Network Working Group                                           A. Clemm
Internet-Draft                                              J. Strassner
Intended status: Standards Track                               Futurewei
Expires: April 23, 2022                                      J. Francois
                                                        October 20, 2021

                     High-Precision Service Metrics


   This document defines a set of metrics for high-precision networking
   services.  These metrics can be used to assess the service levels
   that are being delivered for a networking flow.  Specifically, they
   can be used to determine the degree of compliance with which service
   levels are being delivered relative to service level objectives that
   were defined for the flow.  The metrics can be used as part of flow
   records and/or accounting records.  They can also be used to
   continuously monitor the quality with which high-precision networking
   service are being delivered.

Status of This Memo

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   publication of this document.  Please review these documents
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Key Words . . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Definitions and Acronyms  . . . . . . . . . . . . . . . . . .   3
   4.  Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . .   3
   5.  Discussion Items  . . . . . . . . . . . . . . . . . . . . . .   7
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   7
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .   7
   8.  Normative References  . . . . . . . . . . . . . . . . . . . .   8
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   Many networking applications increasingly rely on high-precision
   networking services that have clearly defined service level
   objectives (SLOs), for example with regards to end-to-end latency.
   Applications requiring such services include industrial networks, for
   example cloud-based industrial controllers for precision machinery,
   vehicular applications, for example tele-driving in which a vehicle
   is remotely controlled by a human operators, or Augmented Reality /
   Virtual Reality (AR/VR) applications involving rendering of point
   clouds remotely.  Many of those applications are not tolerant of
   degrading service levels.  A slight miss in SLOs does not merely
   result in a slight deterioration of the Quality of Experience to end
   users, but may render the application inoperable.  At the same time,
   many of those applications are mission critical, in which sudden
   failures can jeopardize safety or have other adverse consequences.
   However, clearly those applications represent significant business
   opportunity demanding dependable technical solutions.

   Because of this, efforts such as Deterministic Networking (DetNet)
   [RFC8655] are attempting to create solutions in which clear bounds on
   parameters such as end-to-end latency and jitter can be defined in
   order to make service levels being delivered predictable and,
   ideally, deterministic.  However, one area that has not kept pace
   concerns metrics that can account for service levels with which
   services are delivered, specifically the degree of precision for
   agreed-upon service level objectives.  Such metrics, and the
   instrumentation to support them, are important for a number of
   purposes, including monitoring (to ensure that networking services

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   are performing according to their objectives) as well as accounting
   (to maintain a record of service levels actually delivered, important
   for monetization of such services as well as for triaging of

   The current state-of-the-art of such metrics includes (for example)
   interface metrics, useful to obtain data on traffic volume and
   behavior that can be observed at an interface [RFC2863] [RFC8343] but
   agnostic of actual end-to-end service levels and not specific to
   distinct flows.  Flow records [RFC7011] [RFC7012] maintain statistics
   about flows, including flow volume and flow duration, but again
   contain very little information about end-to-end service levels, let
   alone whether the service levels delivered meet their targets, i.e.
   their associated SLOs.

   This specification introduces a new set of metrics aimed at capturing
   end-to-end service levels for a flow, specifically the degree to
   which flows comply with the SLOs that are in effect.

   It should be noted that at this point, the set of metrics proposed
   here is intended as a "starter set" that is intended to spark further
   discussion.  Other metrics are certainly conceivable; we expect that
   the list of metrics will evolve over time as part of Working Group

2.  Key Words

   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.

3.  Definitions and Acronyms

      MTBF: Mean Time Between Failures

      SL: Service Level

      SLA: Service Level Agreement

      SLO: Service Level Objective

4.  Metrics

   The following section proposes a set of accounting metrics focus on
   end-to-end latency objectives.  They indicate whether any violations
   of end-to-end latency occurred at the packet level.  These metrics

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   are intended to be applied on a per-flow basis and are intended to
   assess the degree to which a flow's end-to-end service levels comply
   with the SLO in effect for that flow.

   While the focus in this document concerns end-to-end latency
   objectives, analogous metrics could also be defined for other end-to-
   end service level parameters, such as loss (which is distinct from
   loss occurring at any one given interface) or delay variation.

   o  Violated Packets.  This indicates the number of packets for which
      a violation of a latency SLO occurred.

   o  Violated Time Units (e.g. violated seconds, violated
      milliseconds).  This indicates the number of time units during
      which one or more violations of SLOs were observed, regardless of
      how many violations took place during the same interval.  This
      measure is useful in scenarios where bursts of violations might
      suddenly occur (e.g. due to temporary network congestion, during
      route convergence etc.) and the count of violated packets by
      itself might paint a misleading picture.

   The following additional set of metrics may be useful in certain
   scenarios as well.  However, their precise definition may be subject
   to policy and further discussion is needed:

   o  Significantly Violated Packets.  This indicates the number of
      packets for which a "significant" violation occurred, where
      "significant" implies an SLO that was not merely a near-miss but
      that missed the objective by a degree determined especially

   o  Significantly Violated Time Units (e.g. significantly violated
      seconds, significantly violated milliseconds).  This indicates the
      number of time units during which any significant violation

   o  Severely Violated Time Units (e.g. severely violated seconds,
      severely violated milliseconds).  "Severe" here refers to the
      occurrence of multiple violations within the same time unit.  The
      definition of "severe" may be subject to policy; it may also take
      into account the significance of the violations that occur.

   Note that there is no definition of Severely Violated Packets.  The
   term "severe" is used in conjunction with the occurrence of multiple
   violations related to multiple packets, not any one packet in

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   From these first-order metrics, second-order metrics can be defined
   that build on the first set of metrics.  Some of these metrics are
   modeled after Mean Time Between Failure, or MTBF metrics - a
   "failure" in this context referring to a failure to deliver a packet
   according to its SLO.

   o  Time since last violated time unit (i.e., since last violated ms,
      since last violated second).  (This parameter is particularly
      useful for the monitoring of the current health.)

   o  Packets since last violated packet.  (This parameter is
      particularly useful for the monitoring of the current health.)

   o  Mean time between violated time units (i.e. between violated
      milliseconds, between violated seconds).  This refers to the
      arithmetic mean of time between violations such as violated time

   o  Mean packets between violations.  This refers to the arithmetic
      mean of the number of SLO-compliant packets between SLO
      violations.  (Another variation of "MTBF" in a service setting.)

   The same set of metrics can also be applied to significant
   violations, and to severe violations:

   o  Time since last significantly violated time unit (i.e., since last
      significantly violated ms, since last significantly violated

   o  Time since last severely violated time unit (i.e., since last
      severely violated ms, since last severely violated second).

   o  Packets since last significatly violated packet.

   o  Mean time between significantly violated time units (i.e. between
      significantly violated milliseconds, between significantly
      violated seconds).

   o  Mean time between severely violated time units (i.e. between
      severely violated milliseconds, between severely violated

   o  Mean packets between significant violations.  This refers to the
      arithmetic mean of the number of SLO-compliant packets between
      significant SLO violations.

   The next set of metrics puts the violations in relationship to non-
   violations.  It is intended to provide an analogous measure to that

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   of availability, typically defined as the number of time units during
   which a system (or service) is unavailable divided by the total
   number of time units.  In analogy, a time unit that is "violated" can
   be viewed as one in which a service is not available with the
   advertised precision:

   o  Precision availability (of milliseconds, of seconds): the ratio
      between violated time units (seconds, milliseconds) and the total
      time units for the duration of the service.

   o  Analogous metrics for precision availability re: severely violated
      time units, re: significantly violated time units.

   It should be noted that certain Service Level Agreements may be
   statistical in nature, requiring the service levels of packets in a
   flow to adhere to certain distributions.  For example, an SLA might
   state that any given SLO applies only to a certain percentage of
   packets, allowing for a certain amount of violations to take place.
   A "violated packet" in that case does not necessarily constitute an
   SLO violation.  However, it is still useful to maintain those
   statistics, as the number of violated packets still matters when
   looked at in proportion to the total number of packets.

   Along that vein, an SLA might establish an SLO of, say, end-to-end
   latency to not exceed 20ms for 99% of packets, to not exceed 25ms for
   99.999% of packets, and to never exceed 30ms for anything beyond.  In
   that case, any individual packet missing the 20 ms latency target
   cannot be considered an SLO violation in itself, but compliance with
   the SLO may need to be assessed after the fact.

   To support statistical SLAs more directly, it is feasible to support
   additional metrics, such as metrics that represent histograms for
   service level parameters with buckets corresponding to individual
   service level objectives.  For the example just given, a histogram
   for a given flow could be maintained with three buckets: one
   containing the count of packets within 20ms, a second with a count of
   packets between 20 and 25ms (or simply all within 25ms), a third with
   a count of packet between 25 and 30ms (or simply all packets within
   30ms, and a fourth with a count of anything beyond (or simply a total
   count).  Of course, the number of buckets and the boundaries between
   those buckets should correspond to the needs of the application
   respectively SLA, i.e. to the specific guarantees and SLOs that were
   provided.  The definition of histogram metrics is for further study.

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5.  Discussion Items

   The following is a list of items for which further discussion is
   needed as to whether they should be included in the scope of this

   o  A YANG data model

   o  A set of IPFIX Information Elements

   o  Statistical metrics: e.g. histograms/buckets

   o  Policies regarding the definition of "significant" and "severe"

   o  Additional second-order metrics, such as "longest disruption of
      service time" (measuring consecutive time units with violations)

6.  IANA Considerations


7.  Security Considerations

   Instrumentation for metrics that are used to assess compliance with
   SLOs consitute an interesting target for an attacker.  By interfering
   with the maintaining of such metrics, services could be falsely
   identified as being in compliance (when they are not), or vice-versa
   flagged as being non-compliant (when indeed they are).  While this
   document does not specify how networks should be instrumented to
   maintain the identified metrics, such instrumentation needs to be
   properly secured to ensure accurate measurements and prohibit
   tampering with metrics being kept.

   Where metrics are being defined relative to an SLO, the configuration
   of those SLOs needs to be properly secured.  Likewise, where SLOs can
   be adjusted, it needs to be clear which particular SLO any given
   metrics instance refers to.  The same service levels that constitute
   SLO violations for one flow, and that should be maintained as part of
   the "violated time units", "violated packets", and related metrics,
   may be perfectly compliant for another flow.  Where it is not
   possible to properly tie together SLOs and violation metrics, it will
   be preferrable to merely maintain statistics about sevice levels that
   were delivered (for example, overall histograms of end-to-end
   latency), without assessing which of these constitute violations.

   By the same token, where the definition of what constitutes a
   "severe" violation or a "significant" violation depends on policy or

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   context, the configuration of such policy or context needs to be
   specially secured and the configuration of this policy be bound to
   the metrics being maintained.  This way it will be clear which policy
   was in effect when those metrics were being assessed.  An attacker
   that is able to tamper with such policies will render the
   corresponding metrics useless (in the best case) or misleading (in
   the worst case).

8.  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,

   [RFC2863]  McCloghrie, K. and F. Kastenholz, "The Interfaces Group
              MIB", RFC 2863, DOI 10.17487/RFC2863, June 2000,

   [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,

   [RFC7012]  Claise, B., Ed. and B. Trammell, Ed., "Information Model
              for IP Flow Information Export (IPFIX)", RFC 7012,
              DOI 10.17487/RFC7012, September 2013,

   [RFC7950]  Bjorklund, M., Ed., "The YANG 1.1 Data Modeling Language",
              RFC 7950, DOI 10.17487/RFC7950, August 2016,

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

   [RFC8343]  Bjorklund, M., "A YANG Data Model for Interface
              Management", RFC 8343, DOI 10.17487/RFC8343, March 2018,

   [RFC8655]  Finn, N., Thubert, P., Varga, B., and J. Farkas,
              "Deterministic Networking Architecture", RFC 8655,
              DOI 10.17487/RFC8655, October 2019,

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Authors' Addresses

   Alexander Clemm
   2330 Central Expressway
   Santa Clara  CA 95050


   John Strassner
   2330 Central Expressway
   Santa Clara  CA 95050


   Jerome Francois
   615 Rue du Jardin Botanique
   Villers-les-Nancy  54600


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