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OPSAWG                                                      H. Song, Ed.
Internet-Draft                                                 Futurewei
Intended status: Informational                                     Z. Li
Expires: March 9, 2020                                           T. Zhou
                                                                  Huawei
                                                                  F. Qin
                                                            China Mobile
                                                                 J. Shin
                                                              SK Telecom
                                                                  J. Jin
                                                                   LG U+
                                                       September 6, 2019


              In-situ Flow Information Telemetry Framework
                  draft-song-opsawg-ifit-framework-04

Abstract

   Unlike the existing active and passive OAM techniques, the emerging
   on-path flow telemetry techniques provide unmatched visibility into
   user traffic, showing great application potential not only for
   today's network OAM but also for future's automatic network
   operation.  Summarizing the current industry practices that addresses
   the deployment challenges and application requirements, we provide a
   closed-loop framework, named In-situ Flow Information Telemetry
   (iFIT), for efficiently applying a family of underlying on-path flow
   telemetry techniques in various network environments.  The framework
   enumerates several key architectural components and describes how
   these components are assembled together to achieve a complete and
   closed-loop working solution for on-path flow telemetry.  Following
   such a framework allows better scalability, fosters application
   innovations, and promotes both vertical and horizontal
   interoperability.

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.




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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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Table of Contents

   1.  Requirements and Challenges . . . . . . . . . . . . . . . . .   3
   2.  iFIT Framework Overview . . . . . . . . . . . . . . . . . . .   4
   3.  Smart Flow and Data Selection . . . . . . . . . . . . . . . .   6
   4.  Export Data Reduction . . . . . . . . . . . . . . . . . . . .   6
   5.  Dynamic Network Probe . . . . . . . . . . . . . . . . . . . .   7
   6.  Encapsulation and Tunnel Modes  . . . . . . . . . . . . . . .   7
   7.  On-demand Technique Selection and Integration . . . . . . . .   8
   8.  Summary and Future Work . . . . . . . . . . . . . . . . . . .   8
   9.  Security Considerations . . . . . . . . . . . . . . . . . . .   8
   10. IANA Considerations . . . . . . . . . . . . . . . . . . . . .   8
   11. Contributors  . . . . . . . . . . . . . . . . . . . . . . . .   9
   12. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .   9
   13. References  . . . . . . . . . . . . . . . . . . . . . . . . .   9
     13.1.  Normative References . . . . . . . . . . . . . . . . . .   9
     13.2.  Informative References . . . . . . . . . . . . . . . . .   9
     13.3.  URIs . . . . . . . . . . . . . . . . . . . . . . . . . .  11
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  11





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1.  Requirements and Challenges

   Application-aware network operation is important for user SLA
   compliance, service path enforcement, fault diagnosis, and network
   resource optimization.  A family of on-path flow telemetry
   techniques, including In-situ OAM (IOAM)
   [I-D.brockners-inband-oam-data], PBT
   [I-D.song-ippm-postcard-based-telemetry], IFA [I-D.kumar-ippm-ifa],
   Enhanced AM [I-D.zhou-ippm-enhanced-alternate-marking], and HTS
   [I-D.mirsky-ippm-hybrid-two-step], are emerging, which can provide
   flow information on the entire forwarding path on a per-packet basis
   in real time.  These techniques are very different from the previous
   active and passive OAM schemes in that they directly modify the user
   packets and can gain visibility on every user packet.  Given the
   unique characteristics of such techniques, we categorize these on-
   path telemetry techniques as the hybrid OAM type III, supplementing
   the classification defined in [RFC7799].

   These techniques are invaluable for application-aware network
   operations not only in data center and enterprise networks but also
   in carrier networks which may cross multiple domains.  Carrier
   network operators have shown strong interests in utilizing such
   techniques for various purposes.  For example, it is vital for the
   operators who offer the bandwidth intensive, latency and loss
   sensitive services such as video streaming and gaming to closely
   monitor the relevant flows in real time as the indispensable first
   step for any further measure.

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

   o  C1: On-path flow telemetry incurs 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: On-path flow telemetry 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 collectible data defined currently are 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.




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      Flexibility and extensibility on data defining and acquiring must
      be considered.

   o  C4: If we were to apply some on-path telemetry technique 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 tunnels.

   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 In-situ OAM trace option is used.  A
      comprehensive solution needs the flexibility to switch between
      different underlying techniques and adjust the configurations and
      parameters at runtime.

2.  iFIT Framework Overview

   To address these challenges, we propose a framework based on multiple
   network operators' requirements and the common industry practice,
   which can help to build a workable on-path flow 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.  As a solution
   framework, iFIT works a level higher than any specific OAM
   techniques, be it active, passive, or hybrid.  The framework is built
   up on a few architectural components.  By assembling these components
   together, a closed-loop is formed to provide a complete solution for
   a particular static, dynamic, and interactive telemetry applications.

   iFIT is an open framework.  It does not enforce any implementation
   details for each component.  Users are free to pick one or more
   underlying techniques and design their own algorithms and
   architectures to fit in each component and make all the components
   work in concert.

   The network architecture that applies iFIT is shown in Figure 1.  The
   iFIT domain is confined between the iFIT head nodes and the iFIT end
   nodes.  An iFIT domain may cross multiple network domains.  iFIT
   support two basic on-path telemetry data collection modes: passport
   mode (e.g., IOAM trace option and IFA), in which telemetry data are
   carried in user packets and exported at the iFIT end nodes, and
   postcard mode (e.g., PBT), in which each node in the iFIT domain may
   export telemetry data through independent OAM packets.  Note that the




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   boundary between the two modes can be blurry.  An application only
   need to mix the two modes.

   The key components of iFIT is listed as follows:

   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




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

3.  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).
   [I-D.song-ippm-ioam-data-validation-option] 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.

4.  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
   data.

   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



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   data collecting and processing servers.  Rather, iFIT takes advantage
   of the in-network computing capability of network devices to process
   the raw data and only push the event notifications to the subscribing
   applications.

5.  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) [I-D.song-opsawg-dnp4iq].  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.

6.  Encapsulation and Tunnel Modes

   Since MPLS and IPv4 network are still prevalent in carrier networks.
   iFIT provides solutions to apply the on-path flow telemetry
   techniques in such networks.  PBT-M
   [I-D.song-ippm-postcard-based-telemetry] does not introduce new
   headers to the packets so the trouble of encapsulation for a new
   header is avoided.  In case a technique that requires a new header is
   preferred, [I-D.song-mpls-extension-header] provides a means to
   encapsulate the extra header using an MPLS extension header.  As for
   IPv4, it is possible to encapsulate the new header in an IP option.
   For example, RAO [RFC2113] can be used to indicate the presence of
   the new header.  A recent proposal [I-D.herbert-ipv4-eh] that
   introduces the IPv4 extension header may lead to a long term
   solution.

   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 [I-D.song-ippm-ioam-tunnel-mode].  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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7.  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.

8.  Summary and Future Work

   iFIT is a framework for applying on-path data plane telemetry
   techniques.  Combining with algorithmic and architectural schemes
   that fit into the framework components, iFIT framework enables a
   practical telemetry solution based on two basic on-path traffic data
   collection modes: passport and postcard.

   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 hybrid type III
   mode, which can provide more flexible and accurate network OAM.

   More challenges and corresponding solutions for iFIT may need to be
   covered.  For example, how iFIT can fit in the big picture of
   autonomous networking and support closed control loops.  A complete
   iFIT framework should also consider the cross-domain operations.  We
   leave these topics for future revisions.

9.  Security Considerations

   No specific security issues are identified other than those have been
   discussed in the drafts on on-path flow information telemetry.

10.  IANA Considerations

   This document includes no request to IANA.







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11.  Contributors

   TBD.

12.  Acknowledgments

   TBD.

13.  References

13.1.  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>.

   [RFC7799]  Morton, A., "Active and Passive Metrics and Methods (with
              Hybrid Types In-Between)", RFC 7799, DOI 10.17487/RFC7799,
              May 2016, <https://www.rfc-editor.org/info/rfc7799>.

   [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>.

13.2.  Informative References

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

   [I-D.herbert-ipv4-eh]
              Herbert, T., "IPv4 Extension Headers and Flow Label",
              draft-herbert-ipv4-eh-01 (work in progress), May 2019.

   [I-D.kumar-ippm-ifa]
              Kumar, J., Anubolu, S., Lemon, J., Manur, R., Holbrook,
              H., Ghanwani, A., Cai, D., Ou, H., and L. Yizhou, "Inband
              Flow Analyzer", draft-kumar-ippm-ifa-01 (work in
              progress), February 2019.

   [I-D.mirsky-ippm-hybrid-two-step]
              Mirsky, G., Lingqiang, W., and G. Zhui, "Hybrid Two-Step
              Performance Measurement Method", draft-mirsky-ippm-hybrid-
              two-step-03 (work in progress), April 2019.



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

   [I-D.song-ippm-ioam-tunnel-mode]
              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.

   [I-D.song-ippm-postcard-based-telemetry]
              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
              2019.

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

   [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-ippm-enhanced-alternate-marking]
              Zhou, T., Fioccola, G., Li, Z., Lee, S., Cociglio, M., and
              Z. Li, "Enhanced Alternate Marking Method", draft-zhou-
              ippm-enhanced-alternate-marking-03 (work in progress),
              July 2019.

   [RFC2113]  Katz, D., "IP Router Alert Option", RFC 2113,
              DOI 10.17487/RFC2113, February 1997,
              <https://www.rfc-editor.org/info/rfc2113>.

   [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>.

   [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, <https://www.rfc-editor.org/info/rfc8321>.




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13.3.  URIs

   [1] https://developers.google.com/protocol-buffers/

Authors' Addresses

   Haoyu Song (editor)
   Futurewei
   2330 Central Expressway
   Santa Clara
   USA

   Email: haoyu.song@futurewei.com


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

   Email: lizhenbin@huawei.com


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

   Email: zhoutianran@huawei.com


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

   Email: qinfengwei@chinamobile.com


   Jongyoon Shin
   SK Telecom
   South Korea

   Email: jongyoon.shin@sk.com




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   Jaewhan Jin
   LG U+
   South Korea

   Email: daenamu1@lguplus.co.kr














































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