Internet DRAFT - draft-claise-opsawg-service-assurance-architecture

draft-claise-opsawg-service-assurance-architecture







OPSAWG                                                         B. Claise
Internet-Draft                                                    Huawei
Intended status: Informational                               J. Quilbeuf
Expires: October 25, 2021                                    Independent
                                                                D. Lopez
                                                          Telefonica I+D
                                                                D. Voyer
                                                             Bell Canada
                                                             T. Arumugam
                                                     Cisco Systems, Inc.
                                                          April 23, 2021


       Service Assurance for Intent-based Networking Architecture
         draft-claise-opsawg-service-assurance-architecture-05

Abstract

   This document describes an architecture for Service Assurance for
   Intent-based Networking (SAIN).  This architecture aims at assuring
   that service instances are correctly running.  As services rely on
   multiple sub-services by the underlying network devices, getting the
   assurance of a healthy service is only possible with a holistic view
   of network devices.  This architecture not only helps to correlate
   the service degradation with the network root cause but also the
   impacted services when a network component fails or degrades.

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
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.

   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 October 25, 2021.








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Copyright Notice

   Copyright (c) 2021 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
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   5
   3.  Architecture  . . . . . . . . . . . . . . . . . . . . . . . .   6
     3.1.  Decomposing a Service Instance Configuration into an
           Assurance Graph . . . . . . . . . . . . . . . . . . . . .   9
     3.2.  Intent and Assurance Graph  . . . . . . . . . . . . . . .  10
     3.3.  Subservices . . . . . . . . . . . . . . . . . . . . . . .  11
     3.4.  Building the Expression Graph from the Assurance Graph  .  11
     3.5.  Building the Expression from a Subservice . . . . . . . .  12
     3.6.  Open Interfaces with YANG Modules . . . . . . . . . . . .  12
     3.7.  Handling Maintenance Windows  . . . . . . . . . . . . . .  13
     3.8.  Flexible Architecture . . . . . . . . . . . . . . . . . .  14
     3.9.  Timing  . . . . . . . . . . . . . . . . . . . . . . . . .  15
     3.10. New Assurance Graph Generation  . . . . . . . . . . . . .  15
   4.  Security Considerations . . . . . . . . . . . . . . . . . . .  16
   5.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  16
   6.  Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  16
   7.  Open Issues . . . . . . . . . . . . . . . . . . . . . . . . .  16
   8.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  16
     8.1.  Normative References  . . . . . . . . . . . . . . . . . .  16
     8.2.  Informative References  . . . . . . . . . . . . . . . . .  17
   Appendix A.  Changes between revisions  . . . . . . . . . . . . .  18
   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .  18
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  19

1.  Terminology

   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




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   14 [RFC2119] [RFC8174] when, and only when, they appear in all
   capitals, as shown here.

   SAIN Agent: Component that communicates with a device, a set of
   devices, or another agent to build an expression graph from a
   received assurance graph and perform the corresponding computation.

   Assurance Graph: DAG representing the assurance case for one or
   several service instances.  The nodes (also known as vertices in the
   context of DAG) are the service instances themselves and the
   subservices, the edges indicate a dependency relations.

   SAIN collector: Component that fetches or receives the computer-
   consumable output of the agent(s) and displays it in a user friendly
   form or process it locally.

   DAG: Directed Acyclic Graph.

   ECMP: Equal Cost Multiple Paths

   Expression Graph: Generic term for a DAG representing a computation
   in SAIN.  More specific terms are:

   o  Subservice Expressions: expression graph representing all the
      computations to execute for a subservice.

   o  Service Expressions: expression graph representing all the
      computations to execute for a service instance, i.e. including the
      computations for all dependent subservices.

   o  Global Computation Graph: expression graph representing all the
      computations to execute for all services instances (i.e. all
      computations performed).

   Dependency: The directed relationship between subservice instances in
   the assurance graph.

   Informational Dependency: Type of dependency whose score does not
   impact the score of its parent subservice or service instance(s) in
   the assurance graph.  However, the symptoms should be taken into
   account in the parent service instance or subservice instance(s), for
   informational reasons.

   Impacting Dependency: Type of dependency whose score impacts the
   score of its parent subservice or service instance(s) in the
   assurance graph.  The symptoms are taken into account in the parent
   service instance or subservice instance(s), as the impacting reasons.




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   Metric: Information retrieved from a network device.

   Metric Engine: Maps metrics to a list of candidate metric
   implementations depending on the target model.

   Metric Implementation: Actual way of retrieving a metric from a
   device.

   Network Service YANG Module: describes the characteristics of
   service, as agreed upon with consumers of that service [RFC8199].

   Service Instance: A specific instance of a service.

   Service configuration orchestrator: Quoting RFC8199, "Network Service
   YANG Modules describe the characteristics of a service, as agreed
   upon with consumers of that service.  That is, a service module does
   not expose the detailed configuration parameters of all participating
   network elements and features but describes an abstract model that
   allows instances of the service to be decomposed into instance data
   according to the Network Element YANG Modules of the participating
   network elements.  The service-to-element decomposition is a separate
   process; the details depend on how the network operator chooses to
   realize the service.  For the purpose of this document, the term
   "orchestrator" is used to describe a system implementing such a
   process."

   SAIN Orchestrator: Component of SAIN in charge of fetching the
   configuration specific to each service instance and converting it
   into an assurance graph.

   Health status: Score and symptoms indicating whether a service
   instance or a subservice is healthy.  A non-maximal score MUST always
   be explained by one or more symptoms.

   Health score: Integer ranging from 0 to 100 indicating the health of
   a subservice.  A score of 0 means that the subservice is broken, a
   score of 100 means that the subservice is perfectly operational.

   Subservice: Part of an assurance graph that assures a specific
   feature or subpart of the network system.

   Symptom: Reason explaining why a service instance or a subservice is
   not completely healthy.








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2.  Introduction

   Network Service YANG Modules [RFC8199] describe the configuration,
   state data, operations, and notifications of abstract representations
   of services implemented on one or multiple network elements.

   Quoting RFC8199: "Network Service YANG Modules describe the
   characteristics of a service, as agreed upon with consumers of that
   service.  That is, a service module does not expose the detailed
   configuration parameters of all participating network elements and
   features but describes an abstract model that allows instances of the
   service to be decomposed into instance data according to the Network
   Element YANG Modules of the participating network elements.  The
   service-to-element decomposition is a separate process; the details
   depend on how the network operator chooses to realize the service.
   For the purpose of this document, the term "orchestrator" is used to
   describe a system implementing such a process."

   In other words, service configuration orchestrators deploy Network
   Service YANG Modules through the configuration of Network Element
   YANG Modules.  Network configuration is based on those YANG data
   models, with protocol/encoding such as NETCONF/XML [RFC6241] ,
   RESTCONF/JSON [RFC8040], gNMI/gRPC/protobuf, etc.  Knowing that a
   configuration is applied doesn't imply that the service is running
   correctly (for example the service might be degraded because of a
   failure in the network), the network operator must monitor the
   service operational data at the same time as the configuration.  The
   industry has been standardizing on telemetry to push network element
   performance information.

   A network administrator needs to monitor her network and services as
   a whole, independently of the use cases or the management protocols.
   With different protocols come different data models, and different
   ways to model the same type of information.  When network
   administrators deal with multiple protocols, the network management
   must perform the difficult and time-consuming job of mapping data
   models: the model used for configuration with the model used for
   monitoring.  This problem is compounded by a large, disparate set of
   data sources (MIB modules, YANG models [RFC7950], IPFIX information
   elements [RFC7011], syslog plain text [RFC3164], TACACS+ [RFC8907],
   RADIUS [RFC2865], etc.).  In order to avoid this data model mapping,
   the industry converged on model-driven telemetry to stream the
   service operational data, reusing the YANG models used for
   configuration.  Model-driven telemetry greatly facilitates the notion
   of closed-loop automation whereby events from the network drive
   remediation changes back into the network.





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   However, it proves difficult for network operators to correlate the
   service degradation with the network root cause.  For example, why
   does my L3VPN fail to connect?  Why is this specific service slow?
   The reverse, i.e. which services are impacted when a network
   component fails or degrades, is even more interesting for the
   operators.  For example, which service(s) is(are) impacted when this
   specific optic dBM begins to degrade?  Which application is impacted
   by this ECMP imbalance?  Is that issue actually impacting any other
   customers?

   Intent-based approaches are often declarative, starting from a
   statement of the "The service works correctly" and trying to enforce
   it.  Such approaches are mainly suited for greenfield deployments.

   Instead of approaching intent from a declarative way, this framework
   focuses on already defined services and tries to infer the meaning of
   "The service works correctly".  To do so, the framework works from an
   assurance graph, deduced from the service definition and from the
   network configuration.  This assurance graph is decomposed into
   components, which are then assured independently.  The root of the
   assurance graph represents the service to assure, and its children
   represent components identified as its direct dependencies; each
   component can have dependencies as well.  The SAIN architecture
   maintains the correct assurance graph when services are modified or
   when the network conditions change.

   When a service is degraded, the framework will highlight where in the
   assurance service graph to look, as opposed to going hop by hop to
   troubleshoot the issue.  Not only can this framework help to
   correlate service degradation with network root cause/symptoms, but
   it can deduce from the assurance graph the number and type of
   services impacted by a component degradation/failure.  This added
   value informs the operational team where to focus its attention for
   maximum return.

   This architecture provides the building blocks to assure both
   physical and virtual entities and is flexible with respect to
   services and subservices, of (distributed) graphs, and of components
   (Section 3.8).

3.  Architecture

   SAIN aims at assuring that service instances are correctly running.
   The goal of SAIN is to assure that service instances are operating
   correctly and if not, to pinpoint what is wrong.  More precisely,
   SAIN computes a score for each service instance and outputs symptoms
   explaining that score, especially why the score is not maximal.  The
   score augmented with the symptoms is called the health status.



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   The SAIN architecture is a generic architecture, applicable to
   multiple environments.  Obviously wireline but also wireless,
   including 5G, virtual infrastructure manager (VIM), and even virtual
   functions.  Thanks to the distributed graph design principle, graphs
   from different environments/orchestrator can be combined together.

   As an example of a service, let us consider a point-to-point L2VPN
   connection (i.e. pseudowire).  Such a service would take as
   parameters the two ends of the connection (device, interface or
   subinterface, and address of the other end) and configure both
   devices (and maybe more) so that a L2VPN connection is established
   between the two devices.  Examples of symptoms might be "Interface
   has high error rate" or "Interface flapping", or "Device almost out
   of memory".

   To compute the health status of such as service, the service is
   decomposed into an assurance graph formed by subservices linked
   through dependencies.  Each subservice is then turned into an
   expression graph that details how to fetch metrics from the devices
   and compute the health status of the subservice.  The subservice
   expressions are combined according to the dependencies between the
   subservices in order to obtain the expression graph which computes
   the health status of the service.

   The overall architecture of our solution is presented in Figure 1.
   Based on the service configuration, the SAIN orchestrator deduces the
   assurance graph.  It then sends to the SAIN agents the assurance
   graph along some other configuration options.  The SAIN agents are
   responsible for building the expression graph and computing the
   health statuses in a distributed manner.  The collector is in charge
   of collecting and displaying the current inferred health status of
   the service instances and subservices.  Finally, the automation loop
   is closed by having the SAIN Collector providing feedback to the
   network orchestrator.

















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          +-----------------+
          | Service         |
          | Configuration   |<--------------------+
          | Orchestrator    |                     |
          +-----------------+                     |
             |            |                       |
             |            | Network               |
             |            | Service               | Feedback
             |            | Instance              | Loop
             |            | Configuration         |
             |            |                       |
             |            V                       |
             |        +-----------------+       +-------------------+
             |        | SAIN            |       | SAIN              |
             |        | Orchestrator    |       | Collector         |
             |        +-----------------+       +-------------------+
             |            |                        ^
             |            | Configuration          | Health Status
             |            | (assurance graph)      | (Score + Symptoms)
             |            V                        | Streamed
             |     +-------------------+           | via Telemetry
             |     |+-------------------+          |
             |     ||+-------------------+         |
             |     +|| SAIN              |---------+
             |      +| agent             |
             |       +-------------------+
             |               ^ ^ ^
             |               | | |
             |               | | |  Metric Collection
             V               V V V
         +-------------------------------------------------------------+
         | Monitored Entities                                          |
         |                                                             |
         +-------------------------------------------------------------+


                        Figure 1: SAIN Architecture

   In order to produce the score assigned to a service instance, the
   architecture performs the following tasks:

   o  Analyze the configuration pushed to the network device(s) for
      configuring the service instance and decide: which information is
      needed from the device(s), such a piece of information being
      called a metric, which operations to apply to the metrics for
      computing the health status.





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   o  Stream (via telemetry [RFC8641]) operational and config metric
      values when possible, else continuously poll.

   o  Continuously compute the health status of the service instances,
      based on the metric values.

3.1.  Decomposing a Service Instance Configuration into an Assurance
      Graph

   In order to structure the assurance of a service instance, the
   service instance is decomposed into so-called subservice instances.
   Each subservice instance focuses on a specific feature or subpart of
   the network system.

   The decomposition into subservices is an important function of this
   architecture, for the following reasons.

   o  TThe result of this decomposition provides a relational picture of
      a service instance, that can be represented as a graph (called
      assurance graph) to the operator.

   o  Subservices provide a scope for particular expertise and thereby
      enable contribution from external experts.  For instance, the
      subservice dealing with the optics health should be reviewed and
      extended by an expert in optical interfaces.

   o  Subservices that are common to several service instances are
      reused for reducing the amount of computation needed.

   The assurance graph of a service instance is a DAG representing the
   structure of the assurance case for the service instance.  The nodes
   of this graph are service instances or subservice instances.  Each
   edge of this graph indicates a dependency between the two nodes at
   its extremities: the service or subservice at the source of the edge
   depends on the service or subservice at the destination of the edge.

   Figure 2 depicts a simplistic example of the assurance graph for a
   tunnel service.  The node at the top is the service instance, the
   nodes below are its dependencies.  In the example, the tunnel service
   instance depends on the peer1 and peer2 tunnel interfaces, which in
   turn depend on the respective physical interfaces, which finally
   depend on the respective peer1 and peer2 devices.  The tunnel service
   instance also depends on the IP connectivity that depends on the IS-
   IS routing protocol.







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                             +------------------+
                             | Tunnel           |
                             | Service Instance |
                             +-----------------+
                                       |
                   +-------------------+-------------------+
                   |                   |                   |
            +-------------+     +-------------+     +--------------+
            | Peer1       |     | Peer2       |     | IP           |
            | Tunnel      |     | Tunnel      |     | Connectivity |
            | Interface   |     | Interface   |     |              |
            +-------------+     +-------------+     +--------------}
                   |                   |                  |
            +-------------+     +-------------+     +-------------+
            | Peer1       |     | Peer2       |     | IS-IS       |
            | Physical    |     | Physical    |     | Routing     |
            | Interface   |     | Interface   |     | Protocol    |
            +-------------+     +-------------+     +-------------+
                   |                   |
            +-------------+     +-------------+
            |             |     |             |
            | Peer1       |     | Peer2       |
            | Device      |     | Device      |
            +-------------+     +-------------+

                     Figure 2: Assurance Graph Example

   Depicting the assurance graph helps the operator to understand (and
   assert) the decomposition.  The assurance graph shall be maintained
   during normal operation with addition, modification and removal of
   service instances.  A change in the network configuration or topology
   shall be reflected in the assurance graph.  As a first example, a
   change of routing protocol from IS-IS to OSPF would change the
   assurance graph accordingly.  As a second example, assuming that ECMP
   is in place for the source router for that specific tunnel; in that
   case, multiple interfaces must now be monitored, on top of the
   monitoring the ECMP health itself.

3.2.  Intent and Assurance Graph

   The SAIN orchestrator analyzes the configuration of a service
   instance to:

   o  Try to capture the intent of the service instance, i.e. what is
      the service instance trying to achieve,

   o  Decompose the service instance into subservices representing the
      network features on which the service instance relies.



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   The SAIN orchestrator must be able to analyze configuration from
   various devices and produce the assurance graph.

   To schematize what a SAIN orchestrator does, assume that the
   configuration for a service instance touches 2 devices and configure
   on each device a virtual tunnel interface.  Then:

   o  Capturing the intent would start by detecting that the service
      instance is actually a tunnel between the two devices, and stating
      that this tunnel must be functional.  This is the current state of
      SAIN, however it does not completely capture the intent which
      might additionally include, for instance, on the latency and
      bandwidth requirements of this tunnel.

   o  Decomposing the service instance into subservices would result in
      the assurance graph depicted in Figure 2, for instance.

   In order for SAIN to be applied, the configuration necessary for each
   service instance should be identifiable and thus should come from a
   "service-aware" source.  While the Figure 1 makes a distinction
   between the SAIN orchestrator and a different component providing the
   service instance configuration, in practice those two components are
   mostly likely combined.  The internals of the orchestrator are
   currently out of scope of this document.

3.3.  Subservices

   A subservice corresponds to subpart or a feature of the network
   system that is needed for a service instance to function properly.
   In the context of SAIN, subservice is actually a shortcut for
   subservice assurance, that is the method for assuring that a
   subservice behaves correctly.

   Subservices, just as with services, have high-level parameters that
   specify the type and specific instance to be assured.  For example,
   assuring a device requires the specific deviceId as parameter.  For
   example, assuring an interface requires the specific combination of
   deviceId and interfaceId.

   A subservice is also characterized by a list of metrics to fetch and
   a list of computations to apply to these metrics in order to infer a
   health status.

3.4.  Building the Expression Graph from the Assurance Graph

   From the assurance graph is derived a so-called global computation
   graph.  First, each subservice instance is transformed into a set of
   subservice expressions that take metrics and constants as input (i.e.



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   sources of the DAG) and produce the status of the subservice, based
   on some heuristics.  Then for each service instance, the service
   expressions are constructed by combining the subservice expressions
   of its dependencies.  The way service expressions are combined
   depends on the dependency types (impacting or informational).
   Finally, the global computation graph is built by combining the
   service expressions.  In other words, the global computation graph
   encodes all the operations needed to produce health statuses from the
   collected metrics.

   Subservices shall be device independent.  To justify this, let's
   consider the interface operational status.  Depending on the device
   capabilities, this status can be collected by an industry-accepted
   YANG module (IETF, Openconfig), by a vendor-specific YANG module, or
   even by a MIB module.  If the subservice was dependent on the
   mechanism to collect the operational status, then we would need
   multiple subservice definitions in order to support all different
   mechanisms.  This also implies that, while waiting for all the
   metrics to be available via standard YANG modules, SAIN agents might
   have to retrieve metric values via non-standard YANG models, via MIB
   modules, Command Line Interface (CLI), etc., effectively implementing
   a normalization layer between data models and information models.

   In order to keep subservices independent from metric collection
   method, or, expressed differently, to support multiple combinations
   of platforms, OSes, and even vendors, the framework introduces the
   concept of "metric engine".  The metric engine maps each device-
   independent metric used in the subservices to a list of device-
   specific metric implementations that precisely define how to fetch
   values for that metric.  The mapping is parameterized by the
   characteristics (model, OS version, etc.) of the device from which
   the metrics are fetched.

3.5.  Building the Expression from a Subservice

   Additionally, to the list of metrics, each subservice defines a list
   of expressions to apply on the metrics in order to compute the health
   status of the subservice.  The definition or the standardization of
   those expressions (also known as heuristic) is currently out of scope
   of this standardization.

3.6.  Open Interfaces with YANG Modules

   The interfaces between the architecture components are open thanks to
   the YANG modules specified in YANG Modules for Service Assurance
   [I-D.claise-opsawg-service-assurance-yang]; they specify objects for
   assuring network services based on their decomposition into so-called
   subservices, according to the SAIN architecture.



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   This module is intended for the following use cases:

   o  Assurance graph configuration:

      *  Subservices: configure a set of subservices to assure, by
         specifying their types and parameters.

      *  Dependencies: configure the dependencies between the
         subservices, along with their types.

   o  Assurance telemetry: export the health status of the subservices,
      along with the observed symptoms.

3.7.  Handling Maintenance Windows

   Whenever network components are under maintenance, the operator want
   to inhibit the emission of symptoms from those components.  A typical
   use case is device maintenance, during which the device is not
   supposed to be operational.  As such, symptoms related to the device
   health should be ignored, as well as symptoms related to the device-
   specific subservices, such as the interfaces, as their state changes
   is probably the consequence of the maintenance.

   To configure network components as "under maintenance" in the SAIN
   architecture, the ietf-service-assurance model proposed in
   [I-D.claise-opsawg-service-assurance-yang] specifies an "under-
   maintenance" flag per service or subservice instance.  When this flag
   is set and only when this flag is set, the companion field
   "maintenance-contact" must be set to a string that identifies the
   person or process who requested the maintenance.  Any symptom
   produced by a service or subservice under maintenance, or by one of
   its dependencies MUST NOT be be reported.  A service or subservice
   under maintenance MAY propagate a symptom "Under Maintenance" towards
   services or subservices that depend on it.

   We illustrate this mechanism on three independent examples based on
   the assurance graph depicted in Figure 2:

   o  Device maintenance, for instance upgrading the device OS.  The
      operator sets the "under-maintenance" flag for the subservice
      "Peer1" device.  This inhibits the emission of symptoms from
      "Peer1 Physical Interface", "Peer1 Tunnel Interface" and "Tunnel
      Service Instance".  All other subservices are unaffected.

   o  Interface maintenance, for instance replacing a broken optic.  The
      operator sets the "under-maintenance" flag for the subservice
      "Peer1 Physical Interface".  This inhibits the emission of




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      symptoms from "Peer 1 Tunnel Interface" and "Tunnel Service
      Instance".  All other subservices are unaffected.

   o  Routing protocol maintenance, for instance modifying parameters or
      redistribution.  The operator sets the "under-maintenance" flag
      for the subservice "IS-IS Routing Protocol".  This inhibits the
      emission of symptoms from "IP connectivity" and "Tunnel Service
      Instance".  All other subservices are unaffected.

3.8.  Flexible Architecture

   The SAIN architecture is flexible in terms of components.  While the
   SAIN architecture in Figure 1 makes a distinction between two
   components, the SAIN configuration orchestrator and the SAIN
   orchestrator, in practice those two components are mostly likely
   combined.  Similarly, the SAIN agents are displayed in Figure 1 as
   being separate components.  Practically, the SAIN agents could be
   either independent components or directly integrated in monitored
   entities.  A practical example is an agent in a router.

   The SAIN architecture is also flexible in terms of services and
   subservices.  Most examples in this document deal with the notion of
   Network Service YANG modules, with well known service such as L2VPN
   or tunnels.  However, the concepts of services is general enough to
   cross into different domains.  One of them is the domain of service
   management on network elements, with also requires its own assurance.
   Examples includes a DHCP server on a linux server, a data plane, an
   IPFIX export, etc.  The notion of "service" is generic in this
   architecture.  Indeed, a configured service can itself be a service
   for someone else.  Exactly like an DHCP server/ data plane/IPFIX
   export can be considered as services for a device, exactly like an
   routing instance can be considered as a service for a L3VPN, exactly
   like a tunnel can considered as a service for an application in the
   cloud.  The assurance graph is created to be flexible and open,
   regardless of the subservice types, locations, or domains.

   The SAIN architecture is also flexible in terms of distributed
   graphs.  As shown in Figure 1, our architecture comprises several
   agents.  Each agent is responsible for handling a subgraph of the
   assurance graph.  The collector is responsible for fetching the
   subgraphs from the different agents and gluing them together.  As an
   example, in the graph from Figure 2, the subservices relative to Peer
   1 might be handled by a different agent than the subservices relative
   to Peer 2 and the Connectivity and IS-IS subservices might be handled
   by yet another agent.  The agents will export their partial graph and
   the collector will stitch them together as dependencies of the
   service instance.




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   And finally, the SAIN architecture is flexible in terms of what it
   monitors.  Most, if not all examples, in this document refer to
   physical components but this is not a constrain.  Indeed, the
   assurance of virtual components would follow the same principles and
   an assurance graph composed of virtualized components (or a mix of
   virtualized and physical ones) is well possible within this
   architecture.

3.9.  Timing

   The SAIN architecture requires the Network Time Protocol (NTP)
   [RFC5905] between all elements: monitored entities, SAIN agents,
   Service Configuration Orchesttrator, the SAIN Collector, as well as
   the SAIN Orchestrator.  This garantees the correlations of all
   symptoms in the system, correlated with the right assurance graph
   version.

   The SAIN agent might have to remove some symptoms for specific
   subservice symptoms, because there are outdated and not relevant any
   longer, or simply because the SAIN agent needs to free up some space.
   Regardless of the reason, it's important for a SAIN collector
   (re-)connecting to a SAIN agent to understand the effect of this
   garbage collection.  Therefore, the SAIN agent contains a YANG object
   specifying the date and time at which the symptoms history starts for
   the subservice instances.

3.10.  New Assurance Graph Generation

   The assurance graph will change along the time, because services and
   subservices come and go (changing the dependencies between
   subservices), or simply because a subservice is now under
   maintenance.  Therefore an assurance graph version must be
   maintained, along with the date and time of its last generation.  The
   date and time of a particular subservice instance (again dependencies
   or under maintenane) might be kept.  From a client point of view, an
   assurance graph change is triggered by the value of the assurance-
   graph-version and assurance-graph-last-change YANG leaves.  At that
   point in time, the client (collector) follows the following process:

   o  Keep the previous assurance-graph-last-change value (let's call it
      time T)

   o  Run through all subservice instance and process the subservice
      instances for which the last-change is newer that the time T

   o  Keep the new assurance-graph-last-change as the new referenced
      date and time




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4.  Security Considerations

   The SAIN architecture helps operators to reduce the mean time to
   detect and mean time to repair.  As such, it should not cause any
   security threats.  However, the SAIN agents must be secure: a
   compromised SAIN agents could be sending wrong root causes or
   symptoms to the management systems.

   Except for the configuration of telemetry, the agents do not need
   "write access" to the devices they monitor.  This configuration is
   applied with a YANG module, whose protection is covered by Secure
   Shell (SSH) [RFC6242] for NETCONF or TLS [RFC8446] for RESTCONF.

   The data collected by SAIN could potentially be compromising to the
   network or provide more insight into how the network is designed.
   Considering the data that SAIN requires (including CLI access in some
   cases), one should weigh data access concerns with the impact that
   reduced visibility will have on being able to rapidly identify root
   causes.

   If a closed loop system relies on this architecture then the well
   known issue of those system also applies, i.e., a lying device or
   compromised agent could trigger partial reconfiguration of the
   service or network.  The SAIN architecture neither augments or
   reduces this risk.

5.  IANA Considerations

   This document includes no request to IANA.

6.  Contributors

   o  Youssef El Fathi

   o  Eric Vyncke

7.  Open Issues

      Refer to the Intent-based Networking NMRG documents

8.  References

8.1.  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>.



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   [RFC5905]  Mills, D., Martin, J., Ed., Burbank, J., and W. Kasch,
              "Network Time Protocol Version 4: Protocol and Algorithms
              Specification", RFC 5905, DOI 10.17487/RFC5905, June 2010,
              <https://www.rfc-editor.org/info/rfc5905>.

   [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>.

8.2.  Informative References

   [I-D.claise-opsawg-service-assurance-yang]
              Claise, B. and J. Quilbeuf, "Service Assurance for Intent-
              based Networking Architecture", February 2020.

   [RFC2865]  Rigney, C., Willens, S., Rubens, A., and W. Simpson,
              "Remote Authentication Dial In User Service (RADIUS)",
              RFC 2865, DOI 10.17487/RFC2865, June 2000,
              <https://www.rfc-editor.org/info/rfc2865>.

   [RFC3164]  Lonvick, C., "The BSD Syslog Protocol", RFC 3164,
              DOI 10.17487/RFC3164, August 2001,
              <https://www.rfc-editor.org/info/rfc3164>.

   [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>.

   [RFC6242]  Wasserman, M., "Using the NETCONF Protocol over Secure
              Shell (SSH)", RFC 6242, DOI 10.17487/RFC6242, June 2011,
              <https://www.rfc-editor.org/info/rfc6242>.

   [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>.

   [RFC7950]  Bjorklund, M., Ed., "The YANG 1.1 Data Modeling Language",
              RFC 7950, DOI 10.17487/RFC7950, August 2016,
              <https://www.rfc-editor.org/info/rfc7950>.

   [RFC8040]  Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
              Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,
              <https://www.rfc-editor.org/info/rfc8040>.





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   [RFC8199]  Bogdanovic, D., Claise, B., and C. Moberg, "YANG Module
              Classification", RFC 8199, DOI 10.17487/RFC8199, July
              2017, <https://www.rfc-editor.org/info/rfc8199>.

   [RFC8446]  Rescorla, E., "The Transport Layer Security (TLS) Protocol
              Version 1.3", RFC 8446, DOI 10.17487/RFC8446, August 2018,
              <https://www.rfc-editor.org/info/rfc8446>.

   [RFC8641]  Clemm, A. and E. Voit, "Subscription to YANG Notifications
              for Datastore Updates", RFC 8641, DOI 10.17487/RFC8641,
              September 2019, <https://www.rfc-editor.org/info/rfc8641>.

   [RFC8907]  Dahm, T., Ota, A., Medway Gash, D., Carrel, D., and L.
              Grant, "The Terminal Access Controller Access-Control
              System Plus (TACACS+) Protocol", RFC 8907,
              DOI 10.17487/RFC8907, September 2020,
              <https://www.rfc-editor.org/info/rfc8907>.

Appendix A.  Changes between revisions

   v02 - v03

   o  Timing Concepts

   o  New Assurance Graph Generation

   v01 - v02

   o  Handling maintenance windows

   o  Flexible architecture better explained

   o  Improved the terminology

   o  Notion of mapping information model to data model, while waiting
      for YANG to be everywhere

   o  Started a security considerations section

   v00 - v01

   o  Terminology clarifications

   o  Figure 1 improved

Acknowledgements





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   The authors would like to thank Stephane Litkowski, Charles Eckel,
   Rob Wilton, Vladimir Vassiliev, Gustavo Alburquerque, Stefan Vallin,
   and Eric Vyncke for their reviews and feedback.

Authors' Addresses

   Benoit Claise
   Huawei

   Email: benoit.claise@huawei.com


   Jean Quilbeuf
   Independent

   Email: jean@quilbeuf.net


   Diego R. Lopez
   Telefonica I+D
   Don Ramon de la Cruz, 82
   Madrid  28006
   Spain

   Email: diego.r.lopez@telefonica.com


   Dan Voyer
   Bell Canada
   Canada

   Email: daniel.voyer@bell.ca


   Thangam Arumugam
   Cisco Systems, Inc.
   Milpitas (California)
   United States of America

   Email: tarumuga@cisco.com











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