Inband Flow Learning Framework
draft-hwy-opsawg-ifl-framework-00
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| Authors | Liuyan Han , Minxue Wang , Fan Yang | ||
| Last updated | 2022-03-03 | ||
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draft-hwy-opsawg-ifl-framework-00
OPSAWG Working Group L. Han
Internet-Draft M. Wang
Intended status: Informational China Mobile
Expires: 4 September 2022 F. Yang
Huawei Technologies
3 March 2022
Inband Flow Learning Framework
draft-hwy-opsawg-ifl-framework-00
Abstract
To deploy the inband performance measurement and flow information
telemetry on live traffic, this document proposes a framework of an
inband and flow based flow information learning mechanism called
Inband Flow Learning (IFL). This document also provides different
deployment approaches and considerations in practical network
deployment.
Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP
14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
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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Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
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 4 September 2022.
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Copyright Notice
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document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
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Please review these documents carefully, as they describe your rights
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Framework of Inband Flow Learning . . . . . . . . . . . . . . 3
4. Service Discovery . . . . . . . . . . . . . . . . . . . . . . 4
5. Inband Flow Information Telemetry Deployment . . . . . . . . 5
5.1. Telemetry Type . . . . . . . . . . . . . . . . . . . . . 5
5.2. Telemetry Policy . . . . . . . . . . . . . . . . . . . . 6
5.3. Telemetry Deployment . . . . . . . . . . . . . . . . . . 7
6. Inband Flow Information Telemetry Adjustment . . . . . . . . 7
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
8. Security Considerations . . . . . . . . . . . . . . . . . . . 8
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 8
9.1. Normative References . . . . . . . . . . . . . . . . . . 8
9.2. Informative References . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Introduction
Network telemetry [I-D.ietf-opsawg-ntf] is a technology for gaining
network insight by applying means of network data generation, data
collection, data correlation, and data consumption. It provides the
network visibility to the state and behavior of a network, which is
crucial for network operation and network load supervision. From
operator's perspective, it is important to monitor live traffic
running in the network, including the bandwidth occupied by the
traffic, traffic delay, traffic jitter and traffic packet loss.
Under this circumstance, inband performance measurement
[I-D.ietf-mpls-inband-pm-encapsulation] [I-D.ietf-6man-ipv6-alt-mark]
and inband flow information telemetry
[I-D.song-opsawg-ifit-framework] work complementary to provide the
network traffic supervision.
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To deploy the inband performance measurement and flow information
telemetry on live traffic, this document proposes a framework of an
inband and flow based flow information learning mechanism called
Inband Flow Learning (IFL). This document also provides different
deployment approaches and considerations in practical network
deployment. Note that this document focuses on generating telemetry
data object based on inband performance measurement of data packet.
Telemetry based on means other than inband performance measurement of
data packet is not within the scope of this document.
2. Terminology
IFL: Inband Flow Learning
IFITI: Inband Flow Information Telemetry Instance
3. Framework of Inband Flow Learning
The framework of Inband Flow Learning (IFL) includes three components
of Service Discovery, Inband Flow Information Telemetry Deployment
and Inband Flow Information Telemetry Adjustment shown in Figure 1.
+---------+---------------------+--------------------+--------------------+
|Component| Service | Inband Flow | Inband Flow |
| | Discovery | Information | Information |
| | |Telemetry Deployment|Telemetry Adjustment|
+---------+---------------------+--------------------+--------------------+
|Function | Flow | Telemetry type | Telemetry instance |
| | characteristic +--------------------+ aging |
| | acquisition | Telemetry policy | |
| | +--------------------+ |
| | | Telemetry instance| |
+---------+---------------------+--------------------+--------------------+
| Means |Configuration trigger| Controller Deploy | Data plane trigger |
| +---------------------+--------------------+--------------------+
| |Live traffic sampling| Device Deploy | Controller trigger |
+---------+---------------------+--------------------+--------------------+
Figure 1 Framework of Inband Flow Learning
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Service Discovery: before starting the telemetry on service flows,
characteristics of traffic which is currently being forwarded in
network should be analyzed. The traffic characteristics can be
acquired either from network operations or automatically generated
from the sampling of live traffics.
Inband Flow Information Telemetry Deployment: after acquiring the
traffic characteristics, telemetry of service flows can be planned
and deployed. In IFL, telemetry is based on a class of flow
characteristic and managed as an Inband Flow Information Telemetry
Instance (IFITI). Before the network node starts the telemetry, the
IFITI type and policy should be specified.
Inband Flow Information Telemetry Adjustment: when the traffic
changes, telemetry instance varies as well. This components includes
the identification of traffic change and further adjustment of
telemetry instances.
4. Service Discovery
Service discovery is a process of sampling to the service flow which
is being transmitted in network in order to further determine which
flow should be monitored. The characteristics of service flow are
represented as IP source address, IP destination address, TCP/UDP
port number, VRF, incoming/outgoing interface on network node, etc.
To target of service discovery is to obtain the flow characteristics.
There are two fundamental means to acquire the flow characteristics
including configuration triggered and sampling based on live
traffics. Regarding the means of triggered by configuration, not
only includes the configuration of Interface/IP address/VRF/Route...
configured on the network nodes, but also database of planed service
flow information stored on the controller and obtained from network
operations, such as a table of services between base station and core
network elements. On the other hand, sampling on the live traffic
means that the network node automatically samples the live traffic in
network, and dynamically generate flow characteristics based on live
traffic. It relies on the capability of forwarding plane of network
node. The comparison of two means are provided in Figure 2.
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+-----------+-----------------------+----------------------------+
| Means | Configuration trigger | Live traffic sampling |
+-----------+-----------------------+----------------------------+
| pros | Easy | real time |
+-----------+-----------------------+----------------------------+
| cons | miss of exceptions |extra FP capability required|
+-----------+-----------------------+----------------------------+
Figure 2 Comparison of Means of Service Discovery
5. Inband Flow Information Telemetry Deployment
5.1. Telemetry Type
Inband flow information telemetry can be categorized into two modes:
End-to-End (E2E) and Hop-by-Hop (HbH). For majority of services, E2E
telemetry of service flows can meet the requirements from operators.
In E2E mode shown in Figure 3, ingress node discovers the traffic
characteristics and proceed on-path telemetry on device to report
data to data consumer. Ingress node may also encapsulate flow
identifier to facilitate the identification of flow information
telemetry on egress node. Egress node identifies the flow and
alternate marking identifier, proceed the record on packet number and
timestamp, and further telemetry the statistics to data consumer.
Transit node does not require any detection of flow information or
processing of telemetry.
+-------------+
|Data Consumer| compute E2E flow info
+-------------+
| |
___flow info__| |____flow info____
| telemetry telemetry |
| |
+---------+ +---------+ +---------+ +---------+
| Ingress |---| Transit | ...| Transit |---| Egress |
| Node | | Node | | Node | | Node |
+---------+ +---------+ +---------+ +---------+
Figure 3 End-to-End Telemetry Type Mode
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The distinction of HbH mode to E2E mode is that transit node also
participates the inband flow information learning and telemetry. In
HbH mode shown in Figure 4, telemetry covers the flow information on
every node of the forwarding path the flow packet is transmitted,
which provides detailed flow information on each hop.
+-------------+
|Data Consumer| compute HbH flow info
+-------------+
| | | | flow info telemetry
______________| | | |_________________
| ___| |___ |
| | | |
+---------+ +---------+ +---------+ +---------+
| Ingress |---| Transit | ...| Transit |---| Egress |
| Node | | Node | | Node | | Node |
+---------+ +---------+ +---------+ +---------+
Figure 4 Hop-by-Hop Telemetry Type Mode
5.2. Telemetry Policy
Telemetry policy is used to determine which flow should be monitored.
By configuring telemetry policy, it can increase the priority of
learning and telemetry to critical flow and reduce or filter the
learning and telemetry of unimportant flows. It is crucial to
network deployment for two reasons, one is the number of flows can be
huge, another is limited by telemetry processing capability either on
the controller or the network node. There might be millions of flows
in a large scale network, for example 5G mobile backhaul network. It
is important to wisely choose the granularity of inband flow
information telemetry. Regarding IP traffics, the telemetry policy
can be based on either one of or combination of IP source/destination
address, TCP/UDP port number, VRFs, or network device interfaces etc.
To use an IP address with a flexible wildcard mask can be used as the
telemetry to an aggregation of multiple flows. A flow identifier
such as Flow-ID Label Indicator
[I-D.ietf-mpls-inband-pm-encapsulation] or FlowMonID
[I-D.ietf-6man-ipv6-alt-mark] is also used to identify a flow at
transit or egress nodes.
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5.3. Telemetry Deployment
In IFL, inband flow information telemetry is based on a class of flow
characteristic and managed as an Inband Flow Information Telemetry
Instance (IFITI). IFITI can be deployed on either controller or
network node. When IFITI is created on controller and deployed from
controller to network node. The network nodes including the ingress
and egress node in E2E mode, as well as transit node in HbH mode are
deployed with separate IFITI. It usually works in the need of an on-
demand fault diagnose. When IFITI is created on network node,
normally ingress node creates IFITI based on the received flow
packets filtered and sampled by the pre-defined telemetry policy.
Ingress node can also encode inband monitoring information in the
flow packets. Transit or egress node detect the inband monitoring
information of packets and automatically create IFITI to deploy the
inband flow information telemetry. To create the IFITI on network
node can greatly facilitate the dynamic and incremental deployment if
needed.
The network node discovers the flow characteristic from the obtained
service live traffic and sends it to the network controller.
According to these flow characteristics, the network controller
generates a Telemetry instance for monitoring the service flow. The
network node obtains the instance and the corresponding identifier,
such as Flow-ID, carries the identifier in the service flow to setup
a relationship between the characteristic information, instance and
the service flow, and performs Telemetry. The network controller
also sends policies for the service discovery. The characteristic
information extracting can base on the policy, preset cycle etc.
If the service message related to certain characteristic information
is not received within the preset time, it is determined that the
characteristic information is in an invalid state. And send the
failure status information to the controller.
6. Inband Flow Information Telemetry Adjustment
When route convergence happens to the network, service flow may
switch to other forwarding nodes. To monitor the same flow
information, new telemetry instance is required to add on the new
transit or egress node. Regarding the IFITI running on the fault
path, the aging of IFITI should be supported in order to recycle the
network resources. IFITI should be deleted once it becomes stale.
Similar to the deployment of IFITI, aging and adjustment of IFITI can
be controlled by the central controller or network node. When a
specific timer used for flow information telemetry timeout, the IFITI
would be deleted to stop the telemetry of the flow.
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7. IANA Considerations
This document has no request to IANA
8. Security Considerations
TBD
9. References
9.1. Normative References
[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>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
9.2. Informative References
[I-D.hwyh-ippm-ps-inband-flow-learning]
Han, L., Wang, M., Yang, F., and J. Huang, "Problem
Statement and Requirement for Inband Flow Learning", Work
in Progress, Internet-Draft, draft-hwyh-ippm-ps-inband-
flow-learning-01, 25 October 2021,
<https://www.ietf.org/archive/id/draft-hwyh-ippm-ps-
inband-flow-learning-01.txt>.
[I-D.ietf-6man-ipv6-alt-mark]
Fioccola, G., Zhou, T., Cociglio, M., Qin, F., and R.
Pang, "IPv6 Application of the Alternate Marking Method",
Work in Progress, Internet-Draft, draft-ietf-6man-ipv6-
alt-mark-12, 22 October 2021,
<https://www.ietf.org/archive/id/draft-ietf-6man-ipv6-alt-
mark-12.txt>.
[I-D.ietf-mpls-inband-pm-encapsulation]
Cheng, W., Min, X., Zhou, T., Dong, X., and Y. Peleg,
"Encapsulation For MPLS Performance Measurement with
Alternate Marking Method", Work in Progress, Internet-
Draft, draft-ietf-mpls-inband-pm-encapsulation-02, 25
October 2021, <https://www.ietf.org/archive/id/draft-ietf-
mpls-inband-pm-encapsulation-02.txt>.
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[I-D.ietf-opsawg-ntf]
Song, H., Qin, F., Martinez-Julia, P., Ciavaglia, L., and
A. Wang, "Network Telemetry Framework", Work in Progress,
Internet-Draft, draft-ietf-opsawg-ntf-13, 3 December 2021,
<https://www.ietf.org/archive/id/draft-ietf-opsawg-ntf-
13.txt>.
[I-D.song-opsawg-ifit-framework]
Song, H., Qin, F., Chen, H., Jin, J., and J. Shin, "A
Framework for In-situ Flow Information Telemetry", Work in
Progress, Internet-Draft, draft-song-opsawg-ifit-
framework-17, 22 February 2022,
<https://www.ietf.org/archive/id/draft-song-opsawg-ifit-
framework-17.txt>.
Authors' Addresses
Liuyan Han
China Mobile
Beijing
China
Email: hanliuyan@chinamobile.com
Minxue Wang
China Mobile
Beijing
China
Email: wangminxue@chinamobile.com
Fan Yang
Huawei Technologies
Beijing
China
Email: shirley.yangfan@huawei.com
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