Network Working Group N. Davis, Ed.
Internet-Draft Ciena
Intended status: Informational A. Farrel, Ed.
Expires: 29 May 2025 Old Dog Consulting
T. Graf
Swisscom
Q. Wu
Huawei
C. Yu
Huawei Technologies
25 November 2024
Some Key Terms for Network Fault and Problem Management
draft-ietf-nmop-terminology-08
Abstract
This document sets out some terms that are fundamental to a common
understanding of network fault and problem management within the
IETF.
The purpose of this document is to bring clarity to discussions and
other work related to network fault and problem management, in
particular to YANG models and management protocols that report, make
visible, or manage network faults and problems.
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
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and may be updated, replaced, or obsoleted by other documents at any
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material or to cite them other than as "work in progress."
This Internet-Draft will expire on 29 May 2025.
Copyright Notice
Copyright (c) 2024 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Please review these documents carefully, as they describe your rights
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Usage of Terms . . . . . . . . . . . . . . . . . . . . . . . 3
3. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3.1. Context Terminology . . . . . . . . . . . . . . . . . . . 3
3.2. Core Terms . . . . . . . . . . . . . . . . . . . . . . . 5
3.3. Other Terms . . . . . . . . . . . . . . . . . . . . . . . 8
4. Workflow Explanations . . . . . . . . . . . . . . . . . . . . 8
5. Security Considerations . . . . . . . . . . . . . . . . . . . 13
6. Privacy Considerations . . . . . . . . . . . . . . . . . . . 13
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 13
Informative References . . . . . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15
1. Introduction
Successful operation of large or busy networks depends on effective
network management. Network management comprises a virtuous circle
of network control, network observability, network analytics, network
assurance, and back to network control. Network fault and problem
management is an important aspect of network management and control
solutions. It deals with the reporting, inspection, correlation, and
management of events within the network. The intention is to focus
on those events that have a negative effect on the network's ability
to forward traffic in an optimal way. Fault and problem management
extends to include actions taken to determine the causes of problems
and to work toward recovery of optimal network behavior.
A number of work efforts within the IETF seek to provide components
of a fault management system, such as YANG models or management
protocols. It is important that a common terminology is used so that
there is a clear understanding of how the elements of the management
and control solutions fit together, and how faults and problems will
be handled.
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This document sets out some terms that are fundamental to a common
understanding of network fault and problem management. While
"faults" and "problems" are concepts that apply at all levels of
technology in the Internet, the scope of this document is restricted
to the network layer and below, hence this document is specifically
about "network fault and problem management."
The terms defined in this document are principally intended for
consistent use within the IETF. Where similar concepts are described
in other bodies, an attempt has been made to harmonize with those
other descriptions, but there is care needed where terms are not used
consistently between bodies or where terms are applied outside the
network layer. If other bodies find the terminology defined in this
document useful, they are free to use it.
Note that some useful terms are defined in [RFC3877] and [RFC8632].
The definitions in this document are informed by those documents, but
they are not dependent on that prior work.
2. Usage of Terms
Other documents may make use of the terms as defined in this
document. It is suggested here that such uses should use
capitalization of the terms as in this document, and should include
an early section listing the terms inherited from this document with
a citation.
3. Terminology
This section contains key terms. It is split into three subsections.
* Section 3.1 contains terms that help to set the context for the
incident and fault management systems.
* Section 3.2 includes specific and detailed core terms that will be
used in other documents that describe elements of the fault
management systems.
* Section 3.3 provides two further terms that may be helpful.
3.1. Context Terminology
This section includes some terminology that helps describe the
context for the rest of this work. The terms may be viewed as a
cascaded hierarchy with each subsequent term building on the
previous. The definitions are deliberately kept relatively terse.
Further documents may expand on these terms without loss of
specificity.
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Network Telemetry: This is defined in [RFC9232] and describes the
process of collecting operational network data categorized into
network planes. Data collected through the Network Telemetry
process does not contain network or device configuration
information. Nor does it contain any data related to service
definition (i.e., intent per [RFC9315]).
Network Monitoring: This is the process of keeping a continuous
record of a resource, function, or connectivity service. The term
'monitoring' focuses on one single dimension and measurement in
dimensional data modeling [DimensionalModeling]. This could be a
measurement of the service state, a network function measurement,
or the state of a network function of a resource as an example.
Network Analytics: Network Analytics is the process of deriving
analytical insights into or from operational network data. A
process could be piece of software, a system, or a human that
analyzes operational data and outputs new analytical data, ideally
metadata (a symptom for example), which is related to the
operational data.
Network Observability: This is the enablement of network behavioral
assessment through analysis of observed operational network data
(logs, alarms, traces, etc.) with the aim of detecting symptoms of
network behavior, and to identify, anomalies and their causes.
Network Observability begins with information gathered using
Network Monitoring tools and that may be further enriched with
other operational data (e.g., change records). The expected
outcome of the observability processes is identification and
analysis of deviations in observed state versus the expected state
of a network.
Thus, there is a cascaded sequence where:
* Network Telemetry: the process of collecting operational data from
the network.
* Network Monitoring: the process of creating/keeping a record of
data gathered in Network Telemetry.
* Network Analytics: the process of deriving insight through the
data recorded in Network Monitoring.
* Network Observability: the process of enabling behavioral
assessment of the network through Network Analytics.
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3.2. Core Terms
The terms are presented below in an order that is intended to flow
such that it is possible to gain understanding reading top to bottom.
The figures and explanations in Section 4 may aid understanding the
terms set out here.
System: An assembly of components that exhibits some behavior.
Resource: A component of a System.
Resource is a recursive concept so that a Resource may be a
collection of other Resources (for example, a network node
comprises a collection of interfaces).
Characteristic: Observable or measurable aspect or behavior
associated with a Resource.
* A Characteristic may be considered with respect to the concept
of dimensional modeling that is built on facts (see 'value',
below) and dimensions (the contexts and descriptors that
identify and give meaning to the facts).
* The term "Metric" is another word for "Characteristic".
Value: A Value is the measurement of a Characteristic associated
with a Resource. It may be in the form of a categorization (e.g.,
high or low), an integer (e.g., a count), or on a continuous
variable (e.g., an analogue measurement).
Condition: A Condition is an interpretation of the Values of a set
of Characteristics of the Resource (with respect to working order
or some other aspect relevant to the Resource purpose/
application).
Change: In the context of Network Monitoring, a Change is the
variation in the Value of a Characteristic associated with a
Resource.
* Most Changes are not noteworthy (i.e., do not have Relevance).
* Perception of Change depends upon Detection, the sampling
rate/accuracy/detail, and perspective.
Detect: To notice the presence of something (State, Change,
activity, form, etc.).
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* Hence also to notice a Change (from the perspective of the
viewer).
Event: The variation in Value of a Characteristic of a Resource at a
measured instant in time (i.e., the period is negligible).
* Compared with a Change, which may be over a period of time, an
Event happens at a measurable instant.
State: A particular Condition that something (e.g., a Resource) is
in (at a specific time).
* While a State may be observed at a specific moment in time, it
is actually achieved by summarizing the measurement over time
in a process sometimes called State compression.
Relevance: Consideration of an Event, State, or Value (through the
application of policy, relative to a specific perspective, intent,
and in relation to other Events, States, and Values) to determine
whether it is of note to the system that controls or manages the
network.
Occurrence: An Event with Relevance.
A particular Change with Relevance.
* An Occurrence may be an aggregation or abstraction of smaller
Occurrences.
* Applies to all scales and scopes, i.e., is essentially fractal
(can recurse indefinitely).
* Note that Occurrence is used here with respect to the temporal
dimension.
Fault: An Occurrence that is not desired/required (as it may be
indicative of a current or future undesired State). A Fault can
generally be associated with a known cause. See [RFC8632] for a
more detailed discussion of network faults.
Problem: A State regarded as undesirable and which may require
remedial action. A Problem cannot necessarily be associated with
a cause. The resolution of a Problem does not necessarily act on
the thing that has the Problem.
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* Note that there is a historic aspect to the concept of a
Problem. The current State may be operational, but there could
have been a failure that is unexplained, and the fact of that
unexplained recent failure is a Problem.
* Note that whilst a Problem is unresolved it may continue to
require attention. A record of resolved Problems may be
maintained in a log.
* Note that there may be a State which is considered to be a
Problem from several perspectives (e.g., a loss of light State
may cause multiple services to fail). A State Change (so that
the light recovers) may cause the Problem to be resolved from
one perspective (the services are operational once more), but
may leave the Problem as unresolved (because the loss of light
has not been explained). There could be a further development
(the reason for the temporary loss of light is traced to a
microbend in the fiber that is repaired) resulting in that
unresolved Problem now being resolved. But this leaves a
further Problem still unresolved (why did the microbend occur
in the first place?).
Incident: A Network Incident is an undesired Occurrence such as an
unexpected interruption of a network service, degradation of the
quality of a network service, or the below-target performance of a
network service. An Incident results from one or more Problems,
and a Problem may give rise to or contribute to one or more
Incidents. Greater discussion of Network Incidents, including
Incident management, can be found in
[I-D.ietf-nmop-network-incident-yang].
Anomaly: A (network) Anomaly is an unusual or unexpected Event or
pattern in network data in the forwarding plane, control plane, or
management plane that deviates from the normal, expected behavior.
See [I-D.ietf-nmop-network-anomaly-architecture] for more details.
Symptom: An observable Characteristic/State/Condition considered as
an indication of a Problem or potential Problem.
Cause: The Events (Detected or otherwise) that gave rise to a Fault/
Problem.
Consolidation: The process of considering multiple Problems,
Symptoms, and their Causes to determine the underlying Causes.
Alert: The indication of a Fault.
Alarm: Per [RFC8632], an Alarm signifies an undesirable State in a
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Resource that requires corrective action. From a management point
of view, an Alarm can be seen as a State in its own right and the
transition to this State is a Fault and may result in an Alert
being issued. The receipt of this Alert may give rise to a
continuous indication (to a human operator) highlighting the
potential or actual presence of a Problem.
3.3. Other Terms
Two other terms may be helpful:
Transient: A State, considered as a Problem, that persists for a
limited amount of time before becoming resolved without direct
action by an operator or by a system that controls or manages the
network.
Intermittent: A State that is not continuous, but keeps occurring in
some time frame.
4. Workflow Explanations
The relationship between System, Resource, and Characteristics is
shown in Figure 1. A System is comprised of Resources, and Resources
have Characteristics.
Characteristics
^
|
Resource
^
|
System
Figure 1: Relationship Between Elements of a System
The Value of a Characteristic of a Resource is expected to change
over time. Specific Changes in Value may be noticed at a specific
time (as digital Changes), Detected, and treated as Events. This is
shown on the left of Figure 2.
The center of Figure 2 shows how the Value of a Characteristic may
change over time. The Value may be Detected at specific times or
periodically and give rise to States (and consequently State
Changes).
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In practice, the Characteristic may vary in an analog manner over
time as shown on the right hand side of Figure 2. The Value can be
read or reported (i.e., Detected) periodically leading to Analog
Values that may be deemed Values with Relevance, or may be evaluated
over time as shown in Figure 6.
Event State Value
^ ^ ^
Detect : Detect : Detect :
: : :
^ ^ ^ ^ ^ /\
: : : : : / \
: : : : : /\ / \
__ __ _____ / \/
| | | | /\/
__| |__ ____| |____ /
Change at a time Change over time Change over time
Figure 2: Characteristics and Changes
Figure 3 shows the workflow progress for Events. As noted above, an
Event is a Change in the Value of a Characteristic at a time. The
Event may be evaluated (considering policy, relative to a specific
perspective, with a view to intent, and in relation to other Events,
States, and Values) to determine if it is an Occurrence and possibly
to indicate a Change of State. An Occurrence may be undesirable (a
Fault) and that can cause an Alert to be generated, may be evidence
of a Problem and could directly indicate a Cause. In some cases, an
Alert may give rise to an Alarm highlighting the potential or actual
presence of a Problem.
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Alert- - - - > Alarm
^
|
| -----> Cause
| |
|----------> Problem
|
|
Fault
^
|
|
|
Occurrence
^
|
|----------> State
|
|
Event
Figure 3: Events and Dependent Terms
Parallel to the workflow for Events, Figure 4 shows the workflow
progress for States. As shown in Figure 2, Change noted at a
particular time gives rise to State. The State may be deemed to have
Relevance considering policy, relative to a specific perspective,
with a view to intent, and in relation to other Events, States, and
Values. A State with Relevance may be deemed a Problem, or may
indicate a Problem.
Problems may be considered as Symptoms and may map directly or
indirectly to Causes. An Incident results from one or more Problems.
An Alarm may be raised as the result of a Problem.
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Alarm
^
| ------> Incident
| |
| | ---> Cause
| | |
Problem---------> Symptom
^
|
| Relevance
|
|
State
Figure 4: States and Dependent Terms
Figure 5 shows how Faults and Problems may be Consolidated to
determine the Causes. The arrows show how one item may give rise to
another.
A Cause can be indicated by or determined from Faults, Problems and
Symptoms. It may be that one Cause points to another, and can also
be considered as a Symptom. The determination of Causes can consider
multiple inputs. An Incident results from one or more Problems.
---------
------------- | |
| ----------> | Symptom |
| | | |
| | ---------
v | ^
--------- |
------->| Cause |<--------- |
| --------- | |
| ^ | | |
| | | | |
| --- | |
| | |
--------- --------- ----------
| Fault |------------------->| Problem |------->| Incident |
--------- --------- ----------
Figure 5: Consolidation of Symptoms and Causes
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The final figure in this section (Figure 6) shows how thresholds are
important in the consideration of Analog Values and Events. The
arrows in the figure show how one item may give rise to or utilize
another. The use of threshold-driven Events and States (and the
Alerts that they might give rise to) must be treated with caution to
dampen any "flapping" (so that consistent States may be observed) and
to avoid overwhelming management processes or systems. Analog Values
may be read or notified from the Resource and could transition a
threshold, be deemed Values with Relevance, or evaluated over time.
Events may be counted, and the Count may cross a threshold or reach a
Value of Relevance.
The Threshold Process may be implementation-specific and subject to
policies. When a threshold is crossed and any other conditions are
matched, an Event may be determined, and treated like any other
Event.
Occurrence
^
|
|---------------------> State
|
| ------- Relevance
|------>| Count |-----------------------------> Value
| ------- | ^
| | | |
| | | | Relevance
| | v |
| | ----------- ----------------
Event | | Evaluated | | |
^ | | over time |<--------| Analog Value |
| v ----------- | |
| ----------- | | |
| | Threshold | | | |
|<----| Process |<------ | |
| | |<----------------------| |
| ----------- ----------------
| ^
| |
| Detect Detect |
| |
Change at a Time Change over Time
Figure 6: Counts, Thresholds, and Values
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5. Security Considerations
This document specifies terminology and has no direct effect on the
security of implementations or deployments. However, protocol
solutions and management models need to be aware of several aspects:
* The exposure of information pertaining to Faults may make
available knowledge of the internal workings of a network (in
particular its vulnerabilities) that may be of use to an attacker.
* Systems that generate management information (messages,
notifications, etc.) when Faults occur, may be attacked by causing
them to generate so much information that the system that manages
the network is swamped and unable to properly manage the network.
* Reporting false information about Faults (or masking reports of
Faults) may cause the system that manages the network to function
incorrectly.
6. Privacy Considerations
In general, Fault Management should not expose information about end-
user activities or user data. The main privacy concern is for a
network operator to keep control of all information about Faults to
protect their privacy and the details of how the network operators
operate their network.
7. IANA Considerations
This document makes no requests for IANA action.
Acknowledgments
The authors would like to thank Med Boucadair, Wanting Du, Joe
Clarke, Javier Antich, Benoit Claise, Christopher Janz, Sherif
Mostafa, Kristian Larsson, Dirk Hugo, Carsten Bormann, Hilarie Orman,
Stewart Bryant, and Paul Kyzivat for their helpful comments.
Special thanks to the team that met at a side meeting at IETF-120 to
discuss some of the thorny issues:
* Benoit Claise
* Watson Ladd
* Brad Peters
* Bo Wu
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* Georgios Karagiannis
* Olga Havel
* Vincenzo Riccobene
* Yi Lin
* Jie Dong
* Aihua Guo
* Thomas Graf
* Qin Wu
* Chaode Yu
* Adrian Farrel
Informative References
[DimensionalModeling]
Wikipedia, "Dimensional Modeling", 18 November 2024,
<https://en.wikipedia.org/w/
index.php?title=Dimensional_modeling>.
[I-D.ietf-nmop-network-anomaly-architecture]
Graf, T., Du, W., and P. Francois, "An Architecture for a
Network Anomaly Detection Framework", Work in Progress,
Internet-Draft, draft-ietf-nmop-network-anomaly-
architecture-01, 20 October 2024,
<https://datatracker.ietf.org/doc/html/draft-ietf-nmop-
network-anomaly-architecture-01>.
[I-D.ietf-nmop-network-incident-yang]
Hu, T., Contreras, L. M., Wu, Q., Davis, N., and C. Feng,
"A YANG Data Model for Network Incident Management", Work
in Progress, Internet-Draft, draft-ietf-nmop-network-
incident-yang-02, 10 October 2024,
<https://datatracker.ietf.org/doc/html/draft-ietf-nmop-
network-incident-yang-02>.
[RFC3877] Chisholm, S. and D. Romascanu, "Alarm Management
Information Base (MIB)", RFC 3877, DOI 10.17487/RFC3877,
September 2004, <https://www.rfc-editor.org/info/rfc3877>.
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[RFC8632] Vallin, S. and M. Bjorklund, "A YANG Data Model for Alarm
Management", RFC 8632, DOI 10.17487/RFC8632, September
2019, <https://www.rfc-editor.org/info/rfc8632>.
[RFC9232] Song, H., Qin, F., Martinez-Julia, P., Ciavaglia, L., and
A. Wang, "Network Telemetry Framework", RFC 9232,
DOI 10.17487/RFC9232, May 2022,
<https://www.rfc-editor.org/info/rfc9232>.
[RFC9315] Clemm, A., Ciavaglia, L., Granville, L. Z., and J.
Tantsura, "Intent-Based Networking - Concepts and
Definitions", RFC 9315, DOI 10.17487/RFC9315, October
2022, <https://www.rfc-editor.org/info/rfc9315>.
Authors' Addresses
Nigel Davis (editor)
Ciena
United Kingdom
Email: ndavis@ciena.com
Adrian Farrel (editor)
Old Dog Consulting
United Kingdom
Email: adrian@olddog.co.uk
Thomas Graf
Swisscom
Binzring 17
CH-8045 Zurich
Switzerland
Email: thomas.graf@swisscom.com
Qin Wu
Huawei
101 Software Avenue, Yuhua District
Nanjing
Jiangsu, 210012
China
Email: bill.wu@huawei.com
Chaode Yu
Huawei Technologies
Email: yuchaode@huawei.com
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