YANG models for VN & TE Performance Monitoring Telemetry and Scaling Intent Autonomics
draft-lee-teas-actn-pm-telemetry-autonomics-12
The information below is for an old version of the document.
| Document | Type |
This is an older version of an Internet-Draft whose latest revision state is "Replaced".
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|
|---|---|---|---|
| Authors | Young Lee , Dhruv Dhody , Satish Karunanithi , Ricard Vilalta , Daniel King , Daniele Ceccarelli | ||
| Last updated | 2019-04-02 | ||
| Replaced by | draft-ietf-teas-actn-pm-telemetry-autonomics, draft-ietf-teas-actn-pm-telemetry-autonomics | ||
| RFC stream | (None) | ||
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draft-lee-teas-actn-pm-telemetry-autonomics-12
TEAS Working Group Y. Lee (Editor)
Internet Draft Dhruv Dhody
Intended Status: Standard Track Satish Karunanithi
Expires: October 2, 2019 Huawei
Ricard Vilalta
CTTC
Daniel King
Lancaster University
Daniele Ceccarelli
Ericsson
April 2, 2019
YANG models for VN & TE Performance Monitoring Telemetry and Scaling
Intent Autonomics
draft-lee-teas-actn-pm-telemetry-autonomics-12
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Copyright Notice
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Copyright (c) 2019 IETF Trust and the persons identified as the
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Abstract
This document provides YANG data models that describe performance
monitoring telemetry and scaling intent mechanism for TE-tunnels and
Virtual Networks (VN).
The models presented in this draft allow customers to subscribe and
monitor their key performance data of their interest on the level of
TE-tunnel or VN. The models also provide customers with the ability
to program autonomic scaling intent mechanism on the level of TE-
tunnel as well as VN.
Table of Contents
1. Introduction...................................................3
1.1. Terminology...............................................4
1.2. Tree diagram..............................................4
1.3. Prefixes in Data Node Names...............................4
2. Use-Cases......................................................4
3. Design of the Data Models......................................6
3.1. TE KPI Telemetry Model....................................6
3.2. VN KPI Telemetry Model....................................7
4. Autonomic Scaling Intent Mechanism.............................8
5. Notification..................................................10
5.1. YANG Push Subscription Examples..........................10
6. YANG Data Tree................................................11
7. Yang Data Model...............................................13
7.1. ietf-te-kpi-telemetry model..............................13
7.2. ietf-vn-kpi-telemetry model..............................18
8. Security Considerations.......................................21
9. IANA Considerations...........................................21
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10. Acknowledgements.............................................22
11. References...................................................22
11.1. Informative References..................................22
11.2. Normative References....................................23
12. Contributors.................................................24
Authors' Addresses...............................................24
1. Introduction
The YANG model discussed in [VN] is used to operate customer-driven
VNs during the VN instantiation, VN computation, and its life-cycle
service management and operations. YANG model discussed in [TE-
Tunnel] is used to operate TE-tunnels during the tunnel
instantiation, and its life-cycle management and operations.
The models presented in this draft allow the applications hosted by
the customers to subscribe and monitor their key performance data of
their interest on the level of VN [VN] or TE-tunnel [TE-Tunnel]. The
key characteristic of the models presented in this document is a
top-down programmability that allows the applications hosted by the
customers to subscribe and monitor key performance data of their
interest and autonomic scaling intent mechanism on the level of VN
as well as TE-tunnel.
According to the classification of [RFC8309], the YANG data models
presented in this document can be classified as customer service
models, which is mapped to CMI (Customer Network Controller (CNC)-
Multi-Domain Service Coordinator (MSDC) interface) of ACTN
[RFC8453].
[RFC8233] describes key network performance data to be considered
for end-to-end path computation in TE networks. Key performance
indicator is a term that describes critical performance data that
may affect VN/TE-tunnel service. The services provided can be
optimized to meet the requirements (such as traffic patterns,
quality, and reliability) of the applications hosted by the
customers.
This document provides YANG data models generically applicable to
any VN/TE-Tunnel service clients to provide an ability to program
their customized performance monitoring subscription and publication
data models and automatic scaling in/out intent data models. These
models can be utilized by a client network controller to initiate
these capability to a transport network controller communicating
with the client controller via a NETCONF [RFC8341] or a RESTCONF
[RFC8040] interface.
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The data model includes configuration and state data according to
the new Network Management Datastore Architecture [RFC8342].
1.1. Terminology
Refer to [RFC8453], [RFC7926], and [RFC8309] for the key terms used
in this document.
1.2. Tree diagram
A simplified graphical representation of the data model is used in
Section 5 of this this document. The meaning of the symbols in
these diagrams is defined in [RFC8340].
1.3. Prefixes in Data Node Names
In this document, names of data nodes and other data model objects
are prefixed using the standard prefix associated with the
corresponding YANG imported modules, as shown in Table 1.
+---------+------------------------------+-----------------+
| Prefix | YANG module | Reference |
+---------+------------------------------+-----------------+
| rt | ietf-routing-types | [RFC8294] |
| te | ietf-te | [TE-Tunnel] |
| te-types| ietf-te-types | [TE-Types] |
| te-kpi | ietf-te-kpi-telemetry | [This I-D] |
| vn | ietf-vn | [VN] |
| vn-tel | ietf-vn-kpi-telemetry | [This I-D] |
+---------+------------------------------+-----------------+
Table 1: Prefixes and corresponding YANG modules
2. Use-Cases
[PERF] describes use-cases relevant to this draft. It introduces the
dynamic creation, modification and optimization of services based on
the performance monitoring. Figure 1 shows a high-level workflows
for dynamic service control based on traffic monitoring.
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+----------------------------------------------+
| Client +-----------------------------+ |
| | Dynamic Service Control APP | |
| +-----------------------------+ |
+----------------------------------------------+
1.Traffic| /|\4.Traffic | /|\
Monitor& | | Monitor | | 8.Traffic
Optimize | | Result 5.Service | | modify &
Policy | | modify& | | optimize
\|/ | optimize Req.\|/ | result
+----------------------------------------------+
| Orchestrator |
| +-------------------------------+ |
| |Dynamic Service Control Agent | |
| +-------------------------------+ |
| +---------------+ +-------------------+ |
| | Flow Optimize | | vConnection Agent | |
| +---------------+ +-------------------+ |
+----------------------------------------------+
2. Path | /|\3.Traffic | /|\
Monitor | | Monitor | |7.Path
Request | | Result 6.Path | | modify &
| | modify& | | optimize
\|/ | optimize Req.\|/ | result
+----------------------------------------------+
| Network SDN Controller |
| +----------------------+ +-----------------+|
| | Network Provisioning | |Abstract Topology||
| +----------------------+ +-----------------+|
| +------------------+ +--------------------+ |
| |Network Monitoring| |Physical Topology DB| |
| +------------------+ +--------------------+ |
+----------------------------------------------+
Figure 1 Workflows for dynamic service control based on traffic
monitoring
Some of the key points from [PERF] are as follows:
. Network traffic monitoring is important to facilitate automatic
discovery of the imbalance of network traffic, and initiate the
network optimization, thus helping the network operator or the
virtual network service provider to use the network more
efficiently and save CAPEX/OPEX.
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. Customer services have various SLA requirements, such as
service availability, latency, latency jitter, packet loss
rate, BER, etc. The transport network can satisfy service
availability and BER requirements by providing different
protection and restoration mechanisms. However, for other
performance parameters, there are no such mechanisms. In order
to provide high quality services according to customer SLA, one
possible solution is to measure the service SLA related
performance parameters, and dynamically provision and optimize
services based on the performance monitoring results.
. Performance monitoring in a large scale network could generate
a huge amount of performance information. Therefore, the
appropriate way to deliver the information in the client and
network interfaces should be carefully considered.
3. Design of the Data Models
The YANG models developed in this document describe two models:
(i) TE KPI Telemetry Model which provides the TE-Tunnel level of
performance monitoring mechanism and scaling intent mechanism
that allows scale in/out programming by the customer. (See
Section 3.1 & 7.1 for details).
(ii) VN KPI Telemetry Model which provides the VN level of the
aggregated performance monitoring mechanism and scaling
intent mechanism that allows scale in/out programming by the
customer (See Section 3.2 & 7.2 for details).
3.1. TE KPI Telemetry Model
This module describes performance telemetry for TE-tunnel model. The
telemetry data is augmented to tunnel state. This module also
allows autonomic traffic engineering scaling intent configuration
mechanism on the TE-tunnel level. Various conditions can be set for
auto-scaling based on the telemetry data (See Section 5 for details)
The TE KPI Telemetry Model augments the TE-Tunnel Model to enhance
TE performance monitoring capability. This monitoring capability
will facilitate proactive re-optimization and reconfiguration of TEs
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based on the performance monitoring data collected via the TE KPI
Telemetry YANG model.
+------------+ +--------------+
| TE-Tunnel | | TE KPI |
| Model |<---------| Telemetry |
+------------+ augments | Model |
+--------------+
3.2. VN KPI Telemetry Model
This module describes performance telemetry for VN model. The
telemetry data is augmented both at the VN Level as well as
individual VN member level. This module also allows autonomic
traffic engineering scaling intent configuration mechanism on the VN
level. Scale in/out criteria might be used for network autonomics in
order the controller to react to a certain set of variations in
monitored parameters (See Section 4 for illustrations).
Moreover, this module also provides mechanism to define aggregated
telemetry parameters as a grouping of underlying VN level telemetry
parameters. Grouping operation (such as maximum, mean) could be set
at the time of configuration. For example, if maximum grouping
operation is used for delay at the VN level, the VN telemetry data
is reported as the maximum {delay_vn_member_1, delay_vn_member_2,..
delay_vn_member_N}. Thus, this telemetry abstraction mechanism
allows the grouping of a certain common set of telemetry values
under a grouping operation. This can be done at the VN-member level
to suggest how the E2E telemetry be inferred from the per domain
tunnel created and monitored by PNCs. One proposed example is the
following:
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+------------------------------------------------------------+
| Client |
| |
+------------------------------------------------------------+
1.Client sets the | /|\ 2. Orchestrator pushes:
grouping op, and | |
subscribes to the | | VN level telemetry for
VN level telemetry for | | - VN Utilized-bw-percentage
Delay and | | (Minimum across VN Members)
Utilized-bw-pecentage | | - VN Delay (Maximum across VN
\|/ | Members)
+------------------------------------------------------------+
| Orchestrator |
| |
+------------------------------------------------------------+
The VN Telemetry Model augments the basic VN model to enhance VN
monitoring capability. This monitoring capability will facilitate
proactive re-optimization and reconfiguration of VNs based on the
performance monitoring data collected via the VN Telemetry YANG
model.
+----------+ +--------------+
| VN | augments | VN |
| Model |<---------| Telemetry |
+----------+ | Model |
+--------------+
4. Autonomic Scaling Intent Mechanism
Scaling intent configuration mechanism allows the client to
configure automatic scale-in and scale-out mechanisms on both the
TE-tunnel and the VN level. Various conditions can be set for auto-
scaling based on the PM telemetry data.
There are a number of parameters involved in the mechanism:
. scale-out-intent or scale-in-intent: whether to scale-out or
scale-in.
. performance-type: performance metric type (e.g., one-way-delay,
one-way-delay-min, one-way-delay-max, two-way-delay, two-way-
delay-min, two-way-delay-max, utilized bandwidth, etc.)
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. threshold-value: the threshold value for a certain performance-
type that triggers scale-in or scale-out.
. scaling-operation-type: in case where scaling condition can be
set with one or more performance types, then scaling-operation-
type (AND, OR, MIN, MAX, etc.) is applied to these selected
performance types and its threshold values.
. Threshold-time: the duration for which the criteria must hold
true.
. Cooldown-time: the duration after a scaling action has been
triggered, for which there will be no further operation.
The following tree is a part of ietf-te-kpi-telemetry tree whose
model is presented in full detail in Sections 6 & 7.
module: ietf-te-kpi-telemetry
augment /te:te/te:tunnels/te:tunnel:
+-rw te-scaling-intent
| +-rw scale-in-intent
| | +-rw threshold-time? uint32
| | +-rw cooldown-time? uint32
| | +-rw scale-in-operation-type? scaling-criteria-operation
| | +-rw scaling-condition* [performance-type]
| | +-rw performance-type identityref
| | +-rw threshold-value? string
| | +-rw te-telemetry-tunnel-ref? -> /te:te/tunnels/tunnel/name
| +-rw scale-out-intent
| +-rw threshold-time? uint32
| +-rw cooldown-time? uint32
| +-rw scale-out-operation-type? scaling-criteria-operation
| +-rw scaling-condition* [performance-type]
| +-rw performance-type identityref
| +-rw threshold-value? string
| +-rw te-telemetry-tunnel-ref? -> /te:te/tunnels/tunnel/name
Let say the client wants to set the scaling out operation based on
two performance-types (e.g., two-way-delay and utilized-bandwidth
for a te-tunnel), it can be done as follows:
. Set Threshold-time: 3600 (sec) (duration for which the
criteria must hold true)
. Set Cooldown-time: 60 (sec) (the duration after a scaling
action has been triggered, for which there will be no further
operation)
. Set AND for the scale-out-operation-type
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In the scaling condition's list, the following two components can be
set:
List 1: Scaling Condition for Two-way-delay
. performance type: Two-way-delay
. threshold-value: 300 mile-seconds
List 2: Scaling Condition for Utilized bandwidth
. performance type: Utilized bandwidth
. threshold-value: 300 megabytes
5. Notification
This model does not define specific notifications. To enable
notifications, the mechanism defined in [YANG-PUSH]
and [Event-Notification] can be used. This mechanism currently
allows the user to:
. Subscribe notifications on a per client basis.
. Specify subtree filters or xpath filters so that only interested
contents will be sent.
. Specify either periodic or on-demand notifications.
5.1. YANG Push Subscription Examples
[YANG-PUSH] allows subscriber applications to request a continuous,
customized stream of updates from a YANG datastore.
Below example shows the way for a client to subscribe for the
telemetry information for a particular tunnel (Tunnel1). The
telemetry parameter that the client is interested in is one-way-
delay.
<netconf:rpc netconf:message-id="101"
xmlns:netconf="urn:ietf:params:xml:ns:netconf:base:1.0">
<establish-subscription
xmlns="urn:ietf:params:xml:ns:yang:ietf-yang-push:1.0">
<filter netconf:type="subtree">
<te xmlns="urn:ietf:params:xml:ns:yang:ietf-te">
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<tunnels>
<tunnel>
<name>Tunnel1</name>
<identifier/>
<state>
<te-telemetry xmlns="urn:ietf:params:xml:ns:yang:ietf-te-kpi-
telemetry">
<one-way-delay/>
</te-telemetry>
</state>
</tunnel>
</tunnels>
</te>
</filter>
<period>500</period>
<encoding>encode-xml</encoding>
</establish-subscription>
</netconf:rpc>
This example shows the way for a client to subscribe for the
telemetry information for all VNs. The telemetry parameter that the
client is interested in is one-way-delay and one-way-utilized-
bandwidth.
<netconf:rpc netconf:message-id="101"
xmlns:netconf="urn:ietf:params:xml:ns:netconf:base:1.0">
<establish-subscription
xmlns="urn:ietf:params:xml:ns:yang:ietf-yang-push:1.0">
<filter netconf:type="subtree">
<actn-state xmlns="urn:ietf:params:xml:ns:yang:ietf-vn">
<vn>
<vn-list>
<vn-id/>
<vn-name/>
<vn-telemetry xmlns="urn:ietf:params:xml:ns:yang:ietf-actn-te-kpi-
telemetry">
<one-way-delay/>
<one-way-utilized-bandwidth/>
</vn-telemetry >
</vn-list>
</vn>
</actn-state>
</filter>
<period>500</period>
</establish-subscription>
</netconf:rpc>
6. YANG Data Tree
module: ietf-te-kpi-telemetry
augment /te:te/te:tunnels/te:tunnel:
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+-rw te-scaling-intent
| +-rw scale-in-intent
| | +-rw threshold-time? uint32
| | +-rw cooldown-time? uint32
| | +-rw scale-in-operation-type? scaling-criteria-operation
| | +-rw scaling-condition* [performance-type]
| | +-rw performance-type identityref
| | +-rw threshold-value? string
| | +-rw te-telemetry-tunnel-ref? -> /te:te/tunnels/tunnel/name
| +-rw scale-out-intent
| +-rw threshold-time? uint32
| +-rw cooldown-time? uint32
| +-rw scale-out-operation-type? scaling-criteria-operation
| +-rw scaling-condition* [performance-type]
| +-rw performance-type identityref
| +-rw threshold-value? string
| +-rw te-telemetry-tunnel-ref? -> /te:te/tunnels/tunnel/name
+-ro te-telemetry
+-ro id? string
+-ro performance-metrics-one-way
| +-ro one-way-delay? uint32
| +-ro one-way-delay-normality? te-types:performance-metrics-normality
| +-ro one-way-residual-bandwidth? rt-types:bandwidth-ieee-float32
| +-ro one-way-residual-bandwidth-normality? te-types:performance-metrics-normality
| +-ro one-way-available-bandwidth? rt-types:bandwidth-ieee-float32
| +-ro one-way-available-bandwidth-normality? te-types:performance-metrics-normality
| +-ro one-way-utilized-bandwidth? rt-types:bandwidth-ieee-float32
| +-ro one-way-utilized-bandwidth-normality? te-types:performance-metrics-normality
+-ro performance-metrics-two-way
| +-ro two-way-delay? uint32
| +-ro two-way-delay-normality? te-types:performance-metrics-normality
+-ro te-ref? -> /te:te/tunnels/tunnel/name
module: ietf-vn-kpi-telemetry
augment /vn:vn/vn:vn-list:
+--rw vn-scaling-intent
| +--rw scale-in-intent
| | +--rw threshold-time? uint32
| | +--rw cooldown-time? uint32
| | +--rw scale-in-operation-type? scaling-criteria-operation
| | +--rw scaling-condition* [performance-type]
| | +--rw performance-type identityref
| | +--rw threshold-value? string
| | +--rw te-telemetry-tunnel-ref? -> /te:te/tunnels/tunnel/name
| +--rw scale-out-intent
| +--rw threshold-time? uint32
| +--rw cooldown-time? uint32
| +--rw scale-out-operation-type? scaling-criteria-operation
| +--rw scaling-condition* [performance-type]
| +--rw performance-type identityref
| +--rw threshold-value? string
| +--rw te-telemetry-tunnel-ref? -> /te:te/tunnels/tunnel/name
+--ro vn-telemetry
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+--ro performance-metrics-one-way
| +--ro one-way-delay? uint32
| +--ro one-way-delay-normality? te-types:performance-metrics-normality
| +--ro one-way-residual-bandwidth? rt-types:bandwidth-ieee-float32
| +--ro one-way-residual-bandwidth-normality? te-types:performance-metrics-normality
| +--ro one-way-available-bandwidth? rt-types:bandwidth-ieee-float32
| +--ro one-way-available-bandwidth-normality? te-types:performance-metrics-normality
| +--ro one-way-utilized-bandwidth? rt-types:bandwidth-ieee-float32
| +--ro one-way-utilized-bandwidth-normality? te-types:performance-metrics-normality
+--ro performance-metrics-two-way
| +--ro two-way-delay? uint32
| +--ro two-way-delay-normality? te-types:performance-metrics-normality
+--ro grouping-operation? grouping-operation
augment /vn:vn/vn:vn-list/vn:vn-member-list:
+--ro vn-member-telemetry
+--ro performance-metrics-one-way
| +--ro one-way-delay? uint32
| +--ro one-way-delay-normality? te-types:performance-metrics-normality
| +--ro one-way-residual-bandwidth? rt-types:bandwidth-ieee-float32
| +--ro one-way-residual-bandwidth-normality? te-types:performance-metrics-normality
| +--ro one-way-available-bandwidth? rt-types:bandwidth-ieee-float32
| +--ro one-way-available-bandwidth-normality? te-types:performance-metrics-normality
| +--ro one-way-utilized-bandwidth? rt-types:bandwidth-ieee-float32
| +--ro one-way-utilized-bandwidth-normality? te-types:performance-metrics-normality
+--ro performance-metrics-two-way
| +--ro two-way-delay? uint32
| +--ro two-way-delay-normality? te-types:performance-metrics-normality
+--ro te-grouped-params* -> /te:te/tunnels/tunnel/te-kpi:te-telemetry/id
+--ro grouping-operation? grouping-operation
7. Yang Data Model
7.1. ietf-te-kpi-telemetry model
The YANG code is as follows:
<CODE BEGINS> file "ietf-te-kpi-telemetry@2019-04-02.yang"
module ietf-te-kpi-telemetry {
namespace "urn:ietf:params:xml:ns:yang:ietf-te-kpi-telemetry";
prefix te-tel;
import ietf-te {
prefix te;
}
import ietf-te-types {
prefix te-types;
}
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organization
"IETF Traffic Engineering Architecture and Signaling (TEAS)
Working Group";
contact
"Editor: Young Lee <leeyoung@huawei.com>
Editor: Dhruv Dhody <dhruv.ietf@gmail.com>
Editor: Ricard Vilalta <ricard.vilalta@cttc.es>
Editor: Satish Karunanithi <satish.karunanithi@gmail.com>";
description
"This module describes telemetry for teas tunnel model";
revision 2019-04-02 {
description
"Initial revision. This YANG file defines
the reusable base types for TE telemetry.";
reference "Derived from earlier versions of base YANG files";
}
identity telemetry-param-type {
description
"Base identity for telemetry param types";
}
identity one-way-delay {
base telemetry-param-type;
description
"To specify average Delay in one (forward)
direction";
}
identity two-way-delay {
base telemetry-param-type;
description
"To specify average Delay in both (forward and reverse)
directions";
}
identity one-way-delay-variation {
base telemetry-param-type;
description
"To specify average Delay Variation in one (forward) direction";
}
identity two-way-delay-variation {
base telemetry-param-type;
description
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"To specify average Delay Variation in both (forward and reverse)
directions";
}
identity utilized-bandwidth {
base telemetry-param-type;
description
"To specify utilized bandwidth over the specified source
and destination.";
}
identity utilized-percentage {
base telemetry-param-type;
description
"To specify utilization percentage of the entity
(e.g., tunnel, link, etc.)";
}
typedef scaling-criteria-operation {
type enumeration {
enum AND {
description
"AND operation";
}
enum OR {
description
"OR operation";
}
}
description
"Operations to analize list of scaling criterias";
}
grouping scaling-duration {
description
"Base scaling criteria durations";
leaf threshold-time {
type uint32;
units "seconds";
description
"The duration for which the criteria must hold true";
}
leaf cooldown-time {
type uint32;
units "seconds";
description
"The duration after a scaling-in/scaling-out action has been
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triggered, for which there will be no further operation";
}
}
grouping scaling-criteria {
description
"Grouping for scaling criteria";
leaf performance-type {
type identityref {
base telemetry-param-type;
}
description
"Reference to the tunnel level telemetry type";
}
leaf threshold-value {
type string;
description
"Scaling threshold for the telemetry parameter type";
}
leaf te-telemetry-tunnel-ref {
type leafref {
path "/te:te/te:tunnels/te:tunnel/te:name";
}
description
"Reference to tunnel";
}
}
grouping scaling-in-intent {
description
"Basic scaling in intent";
uses scaling-duration;
leaf scale-in-operation-type {
type scaling-criteria-operation;
default "AND";
description
"Operation to be applied to check between
scaling criterias to check if the scale in
threshold condition has been met.
Defaults to AND";
}
list scaling-condition {
key "performance-type";
description
"Scaling conditions";
uses scaling-criteria;
}
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}
grouping scaling-out-intent {
description
"Basic scaling out intent";
uses scaling-duration;
leaf scale-out-operation-type {
type scaling-criteria-operation;
default "OR";
description
"Operation to be applied to check between
scaling criterias to check if the scale out
threshold condition has been met.
Defauls to OR";
}
list scaling-condition {
key "performance-type";
description
"Scaling conditions";
uses scaling-criteria;
}
}
augment "/te:te/te:tunnels/te:tunnel" {
description
"Augmentation parameters for config scaling-criteria
TE tunnel topologies. Scale in/out criteria might be used
for network autonomics in order the controller
to react to a certain set of monitored params.";
container te-scaling-intent {
description
"scaling intent";
container scale-in-intent {
description
"scale-in";
uses scaling-in-intent;
}
container scale-out-intent {
description
"scale-out";
uses scaling-out-intent;
}
}
container te-telemetry {
config false;
description
"telemetry params";
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leaf id {
type string;
description
"Id of telemetry param";
}
uses te-types:performance-metrics-attributes;
leaf te-ref {
type leafref {
path "/te:te/te:tunnels/te:tunnel/te:name";
}
description
"Reference to measured te tunnel";
}
}
}
}
<CODE ENDS>
7.2. ietf-vn-kpi-telemetry model
The YANG code is as follows:
<CODE BEGINS> file "ietf-vn-kpi-telemetry@2019-03-27.yang"
module ietf-vn-kpi-telemetry {
namespace "urn:ietf:params:xml:ns:yang:ietf-vn-kpi-telemetry";
prefix actn-tel;
import ietf-vn {
prefix vn;
}
import ietf-te {
prefix te;
}
import ietf-te-types {
prefix te-types;
}
import ietf-te-kpi-telemetry {
prefix te-kpi;
}
organization
"IETF Traffic Engineering Architecture and Signaling (TEAS)
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Working Group";
contact
"Editor: Young Lee <leeyoung@huawei.com>
Editor: Dhruv Dhody <dhruv.ietf@gmail.com>
Editor: Ricard Vilalta <ricard.vilalta@cttc.es>
Editor: Satish Karunanithi <satish.karunanithi@gmail.com>";
description
"This module describes telemetry for actn vn model";
revision 2019-03-27 {
description
"Initial revision. This YANG file defines
the ACTN VN telemetry.";
reference "Derived from earlier versions of base YANG files";
}
typedef grouping-operation {
type enumeration {
enum MINIMUM {
description
"Select the minimum param";
}
enum MAXIMUM {
description
"Select the maximum param";
}
enum MEAN {
description
"Select the MEAN of the params";
}
enum STD_DEV {
description
"Select the standard deviation of the
monitored params";
}
enum AND {
description
"Select the AND of the params";
}
enum OR {
description
"Select the OR of the params";
}
}
description
"Operations to analize list of monitored params";
}
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grouping vn-telemetry-param {
description
"augment of te-kpi:telemetry-param for VN specific params";
leaf-list te-grouped-params {
type leafref {
path "/te:te/te:tunnels/te:tunnel/te-kpi:te-telemetry/te-kpi:id";
}
description
"Allows the definition of a vn-telemetry param
as a grouping of underlying TE params";
}
leaf grouping-operation {
type grouping-operation;
description
"describes the operation to apply to
te-grouped-params";
}
}
augment "/vn:vn/vn:vn-list" {
description
"Augmentation parameters for state TE VN topologies.";
container vn-scaling-intent {
description
"scaling intent";
container scale-in-intent {
description
"VN scale-in";
uses te-kpi:scaling-in-intent;
}
container scale-out-intent {
description
"VN scale-out";
uses te-kpi:scaling-out-intent;
}
}
container vn-telemetry {
config false;
description
"VN telemetry params";
uses te-types:performance-metrics-attributes;
leaf grouping-operation {
type grouping-operation;
description
"describes the operation to apply to the VN-members";
}
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}
}
augment "/vn:vn/vn:vn-list/vn:vn-member-list" {
description
"Augmentation parameters for state TE vn member topologies.";
container vn-member-telemetry {
config false;
description
"VN member telemetry params";
uses te-types:performance-metrics-attributes;
uses vn-telemetry-param;
}
}
}
<CODE ENDS>
8. Security Considerations
The configuration, state, and action data defined in this document
are designed to be accessed via a management protocol with a secure
transport layer, such as NETCONF [RFC6241]. The NETCONF access
control model [RFC8341] provides the means to restrict access for
particular NETCONF users to a preconfigured subset of all available
NETCONF protocol operations and content.
A number of configuration data nodes defined in this document are
writable/deletable (i.e., "config true") These data nodes may be
considered sensitive or vulnerable in some network environments.
9. IANA Considerations
This document registers the following namespace URIs in the IETF XML
registry [RFC3688]:
--------------------------------------------------------------------
URI: urn:ietf:params:xml:ns:yang:ietf-te-kpi-telemetry
Registrant Contact: The IESG.
XML: N/A, the requested URI is an XML namespace.
--------------------------------------------------------------------
--------------------------------------------------------------------
URI: urn:ietf:params:xml:ns:yang:ietf-kpi-telemetry
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Registrant Contact: The IESG.
XML: N/A, the requested URI is an XML namespace.
--------------------------------------------------------------------
This document registers the following YANG modules in the YANG
Module.
Names registry [RFC7950]:
--------------------------------------------------------------------
name: ietf-te-kpi-telemetry
namespace: urn:ietf:params:xml:ns:yang:ietf-te-kpi-telemetry
reference: RFC XXXX (TDB)
--------------------------------------------------------------------
--------------------------------------------------------------------
name: ietf-vn-kpi-telemetry
namespace: urn:ietf:params:xml:ns:yang:ietf-vn-kpi-telemetry
reference: RFC XXXX (TDB)
--------------------------------------------------------------------
10. Acknowledgements
We thank Rakesh Gandhi, Tarek Saad and Igor Bryskin for useful
discussions and their suggestions for this work.
11. References
11.1. Informative References
[RFC3688] M. Mealling, "The IETF XML Registry", RFC 3688, January
2004.
[RFC7950] M. Bjorklund, Ed., "The YANG 1.1 Data Modeling Language",
August 2016.
[RFC6020] M. Bjorklund, Ed., "YANG - A Data Modeling Language for
the Network Configuration Protocol (NETCONF)", RFC 6020,
October 2010.
[RFC8199] D. Bogdanovic, B. Claise, and C. Moberg, "YANG Module
Classification", RFC 8199, July 2017.
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[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241.
[RFC8294] X. Liu, et al, "Routing Area Common YANG Data Types", RFC
8294, December 2017.
[RFC7926] A. Farrel (Ed.), "Problem Statement and Architecture for
Information Exchange between Interconnected Traffic-
Engineered Networks", RFC 7926, July 2016.
[RFC8309] Q. Wu, W. Cheng, and A. Farrel. "Service Models
Explained", RFC 8309, January 2018.
[RFC8340] M. Bjorklund and L. Berger (Editors), "YANG Tree
Diagrams", RFC 8340, March 2018.
[YANG-PUSH] A. Clemm, et al, "Subscription to YANG Datastores",
draft-ietf-netconf-yang-push, work in progress.
[Event-Notification] E. Voit, et al, "Subscription to YANG
Datastores", draft-ietf-netconf-yang-push, work in
progress.
[PERF] Y. XU, et al., "Use Cases and Requirements of Dynamic Service
Control based on Performance Monitoring in ACTN
Architecture", draft-xu-actn-perf-dynamic-service-control,
work in progress.
[RFC8341] A. Bierman, M. Bjorklund, "Network Configuration Access
Control Model", RFC 8341, March 2018.
[RFC8453] D. Ceccarelli and Y. Lee (Editors), "Framework for
Abstraction and Control of Traffic Engineered Networks",
RFC 8453, August 2018.
11.2. Normative References
[TE-Tunnel] T. Saad (Editor), "A YANG Data Model for Traffic
Engineering Tunnels and Interfaces", draft-ietf-teas-yang-
te, work in progress.
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[TE-Types] T. Saad, et.al, "Traffic Engineering Common YANG Types",
draft-ietf-teas-yang-te-types, work in progress.
[VN] Y. Lee (Editor), "A Yang Data Model for ACTN VN Operation",
draft-lee-teas-actn-vn-yang, work in progress.
[RFC8233] D. Dhody, et al., "Extensions to the Path Computation
Element Communication Protocol (PCEP) to compute service
aware Label Switched Path (LSP)", RFC 8233, September
2017.
12. Contributors
Authors' Addresses
Young Lee (Editor)
Huawei Technologies
5340 Legacy Drive Suite 173
Plano, TX 75024, USA
Email: leeyoung@huawei.com
Dhruv Dhody
Huawei Technology
Leela Palace
Bangalore, Karnataka 560008
India
Email: dhruv.dhody@huawei.com
Satish Karunanithi
Huawei Technology
Leela Palace
Bangalore, Karnataka 560008
India
Email: satish.karunanithi@gmail.com
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Ricard Vilalta
Centre Tecnologic de Telecomunicacions de Catalunya (CTTC/CERCA)
Av. Carl Friedrich Gauss 7
08860 - Castelldefels
Barcelona (Spain)
Email: ricard.vilalta@cttc.es
Daniel King
Lancaster University
Email: d.king@lancaster.ac.uk
Daniele Ceccarelli
Ericsson
Torshamnsgatan,48
Stockholm, Sweden
Email: daniele.ceccarelli@ericsson.com
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