TEAS Working Group Y. Lee (Editor)
Internet Draft Dhruv Dhody
Intended Status: Standard Track Satish Karunanithi
Expires: July 11, 2019 Huawei
Ricard Vilalta
CTTC
Daniel King
Lancaster University
Daniele Ceccarelli
Ericsson
January 11, 2019
YANG models for ACTN TE Performance Monitoring Telemetry and Network
Autonomics
draft-lee-teas-actn-pm-telemetry-autonomics-10
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Abstract
Abstraction and Control of TE Networks (ACTN) refers to the set of
virtual network operations needed to operate, control and manage
large-scale multi-domain, multi-layer and multi-vendor TE networks,
so as to facilitate network programmability, automation, efficient
resource sharing.
This document provides YANG data models that describe Key
Performance Indicator (KPI) telemetry and network autonomics for TE-
tunnels and ACTN VNs.
Table of Contents
1. Introduction...................................................3
1.1. Terminology...............................................3
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....................................7
3.2. ACTN TE KPI Telemetry Model...............................7
4. Scaling Intent Illustration....................................9
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-actn-te-kpi-telemetry model.........................18
8. Security Considerations.......................................21
9. IANA Considerations...........................................21
10. Acknowledgements.............................................22
11. References...................................................22
11.1. Informative References..................................22
11.2. Normative References....................................23
12. Contributors.................................................24
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Authors' Addresses...............................................24
1. Introduction
Abstraction and Control of TE Networks (ACTN) describes a method for
operating a Traffic Engineered (TE) network (such as an MPLS-TE
network or a layer 1/0 transport network) to provide connectivity
and virtual network services for customers of the TE network
[RFC8453]. The services provided can be optimized to meet the
requirements (such as traffic patterns, quality, and reliability) of
the applications hosted by the customers. Data models are a
representation of objects that can be configured or monitored within
a system. Within the IETF, YANG [RFC6020] is the language of choice
for documenting data models, and YANG models have been produced to
allow configuration or modeling of a variety of network devices,
protocol instances, and network services. YANG data models have been
classified in [RFC8199] and [RFC8309].
[ACTN-VN] describes how customers or end to end orchestrators can
request and/or instantiate a generic virtual network service. [ACTN-
Applicability] describes a connection between IETF YANG model
classifications to ACTN interfaces. In particular, it describes the
customer service model can be mapped into the CMI (CNC-MDSC
Interface) of the ACTN architecture.
The YANG model on the ACTN CMI is known as customer service model in
[RFC8309]. [PCEP-Service-Aware] 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 service.
This document provides TE KPI Telemetry Model which provides the TE-
Tunnel level of performance monitoring model and the scaling
mechanisms. It also provides ACTN VN TE KPI Telemetry Model which
provides the VN level of the aggregated performance monitoring model
and the scaling mechanisms.
1.1. Terminology
Refer to [RFC8453], [RFC7926], and [RFC8309] for the key terms used
in this document.
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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 | [ACTN-VN] |
| actn-tel| ietf-actn-te-kpi-telemetry | {This I-D] |
+---------+------------------------------+-----------------+
Table 1: Prefixes and corresponding YANG modules
2. Use-Cases
[ACTN-PERF] describes use-cases relevant to this draft. It
introduces the dynamic creation, modification and optimization of
services based on the performance monitoring in the Abstraction and
Control of Transport Networks (ACTN) architecture. Figure 1 shows a
high-level workflows for dynamic service control based on traffic
monitoring.
Some of the key points from [ACTN-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.
. 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
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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 CMI and MPI
interfaces should be carefully considered.
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+-------------------------------------------+
| CNC +-----------------------------+ |
| | Dynamic Service Control APP | |
| +-----------------------------+ |
+-------------------------------------------+
1.Traffic| /|\4.Traffic | /|\
Monitor& | | Monitor | | 8.Traffic
Optimize | | Result 5.Service | | modify &
Policy | | modify& | | optimize
\|/ | optimize Req.\|/ | result
+------------------------------------------------+
| MDSC +-------------------------------+ |
| |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
+-------------------------------------------------------+
| PNC +----------------------+ +----------------------+ |
| | Network Provisioning | |Abstract Topology Gen.| |
| +----------------------+ +----------------------+ |
| +------------------+ +--------------------+ |
| |Network Monitoring| |Physical Topology DB| |
| +------------------+ +--------------------+ |
+-------------------------------------------------------+
Figure 1 Workflows for dynamic service control based on traffic
monitoring
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 (See Section 3.1 & 7.1 for
details).
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(ii) ACTN TE KPI Telemetry Model which provides the VN level of the
aggregated performance monitoring mechanism (See Section 3.2
& 7.2 for details).
The models include -
(i) Performance Telemetry details as measured during the last
interval, e.g., delay.
(ii) Scaling Intent based on with TE/VN could be scaled in/out (See
Section 4 for an illustration).
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
based on the performance monitoring data collected via the TE KPI
Telemetry YANG model.
+------------+ +--------------+
| TE-Tunnel | | TE KPI |
| Model |<---------| Telemetry |
+------------+ augments | Model |
+--------------+
3.2. ACTN TE KPI Telemetry Model
This module describes performance telemetry for ACTN 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
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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:
+------------------------------------------------------------+
| CNC |
| |
+------------------------------------------------------------+
1.CNC sets the | /|\ 2. MDSC gets VN Telemetry
grouping op, and | |
subscribes to the | | VN KPI TELEMETRY (VN Level)
VN level telemetry for | | VN Utilized-bw-percentage:
Delay and | | Minimum across VN Members
Utilized-bw-pecentage | | VN Delay: Maximum across VN
\|/ | Members
+------------------------------------------------------------+
| MDSC |
| |
+------------------------------------------------------------+
The ACTN VN TE-Telemetry Model augments the basic ACTN 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 ACTN VN
Telemetry YANG model.
+----------+ +--------------+
| ACTN VN | augments | ACTN |
| Model |<---------| TE-Telemetry |
+----------+ | Model |
+--------------+
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4. Scaling Intent Illustration
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
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.
For example, if the client were to set scale-out-intent (as the
above tree), it can specify the threshold-time and cooldown-time to
which the scaling intent would apply. Threshold time refers to the
duration for which the criteria must hold true. Cooldown time refers
to the duration after a scaling action has been triggered, for which
there will be no further operation.
Performance type can be any type as defined in performance-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.). Scaling condition can be set with one or more performance
types. When multiple performance types are set, then scaling-
operation-type (AND or OR) is applied to these selected performance
types and its threshold values.
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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:
. Two-way-delay threshold: 300 mileseconds
. Utilized bandwidth: 300 megabytes
By setting AND for the scale-out-operation-type, the two criteria
have to meet at the same time to trigger scale-out operation.
5. Notification
This model does not define specific notifications. To enable
notifications, the mechanism defined in [I-D.ietf-netconf-yang-push]
and [I-D.ietf-netconf-rfc5277bis] 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
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.
Tunnel1
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500
encode-xml
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.
500
6. YANG Data Tree
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
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| +-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-actn-te-kpi-telemetry
augment /vn:actn/vn:vn/vn:vn-list:
+-rw vn-scaling-intent
| +-rw scale-in-intent
| +-rw scale-out-intent
+-ro vn-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 grouping-operation? grouping-operation
augment /vn:actn/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
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| +-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:
file "ietf-te-kpi-telemetry@2019-01-11.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;
}
import ietf-routing-types {
prefix rt-types;
}
organization
"IETF Traffic Engineering Architecture and Signaling (TEAS)
Working Group";
contact
"Editor: Young Lee
Editor: Dhruv Dhody
Editor: Ricard Vilalta
Editor: Satish Karunanithi ";
description
"This module describes telemetry for teas tunnel model";
revision 2019-01-11 {
description
"Initial revision. This YANG file defines
the reusable base types for TE telemetry.";
reference "Derived from earlier versions of base YANG files";
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}
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
"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.)";
}
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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
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
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"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;
}
}
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";
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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";
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";
}
}
}
}
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7.2. ietf-actn-te-kpi-telemetry model
The YANG code is as follows:
file "ietf-actn-te-kpi-telemetry@2019-01-11.yang"
module ietf-actn-te-kpi-telemetry {
namespace "urn:ietf:params:xml:ns:yang:ietf-actn-te-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)
Working Group";
contact
"Editor: Young Lee
Editor: Dhruv Dhody
Editor: Ricard Vilalta
Editor: Satish Karunanithi ";
description
"This module describes telemetry for actn vn model";
revision 2019-01-11 {
description
"Initial revision. This YANG file defines
the ACTN VN telemetry.";
reference "Derived from earlier versions of base YANG files";
}
typedef grouping-operation {
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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";
}
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";
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}
}
augment "/vn:actn/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";
}
}
}
augment "/vn:actn/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;
}
}
}
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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 [RFC6536] 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-actn-te-kpi-telemetry
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)
--------------------------------------------------------------------
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--------------------------------------------------------------------
name: ietf-actn-te-kpi-telemetry
namespace: urn:ietf:params:xml:ns:yang:ietf-actn-te-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
[RFC4110] R. Callon and M. Suzuki, "A Framework for Layer 3
Provider-Provisioned Virtual Private Networks (PPVPNs)",
RFC 4110, July 2005.
[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.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241.
[Restconf] A. Bierman, M. Bjorklund, and K. Watsen, "RESTCONF
Protocol", draft-ietf-netconf-restconf, work in progress.
[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.
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[RFC8340] M. Bjorklund and L. Berger (Editors), "YANG Tree
Diagrams", RFC 8340, March 2018.
[RFC8342] Bjorklund, M., Schoenwaelder, J., Shafer, P., Watsen, K.,
and R. Wilton, "Network Management Datastore Architecture
(NMDA)", RFC 8342, March 2018,
11.2. Normative References
[RFC8453] D. Ceccarelli and Y. Lee (Editors), "Framework for
Abstraction and Control of Traffic Engineered Networks",
RFC 8453, August 2018.
[TE-Topology] X. Liu, et al., "YANG Data Model for TE Topologies",
draft-ietf-teas-yang-te-topo, work in progress.
[TE-Tunnel] T. Saad (Editor), "A YANG Data Model for Traffic
Engineering Tunnels and Interfaces", draft-ietf-teas-yang-
te, work in progress.
[ACTN-VN] Y. Lee (Editor), "A Yang Data Model for ACTN VN
Operation", draft-lee-teas-actn-vn-yang, work in progress.
[L3SM-YANG] S. Litkowski, L.Tomotaki, and K. Ogaki, "YANG Data Model
for L3VPN service delivery", draft-ietf-l3sm-l3vpn-
service-model, work in progress.
[PCEP-Service-Aware] D. Dhody, et al., "Extensions to the Path
Computation Element Communication Protocol (PCEP) to
compute service aware Label Switched Path (LSP)", draft-
ietf-pce-pcep-service-aware, work in progress.
[ACTN-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-
03, work in progress.
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12. Contributors
Authors' Addresses
Young Lee
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
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
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Daniele Ceccarelli
Ericsson
Torshamnsgatan,48
Stockholm, Sweden
Email: daniele.ceccarelli@ericsson.com
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