Internet-Draft Incident Terminology June 2024
Davis, et al. Expires 12 December 2024 [Page]
Workgroup:
Network Working Group
Internet-Draft:
draft-ietf-nmop-terminology-01
Published:
Intended Status:
Informational
Expires:
Authors:
N. Davis, Ed.
Ciena
A. Farrel, Ed.
Old Dog Consulting
T. Graf
Swisscom
Q. Wu
Huawei
C. Yu
Huawei Technologies

Some Key Terms for Network Incident and Problem Management

Abstract

This document sets out some terms that are fundamental to a common understanding of network incident and problem management within the IETF.

The purpose of this document is to bring clarity to discussions and other work related to network incident and problem management in particular YANG models and management protocols that report, make visible, or manage network incidents 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 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 12 December 2024.

Table of Contents

1. Introduction

Successful operation of large or busy networks depends on network management. Network management comprises a virtuous circle of network control, network observability, network analytics, network assurance, and back to network control. Network incident 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 have a negative effect on the network's ability to forward traffic in an optimal way. Incident 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 an incident 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 incidents and problems will be handled.

This document sets out some terms that are fundamental to a common understanding of incident and problem management. These terms are mainly intended for use within IETF documents.

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. Terminology

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 3 may aid understanding the terms set out here.

System:

An assembly of components that exhibits some behavior.

External System:

A system that includes elements that are beyond the scope of the control system.

Controlled External System:

An external system that is of interest to and is influenced by the control system. Viewed as a collection of resources.

Resource:

A component, commodity, service, or capability that can be used to support the delivery of some function.

  • Resource is a recursive concept so that a resource may be a collection of other resources (for example, a network node is a collection of interfaces).

  • Connectivity services and network capabilities may be realized by the collection of many resources, yet services and capabilities may also be recognized as resources in their own right.

Characteristic:

Observable or measurable aspect or behavior associated with a resource.

  • A characteristic may be considered with respect to the concept of dimensional that is built on facts (see 'value', below) and dimensions (the contexts and descriptors that identify and give meaning to the facts).

Value:

A measurable amount which may be in the form of an integer (e.g., a count) or on a continuous variable (e.g., an analogue measurement) associated with a characteristic.

Condition:

The 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:

Variation in values associated with a characteristic of a resource at a specific time or over time.

  • Most changes are not noteworthy (i.e., are not relevant).

  • 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.).

  • Hence also to notice a change (from the perspective of the viewer).

Event:

The detected change in value (of a characteristic of a resource) at a measurable instant in time (i.e., the period is negligible).

  • Compared with a change, which is 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 viewpoint/perspective, intent, and in relation to other events, states, and values) to determine whether it is of note to the control system.

Occurrence:

A relevant event.

A particular relevant change.

  • 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.

Incident:

An occurrence that is not desired/required (as it may be indicative of a future undesired State).

Problem:

A state regarded as undesirable and may require remedial action.

  • 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 is now resolved. But this leaves a further problem still unresolved (why did the microbend occur in the first place?).

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 problem.

Root Cause:

The fundamental cause that gave rise to all associated problems.

Consolidation:

The process of considering multiple problems, symptoms, and their causes to determine the root cause.

Alert:

The indication of an incident.

Alarm:

A continuous indication (to a human operator) highlighting the potential or actual presence of a problem.

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 control system.

Intermittent:

A state that is not maintained, but keeps occurring in some meaningfully short time frame.

3. Workflow Explanations

The relationship between system, resource, and characteristics is shown in Figure 1. A Controlled External System is comprised of Resources, and Resources have Characteristics.


                Characteristics
                       ^
                       |
                    Resource
                       ^
                       |
           Controlled External System
                       ^
                       |
                External 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).

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 Analogue Values that may be deemed Relevant Values, 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 viewpoint/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 (an Incident) and that can cause an Alert to be generated, may be evidence of a Problem and could directly indicate a Cause.



        Alert- - - - > Alarm
          ^
          |
          |     -----> Cause
          |    |
          |----------> Problem
          |
          |
      Incident
          ^
          |
          |
          |
     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 relevant (via Relevance) considering policy, relative to a specific viewpoint/perspective, with a view to intent, and in relation to other Events, States, and Values. A Relevant State 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 Alarm may be raised as the result of a Problem.


        Alarm
          ^
          |
          |       ----> Cause
          |      |
      Problem---------> Symptom
          ^
          |
          |
          |
    Relevant State
          ^
          |
          |
          |
        State

Figure 4: States and Dependent Terms

Figure 5 shows how Incidents and Problems may be consolidated to determine Causes and the underlying Root Cause.

A Cause can be indicated by or determined from Incidents, Problems and Symptoms. It may be that one Cause points to another, and can also be considered as a Symptom. The determination of Causes and the Root Cause can consider multiple inputs.


                 ------------
                | Root Cause |
                 ------------
                      ^                 ---------
                      |  ------------- |         |
                      | |  ----------> | Symptom |
                      | | |            |         |
                      | | |             ---------
                      | v |                 ^
                    ---------               |
         --------->|  Cause  |<----------   |
        |           ---------            |  |
        |             ^   |              |  |
        |             |   |              |  |
        |              ---               |  |
        |                                |  |
      ----------                      ---------
     | Incident |------------------> | Problem |
      ----------                      ---------

Figure 5: Consolidation of Symptoms and Causes

The final figure in this section (Figure 6) shows how thresholds are important in the consideration of Analogue Values and Events. Analogue Values may be read or notified from the Resource and could transition a threshold, be deemed Relevant Values, or evaluated over time. Events may be counted, and the Count may cross a threshold or reach a Relevant Value.

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
     |
     |        -------
     |------>| Count |-------------------------> Relevant Value
     |        -------          |                       ^
     |           |             |                       |
     |           |             |                       |
     |           |             v                       |
     |           |        -----------           ----------------
   Event         |       | Evaluated |         |                |
     ^           |       | over time |<--------| Analogue Value |
     |           v        -----------          |                |
     |      -----------        |               |                |
     |     | Threshold |       |               |                |
     |<----|  Process  |<------                |                |
     |     |           |<----------------------|                |
     |      -----------                         ----------------
     |                                                 ^
     |                                                 |
     | Detect                                   Detect |
     |                                                 |
Change at a Time                                Change over Time

Figure 6: Counts, Thresholds, and Values

4. 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:

5. Privacy Considerations

In general, Incident 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 incidents to protect their privacy and the details of how they operate their network.

6. IANA Considerations

This document makes no requests for IANA action.

Acknowledgments

The authors would like to thank Med Boucadair, Wanting Du, and Benoit Claise for their helpful comments.

Informative References

[RFC3877]
Chisholm, S. and D. Romascanu, "Alarm Management Information Base (MIB)", RFC 3877, DOI 10.17487/RFC3877, , <https://www.rfc-editor.org/info/rfc3877>.
[RFC8632]
Vallin, S. and M. Bjorklund, "A YANG Data Model for Alarm Management", RFC 8632, DOI 10.17487/RFC8632, , <https://www.rfc-editor.org/info/rfc8632>.

Authors' Addresses

Nigel Davis (editor)
Ciena
United Kingdom
Adrian Farrel (editor)
Old Dog Consulting
United Kingdom
Thomas Graf
Swisscom
Binzring 17
CH-8045 Zurich
Switzerland
Qin Wu
Huawei
101 Software Avenue, Yuhua District
Nanjing
Jiangsu, 210012
China
Chaode Yu
Huawei Technologies