end-to-end visibility from
      various sources, which results in a huge volume of data.  However,
      the sheer data quantity should not stress the network bandwidth,
      regardless of the data delivery approach (i.e., through in-band or
      out-of-band channels).

   o  The data plane devices must provide the data in a timely manner
      with the minimum possible delay.  Long processing, transport,
      storage, and analysis delay can impact the effectiveness of the
      control loop and even render the data useless.

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   o  The data should be structured and labeled, and easy for
      applications to parse and consume.  At the same time, the data
      types needed by applications can vary significantly.  The data
      plane devices need to provide enough flexibility and
      programmability to support the precise data provision for

   o  The data plane telemetry should support incremental deployment and
      work even though some devices are unaware of the system.  This
      challenge is highly relevant to the standards and legacy networks.

2.4.2.  Dynamic Network Probe

   Hardware based Dynamic Network Probe (DNP) [I-D.song-opsawg-dnp4iq]
   provides a programmable means to customize the data that an
   application collects from the data plane.  A direct benefit of DNP is
   the reduction of the exported data.  A full DNP solution covers
   several components including data source, data subscription, and data
   generation.  The data subscription needs to define the custom data
   which can be composed and derived from the raw data sources.  The
   data generation takes advantage of the moderate in-network computing
   to produce the desired data.

   While DNP can introduce unforeseeable flexibility to the data plane
   telemetry, it also faces some challenges.  It requires a flexible
   data plane that can be dynamically reprogrammed at runtime.  The
   programming API is yet to be defined.

2.4.3.  IP Flow Information Export (IPFIX) protocol

   Traffic on a network can be seen as a set of flows passing through
   network elements.  IP Flow Information Export (IPFIX) [RFC7011]
   provides a means of transmitting traffic flow information for
   administrative or other purposes.  A typical IPFIX enabled system
   includes a pool of Metering Processes collects data packets at one or
   more Observation Points, optionally filters them and aggregates
   information about these packets.  An Exporter then gathers each of
   the Observation Points together into an Observation Domain and sends
   this information via the IPFIX protocol to a Collector.

2.4.4.  In-Situ OAM

   Traditional passive and active monitoring and measurement techniques
   are either inaccurate or resource-consuming.  It is preferable to
   directly acquire data associated with a flow's packets when the
   packets pass through a network.  In-situ OAM (iOAM)
   [I-D.brockners-inband-oam-requirements], a data generation technique,
   embeds a new instruction header to user packets and the instruction

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   directs the network nodes to add the requested data to the packets.
   Thus, at the path end the packet's experience on the entire
   forwarding path can be collected.  Such firsthand data is invaluable
   to many network OAM applications.

   However, iOAM also faces some challenges.  The issues on performance
   impact, security, scalability and overhead limits, encapsulation
   difficulties in some protocols, and cross-domain deployment need to
   be addressed.

3.  Security Considerations


4.  IANA Considerations

   This document includes no request to IANA.

5.  Contributors

   The other contributors of this document are listed as follows.

   o  Yunan Gu, Huawei

6.  Acknowledgments


7.  References

7.1.  Normative References

   [RFC1157]  Case, J., Fedor, M., Schoffstall, M., and J. Davin,
              "Simple Network Management Protocol (SNMP)", RFC 1157,
              DOI 10.17487/RFC1157, May 1990,

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,

   [RFC6241]  Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
              and A. Bierman, Ed., "Network Configuration Protocol
              (NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,

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   [RFC7011]  Claise, B., Ed., Trammell, B., Ed., and P. Aitken,
              "Specification of the IP Flow Information Export (IPFIX)
              Protocol for the Exchange of Flow Information", STD 77,
              RFC 7011, DOI 10.17487/RFC7011, September 2013,

   [RFC7540]  Belshe, M., Peon, R., and M. Thomson, Ed., "Hypertext
              Transfer Protocol Version 2 (HTTP/2)", RFC 7540,
              DOI 10.17487/RFC7540, May 2015,

   [RFC7854]  Scudder, J., Ed., Fernando, R., and S. Stuart, "BGP
              Monitoring Protocol (BMP)", RFC 7854,
              DOI 10.17487/RFC7854, June 2016,

7.2.  Informative References

              Brockners, F., Bhandari, S., Dara, S., Pignataro, C.,
              Gredler, H., Leddy, J., Youell, S., Mozes, D., Mizrahi,
              T., <>, P., and r. remy@barefootnetworks.com,
              "Requirements for In-situ OAM", draft-brockners-inband-
              oam-requirements-03 (work in progress), March 2017.

              Zheng, G., Zhou, T., and A. Clemm, "UDP based Publication
              Channel for Streaming Telemetry", draft-ietf-netconf-udp-
              pub-channel-01 (work in progress), November 2017.

              Clemm, A., Voit, E., Prieto, A., Tripathy, A., Nilsen-
              Nygaard, E., Bierman, A., and B. Lengyel, "YANG Datastore
              Subscription", draft-ietf-netconf-yang-push-14 (work in
              progress), February 2018.

              Kumar, A., Kolhe, J., Ghemawat, S., and L. Ryan, "gRPC
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Authors' Addresses

   Haoyu Song (editor)
   2330 Central Expressway
   Santa Clara

   Email: haoyu.song@huawei.com

   Tianran Zhou
   156 Beiqing Road
   Beijing, 100095
   P.R. China

   Email: zhoutianran@huawei.com

   Zhenbin Li
   156 Beiqing Road
   Beijing, 100095
   P.R. China

   Email: lizhenbin@huawei.com

Song, et al.            Expires September 2, 2018              [Page 16]

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