In-situ Flow Information Telemetry Framework

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Document Type Active Internet-Draft (individual)
Authors Haoyu Song  , Zhenbin Li  , Tianran Zhou  , Fengwei Qin  , Jongyoon Shin  , Jaewhan Jin 
Last updated 2019-07-08 (latest revision 2019-06-12)
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OPSAWG                                                      H. Song, Ed.
Internet-Draft                                                 Futurewei
Intended status: Informational                                     Z. Li
Expires: January 9, 2020                                         T. Zhou
                                                                  F. Qin
                                                            China Mobile
                                                                 J. Shin
                                                              SK Telecom
                                                                  J. Jin
                                                                   LG U+
                                                            July 8, 2019

              In-situ Flow Information Telemetry Framework


   In-situ Flow Information Telemetry (iFIT) is a framework for applying
   on-path data plane telemetry techniques such as In-situ OAM (iOAM)
   and Postcard-Based Telemetry (PBT).  It enumerates several key
   components and describes how these components are assembled to
   achieve a complete working solution for on-path user traffic
   telemetry in carrier networks.

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "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
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   This Internet-Draft will expire on January 9, 2020.

Copyright Notice

   Copyright (c) 2019 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Smart Flow and Data Selection . . . . . . . . . . . . . . . .   5
   3.  Export Data Reduction . . . . . . . . . . . . . . . . . . . .   5
   4.  Dynamic Network Probe . . . . . . . . . . . . . . . . . . . .   6
   5.  Encapsulation and Tunnel Modes  . . . . . . . . . . . . . . .   6
   6.  On-demand Technique Selection and Integration . . . . . . . .   7
   7.  Summary and Future Work . . . . . . . . . . . . . . . . . . .   7
   8.  Security Considerations . . . . . . . . . . . . . . . . . . .   7
   9.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   8
   10. Contributors  . . . . . . . . . . . . . . . . . . . . . . . .   8
   11. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .   8
   12. References  . . . . . . . . . . . . . . . . . . . . . . . . .   8
     12.1.  Normative References . . . . . . . . . . . . . . . . . .   8
     12.2.  Informative References . . . . . . . . . . . . . . . . .   8
     12.3.  URIs . . . . . . . . . . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   Application-aware network operation is important for user SLA
   compliance, service path enforcement, fault diagnosis, and network
   resource optimization.  In-situ OAM (IOAM)
   [I-D.brockners-inband-oam-data] and PBT
   [] provide the direct on-path
   experience of user traffic.  These techniques are invaluable for
   application-aware network operations in not only data center and
   enterprise networks but also carrier networks.

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   However, successfully applying such techniques in carrier networks
   poses several practical challenges:

   o  C1: IOAM and PBT incur extra packet processing which may strain
      the network data plane.  The potential impact on the forwarding
      performance creates an unfavorable "observer effect" which not
      only damages the fidelity of the measurement but also defies the
      purpose of the measurement.

   o  C2: IOAM and PBT can generate a huge amount of OAM data which may
      claim too much transport bandwidth and inundate the servers for
      data collection, storage, and analysis.  Increasing the data
      handling capacity is technically viable but expensive.

   o  C3: The currently defined set of data is essential but limited.
      As the network operation evolves to become intent-based and
      automatic, and the trends of network virtualization, network
      convergence, and packet-optical integration continue, more data
      will be needed in an on-demand and interactive fashion.
      Flexibility and extensibility on data acquiring must be

   o  C4: If we were to apply IOAM and PBT in today's carrier networks,
      we must provide solutions to tailor the provider's network
      deployment base and support an incremental deployment strategy.
      That is, we need to come up with encapsulation schemes for various
      predominant protocols such as Ethernet, IPv4, and MPLS with
      backward compatibility and properly handle various transport

   o  C5: Applying only a single underlying telemetry technique may lead
      to defective result.  For example, packet drop can cause the lost
      of the flow telemetry data and the packet drop location and reason
      remains unknown if only IOAM is used.  A comprehensive solution
      needs the flexibility to switch between different underlying
      techniques and adjust the configurations and parameters at

   To address these challenges, we propose a framework based on our
   prototype experience which can help to build a workable data-plane
   telemetry solution.  We name the framework "In-situ Flow Information
   Telemetry" (iFIT) to reflect the fact that this framework is
   dedicated to the on-path telemetry data about user/application flow
   experience.  In future, other related data plane OAM techniques such
   as IPFPM [RFC8321] can also be integrated into iFIT to provide richer
   capabilities.  The network architecture that applies iFIT is shown in
   Figure 1.  The key components of iFIT is listed as follows:

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   o  Smart flow and data selection policy to address C1.

   o  Export data reduction to address C2.

   o  Dynamic network probe to address C3.

   o  Encapsulation and tunnel modes to address C4.

   o  On-demand technique selection to address C5.

                          |                                 |
                          |        iFIT Applications        |
                          |                                 |
                                 ^                    ^
                                 |                    |
                                 V                    |
                          +------------+        +-----+-----+
                          |            |        |           |
                          | Controller |        | Collector |
                          |            |        |           |
                          +-----:------+        +-----------+
                                :                     ^
                                :configuration        |telemetry data
                                :                     |
                 :             :                 :    |         :
                 :   +---------:---+-------------:---++---------:---+
                 :   |         :   |             :   |          :   |
                 V   |         V   |             V   |          V   |
              +------+-+     +-----+--+       +------+-+     +------+-+
    usr pkts  | iFIT   |     | Path   |       | Path   |     | iFIT   |
         ====>| Head   |====>| Node   |==//==>| Node   |====>| End    |====>
              | Node   |     | A      |       | B      |     | Node   |
              +--------+     +--------+       +--------+     +--------+

                        Figure 1: iFIT Architecture

   In the remaining of the document, we provide the detailed discussion
   of the iFIT's components.

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2.  Smart Flow and Data Selection

   In most cases, it is impractical to enable the data collection for
   all the flows and for all the packets in a flow due to the potential
   performance and bandwidth impacts.  Therefore, a workable solution
   must select only a subset of flows and flow packets to enable the
   data collection, even though this means the loss of some information.

   In data plane, the Access Control List (ACL) provides an ideal means
   to determine the subset of flow(s).
   [] describes how one can set
   a sample rate or probability to a flow to allow only a subset of flow
   packets to be monitored, how one can collect different set of data
   for different packets, and how one can disable or enable data
   collection on any specific network node.  The document further
   introduces enhancement to IOAM to allow any node to accept or deny
   the data collection in full or partially.

   Based on these flexible mechanisms, iFIT allows applications to apply
   smart flow and data selection policies to suit the requirements.  The
   applications can dynamically change the policies at any time based on
   the network load, processing capability, focus of interest, and any
   other criteria.  We have developed some adaptive algorithm which can
   limit the performance impact and yet achieve the satisfactory
   telemetry data density.

3.  Export Data Reduction

   The flow telemetry data can catch the dynamics of the network and the
   interactions between user traffic and network.  Nevertheless, the
   data inevitably contain redundancy.  It is advisable to remove the
   redundancy from the data in order to reduce the data transport
   bandwidth and server processing load.

   In addition to efficiently encode the export data (e.g., IPFIX
   [RFC7011] or protobuf [1]), iFIT can also cache the data and send the
   accumulated data in batch if the data is not time sensitive.  Various
   deduplication and compression techniques can be applied on the batch

   From the application perspective, an application may only be
   interested in some special events which can be derived from the
   telemetry data.  For example, in case that the forwarding delay of a
   packet exceeds a threshold or a flow changes its forwarding path is
   of interest, it is unnecessary to send the original raw data to the
   data collecting and processing servers.  Rather, iFIT takes advantage
   of the in-network computing capability of network devices to process

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   the raw data and only push the event notifications to the subscribing

4.  Dynamic Network Probe

   Due to the limited data plane resource, it is unlikely one can
   provide all the data all the time.  On the other hand, the data
   needed by applications may be arbitrary but ephemeral.  It is
   critical to meet the dynamic data requirements with limited resource.

   Fortunately, data plane programmability allows iFit to dynamically
   load new data probes.  These on-demand probes are called Dynamic
   Network Probes (DNP) [].  DNP is the technique
   to enable probes for customized data collection in different network
   planes.  When working with IOAM or PBT, DNP is loaded to the data
   plane through incremental programming or configuration.  The DNP can
   effectively conduct data generation, processing, and aggregation.

   DNP introduces enough flexibility and extensibility to iFIT.  It can
   implement the optimizations for export data reduction motioned in the
   previous section.  It can also generate custom data as required by
   today and tomorrow's applications.

5.  Encapsulation and Tunnel Modes

   Since MPLS and IPv4 network are still prevalent in carrier networks.
   iFIT provides solutions to apply IOAM and PBT in such networks.
   PBT-M [] does not introduce new
   headers to the packets so the trouble of encapsulation for IOAM and
   PBT-I is avoided.  If IOAM or PBT-I is preferred,
   [] provides a means to encapsulate the
   extra header using an MPLS extension header.  As for IPv4, it is
   possible to encapsulate the IOAM or PBT-I header in an IP option.
   For example, RAO [RFC2113] can be used to indicate the presence of
   the new header.

   In carrier networks, it is common for user traffic to traverse
   various tunnels for QoS, traffic engineering, or security. iFIT
   supports both the uniform mode and the pipe mode for tunnel support
   as described in [].  With such
   flexibility, the operator can either gain a true end-to-end
   visibility or apply a hierarchical approach which isolates the
   monitoring domain between customer and provider.

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6.  On-demand Technique Selection and Integration

   With multiple underlying data collection and export techniques at its
   disposal, iFIT can flexibly adapt to different network conditions and
   different application requirements.

   For example, depending on the types of data that are of interest,
   iFIT may choose either IOAM or PBT to collect the data; if an
   application needs to track down where the packets are lost, it may
   switch from IOAM to PBT.

   iFIT can further integrate multiple data plane monitoring and
   measurement techniques together and present a comprehensive data
   plane telemetry solution to network operating applications.

7.  Summary and Future Work

   iFIT is a framework for applying on-path data plane telemetry
   techniques.  Combining with algorithmic and architectural components,
   iFIT framework enables a practical telemetry solution based on two
   basic on-path traffic data collection patterns: passport (e.g., IOAM
   trace and e2e modes) and postcard (e.g., PBT).

   The operation of iFIT differs from both active OAM and passive OAM as
   defined in [RFC7799].  It does not generate any active probe packets
   or passively observe unmodified user packets.  Instead, it modifies
   selected user packets to collect useful information about them.
   Therefore, the iFIT operation can be considered the third mode of
   OAM, hybrid OAM, which can provide more flexible and accurate network

   There are many more challenges and corresponding solutions for iFIT
   that we did not cover in the current version of this document.  For
   example, how the telemetry data are stored, analyzed, and visualized;
   how the telemetry data interfaces and work with the network operation
   applications which run machine learning and big data analytic
   algorithms; and ultimately, how iFIT can support closed control loops
   for autonomous networking?  A complete iFIT framework should also
   consider the cross-domain operations.  We leave these topics for
   future revisions.

8.  Security Considerations

   No specific security issues are identified other than those have been
   discussed in IOAM and PBT drafts.

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9.  IANA Considerations

   This document includes no request to IANA.

10.  Contributors


11.  Acknowledgments


12.  References

12.1.  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,

   [RFC7799]  Morton, A., "Active and Passive Metrics and Methods (with
              Hybrid Types In-Between)", RFC 7799, DOI 10.17487/RFC7799,
              May 2016, <>.

   [RFC8174]  Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
              2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
              May 2017, <>.

12.2.  Informative References

              Brockners, F., Bhandari, S., Pignataro, C., Gredler, H.,
              Leddy, J., Youell, S., Mizrahi, T., Mozes, D., Lapukhov,
              P., Chang, R., and d., "Data Fields
              for In-situ OAM", draft-brockners-inband-oam-data-07 (work
              in progress), July 2017.

              Song, H. and T. Zhou, "In-situ OAM Data Validation
              Option", draft-song-ippm-ioam-data-validation-option-02
              (work in progress), April 2018.

              Song, H., Li, Z., Zhou, T., and Z. Wang, "In-situ OAM
              Processing in Tunnels", draft-song-ippm-ioam-tunnel-
              mode-00 (work in progress), June 2018.

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              Song, H., Zhou, T., Li, Z., Shin, J., and K. Lee,
              "Postcard-based On-Path Flow Data Telemetry", draft-song-
              ippm-postcard-based-telemetry-04 (work in progress), June

              Song, H., Li, Z., Zhou, T., and L. Andersson, "MPLS
              Extension Header", draft-song-mpls-extension-header-02
              (work in progress), February 2019.

              Song, H. and J. Gong, "Requirements for Interactive Query
              with Dynamic Network Probes", draft-song-opsawg-dnp4iq-01
              (work in progress), June 2017.

   [RFC2113]  Katz, D., "IP Router Alert Option", RFC 2113,
              DOI 10.17487/RFC2113, February 1997,

   [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,

   [RFC8321]  Fioccola, G., Ed., Capello, A., Cociglio, M., Castaldelli,
              L., Chen, M., Zheng, L., Mirsky, G., and T. Mizrahi,
              "Alternate-Marking Method for Passive and Hybrid
              Performance Monitoring", RFC 8321, DOI 10.17487/RFC8321,
              January 2018, <>.

12.3.  URIs


Authors' Addresses

   Haoyu Song (editor)
   2330 Central Expressway
   Santa Clara


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


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


   Fengwei Qin
   China Mobile
   No. 32 Xuanwumenxi Ave., Xicheng District
   Beijing, 100032
   P.R. China


   Jongyoon Shin
   SK Telecom
   South Korea


   Jaewhan Jin
   LG U+
   South Korea


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