Toward a Network Telemetry Framework
draft-song-ntf-01
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| Authors | Haoyu Song , Tianran Zhou , Zhenbin Li | ||
| Last updated | 2018-03-19 | ||
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draft-song-ntf-01
Network Working Group H. Song, Ed.
Internet-Draft T. Zhou
Intended status: Informational Z. Li
Expires: September 19, 2018 Huawei
March 18, 2018
Toward a Network Telemetry Framework
draft-song-ntf-01
Abstract
This document suggests the necessity for an architectural framework
to address network telemetry and articulates the categories and
components of such a framework. The requirements, challenges,
existing solutions, and future directions are discussed for each
category of the framework. The framework for network telemetry helps
to set some common ground for the collection of related works and put
future developments into perspective.
Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
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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time. It is inappropriate to use Internet-Drafts as reference
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This Internet-Draft will expire on September 19, 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
2. The Necessity of a Network Telemetry Framework . . . . . . . 6
3. Network Telemetry Framework . . . . . . . . . . . . . . . . . 7
3.1. Existing Works Mapped in the Framework . . . . . . . . . 9
3.2. Management Plane Telemetry . . . . . . . . . . . . . . . 10
3.2.1. Requirements and Challenges . . . . . . . . . . . . . 10
3.2.2. Push Extensions for NETCONF . . . . . . . . . . . . . 11
3.2.3. gRPC Network Management Interface . . . . . . . . . . 11
3.3. Control Plane Telemetry . . . . . . . . . . . . . . . . . 12
3.3.1. Requirements and Challenges . . . . . . . . . . . . . 12
3.3.2. BGP Monitoring Protocol . . . . . . . . . . . . . . . 12
3.4. Data Plane Telemetry . . . . . . . . . . . . . . . . . . 12
3.4.1. Requirements and Challenges . . . . . . . . . . . . . 12
3.4.2. Dynamic Network Probe . . . . . . . . . . . . . . . . 13
3.4.3. IP Flow Information Export (IPFIX) protocol . . . . . 13
3.4.4. In-Situ OAM . . . . . . . . . . . . . . . . . . . . . 13
4. Security Considerations . . . . . . . . . . . . . . . . . . . 14
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14
6. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 14
7. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 14
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 14
8.1. Normative References . . . . . . . . . . . . . . . . . . 14
8.2. Informative References . . . . . . . . . . . . . . . . . 15
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 16
1. Motivation
An intent-driven automated network is the logical next step for
network evolution, aiming to reduce human labor, make the most
efficient use of network resources, and provide better services more
aligned with customer requirements. Tools based on machine learning
technologies and big data analytics are powerful for fault detection
and isolation, identification of anomalies to normal behaviors,
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patterns, and policy violation detection. Some tools can even
predict future events based on historical data. The observation and
inference from collected network data can help guide network policy
updates for planning, intrusion prevention, optimization, and self-
healing. A closed control loop is therefore achieved.
1.1. Use Cases
Specifically, we have identified a few key network OAM use cases that
network operators 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, provide differentiate within a
service, or enforce specific treatment on the traffic. 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 network operator, 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 network operators 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
chained events and the source of the failure is not
straightforward to identify, especially when the 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: Network operators are
motivated to optimize their network utilization for better ROI or
lower CAPEX, as well as differentiation across services and/or
users of a given service. The first step is to know the real-time
network conditions before applying policies to steer the user
traffic or adjust the load balancing algorithm. In some cases
network micro-bursts need to be detected in a very short time-
frame so that fine grained traffic control can be applied to avoid
possible network congestion.
Packet Drop Detection: Sporadic packet drops in networks are
notoriously hard to locate and debug. Network operators are
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plagued by the lack of tools that can identify the packet drop
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 is 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 lacking 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
traffic.
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
IDN: Intent-Driven Network
IPFIX: IP Flow Information Export Protocol
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IPFPM: IP Flow Performance Measurement
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
measurement.
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
datastore
1.3. Network Telemetry
For a long time, network OAM applications have relied upon protocols
such as SNMP [RFC1157] to monitor the network. 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
IDN paradigm, distinguishing itself form the convention technologies
for network OAM. It is expected that network telemetry can provide
the necessary network visibility for automatic network OAM, address
the shortcomings of conventional technologies, and allow for the
emergence of new technologies.
Although the network telemetry technologies continue to evolve,
several defining characteristics of network telemetry have been well
accepted:
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o Instead of polling data from network devices, the telemetry
collector subscribes to the streaming data pushed from the data
source in network devices.
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 solution should
also support the following features:
o The data can be customized at runtime to cater to 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
needs to be correlated to take effect.
2. 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 desirable to have a framework that integrates
multiple telemetry approaches from different layers, and allows
flexible combinations for different applications. The framework will
benefit application development for the following reasons.
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
information.
o Applications require network telemetry to be elastic in order to
efficiently use the network resource and reduce the performance
impact. 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.
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o Efficient data fusion is critical for applications to reduce the
overall quantity of data and improve the accuracy of analysis.
So far, some telemetry related work has been done within IETF.
However, this work is 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 work.
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 work can easily map to.
3. Network Telemetry Framework
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
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need to acquire data from the data plane. On the other hand, an OAM
application may involve more than one plane simultaneously. For
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 provides 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 be directly
available form data sources. The subscription data can be
described by a model. The model can be statically installed or
dynamically installed.
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
devices.
Data Export: Determine how the ready data are delivered to
applications.
Data Analysis: In this final step, data is consumed by applications.
Data analysis can be interactive. It may initiate further data
subscription.
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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 work belongs to the first four
components, in the remainder of the document, we focus on these
components only.
3.1. 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 Work
3.2. Management Plane Telemetry
3.2.1. 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, machines 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 needs to send a large amount of data at high frequency.
Compact encoding formats are 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.
3.2.2. 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.
3.2.3. 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 transport 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 normally reside on a large variety of platforms.
o The built-in load-balancing and failover mechanism.
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3.3. Control Plane Telemetry
3.3.1. 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.
3.3.2. 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
routes.
3.4. Data Plane Telemetry
3.4.1. 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
functions).
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
applications.
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.
3.4.2. 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.
3.4.3. 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.
3.4.4. 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.
4. Security Considerations
TBD
5. IANA Considerations
This document includes no request to IANA.
6. Contributors
The other contributors of this document are listed as follows.
o Yunan Gu, Huawei
o James N. Guichard, Huawei
7. Acknowledgments
TBD.
8. References
8.1. 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,
<https://www.rfc-editor.org/info/rfc1157>.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[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,
<https://www.rfc-editor.org/info/rfc6241>.
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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,
<https://www.rfc-editor.org/info/rfc7011>.
[RFC7540] Belshe, M., Peon, R., and M. Thomson, Ed., "Hypertext
Transfer Protocol Version 2 (HTTP/2)", RFC 7540,
DOI 10.17487/RFC7540, May 2015,
<https://www.rfc-editor.org/info/rfc7540>.
[RFC7854] Scudder, J., Ed., Fernando, R., and S. Stuart, "BGP
Monitoring Protocol (BMP)", RFC 7854,
DOI 10.17487/RFC7854, June 2016,
<https://www.rfc-editor.org/info/rfc7854>.
8.2. Informative References
[I-D.brockners-inband-oam-requirements]
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.
[I-D.ietf-netconf-udp-pub-channel]
Zheng, G., Zhou, T., and A. Clemm, "UDP based Publication
Channel for Streaming Telemetry", draft-ietf-netconf-udp-
pub-channel-02 (work in progress), March 2018.
[I-D.ietf-netconf-yang-push]
Clemm, A., Voit, E., Prieto, A., Tripathy, A., Nilsen-
Nygaard, E., Bierman, A., and B. Lengyel, "YANG Datastore
Subscription", draft-ietf-netconf-yang-push-15 (work in
progress), February 2018.
[I-D.kumar-rtgwg-grpc-protocol]
Kumar, A., Kolhe, J., Ghemawat, S., and L. Ryan, "gRPC
Protocol", draft-kumar-rtgwg-grpc-protocol-00 (work in
progress), July 2016.
[I-D.openconfig-rtgwg-gnmi-spec]
Shakir, R., Shaikh, A., Borman, P., Hines, M., Lebsack,
C., and C. Morrow, "gRPC Network Management Interface
(gNMI)", draft-openconfig-rtgwg-gnmi-spec-01 (work in
progress), March 2018.
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Internet-Draft Network Telemetry Framework March 2018
[I-D.song-opsawg-dnp4iq]
Song, H. and J. Gong, "Requirements for Interactive Query
with Dynamic Network Probes", draft-song-opsawg-dnp4iq-01
(work in progress), June 2017.
[I-D.zhou-netconf-multi-stream-originators]
Zhou, T., Zheng, G., Voit, E., Clemm, A., and A. Bierman,
"Subscription to Multiple Stream Originators", draft-zhou-
netconf-multi-stream-originators-01 (work in progress),
November 2017.
Authors' Addresses
Haoyu Song (editor)
Huawei
2330 Central Expressway
Santa Clara
USA
Email: haoyu.song@huawei.com
Tianran Zhou
Huawei
156 Beiqing Road
Beijing, 100095
P.R. China
Email: zhoutianran@huawei.com
Zhenbin Li
Huawei
156 Beiqing Road
Beijing, 100095
P.R. China
Email: lizhenbin@huawei.com
Song, et al. Expires September 19, 2018 [Page 16]