OPSAWG B. Claise
Internet-Draft J. Quilbeuf
Intended status: Informational Cisco Systems, Inc.
Expires: May 19, 2020 November 16, 2019
Service Assurance for Intent-based Networking Architecture
draft-claise-opsawg-service-assurance-architecture-01
Abstract
This document describes the 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
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This Internet-Draft will expire on May 19, 2020.
Copyright Notice
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described in the Simplified BSD License.
Table of Contents
1. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Architecture . . . . . . . . . . . . . . . . . . . . . . . . 6
3.1. Decomposing a Service Instance Configuration into an
Assurance Graph . . . . . . . . . . . . . . . . . . . . . 8
3.2. Intent and Assurance Graph . . . . . . . . . . . . . . . 9
3.3. Subservices . . . . . . . . . . . . . . . . . . . . . . . 10
3.4. Building the Expression Graph from the Assurance Graph . 10
3.5. Building the Expression from a Subservice . . . . . . . . 11
3.6. Open Interfaces with YANG Modules . . . . . . . . . . . . 11
4. Security Considerations . . . . . . . . . . . . . . . . . . . 12
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 12
6. Open Issues . . . . . . . . . . . . . . . . . . . . . . . . . 12
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 12
7.1. Normative References . . . . . . . . . . . . . . . . . . 12
7.2. Informative References . . . . . . . . . . . . . . . . . 12
Appendix A. Changes between revisions . . . . . . . . . . . . . 13
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 13
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 13
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
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 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.
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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), for informational
reasons.
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 configuraiton 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
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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.
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
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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+
[I-D.ietf-opsawg-tacacs], 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.
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
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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 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.
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.
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 health status of the assured
service instances and subservices. Finally, the automation loop is
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closed by having the SAIN Collector providing feedback to the network
orchestrator.
+-----------------+
| 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
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called a metric, which operations to apply to the metrics for
computing the health status.
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 The result of this decomposition is the assurance case of a
service instance, that can be represented is 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 standardization.
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.
A subservice is characterized by a list of metrics to fetch and a
list of computations to apply to these metrics in order to produce a
health status. Subservices, as services, have high-level parameters
which defines which object should be assured.
3.4. Building the Expression Graph from the Assurance Graph
From the assurance graph is derived a so-called expression graph,
which is actually a DAG whose sources are constants or metrics and
other nodes are operators. The expression 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. Dependending on the
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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.
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.
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.
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4. Security Considerations
TO BE COMPLETED
5. IANA Considerations
This document includes no request to IANA.
6. Open Issues
-Security Considerations to be completed
7. References
7.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
7.2. Informative References
[I-D.claise-opsawg-service-assurance-yang]
Claise, B. and J. Quilbeuf, "Service Assurance for Intent-
based Networking Architecture", November 2019.
[I-D.ietf-opsawg-tacacs]
Dahm, T., Ota, A., dcmgash@cisco.com, d., Carrel, D., and
L. Grant, "The TACACS+ Protocol", draft-ietf-opsawg-
tacacs-15 (work in progress), September 2019.
[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>.
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[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>.
[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>.
[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>.
[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>.
Appendix A. Changes between revisions
v00 - v01
o Terminology clarifications
o Figure 1 improved
Acknowledgements
The authors would like to thank Stephane Litkowski, Charles Eckel,
and Rob Wilton for their reviews.
Authors' Addresses
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Benoit Claise
Cisco Systems, Inc.
De Kleetlaan 6a b1
1831 Diegem
Belgium
Email: bclaise@cisco.com
Jean Quilbeuf
Cisco Systems, Inc.
1, rue Camille Desmoulins
92782 Issy Les Moulineaux
France
Email: jquilbeu@cisco.com
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