TEAS                                                     L. M. Contreras
Internet-Draft                                                Telefonica
Intended status: Informational                                    X. Liu
Expires: 23 April 2026                                         Alef Edge
                                                         20 October 2025


                       DC aware TE topology model
                 draft-llc-teas-dc-aware-topo-model-05

Abstract

   This document proposes the extension of the TE topology model for
   including information related to data center resource capabilities.
   For that purpose, it defines a YANG module to augment TE topologies
   with awareness of data-center computing resources.

   Although the model is designed to be compatible with TE aware
   topologies, it can also be applied to non-TE networks.

Status of This Memo

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   This Internet-Draft will expire on 23 April 2026.

Copyright Notice

   Copyright (c) 2025 IETF Trust and the persons identified as the
   document authors.  All rights reserved.










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   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents (https://trustee.ietf.org/
   license-info) in effect on the date of publication of this document.
   Please review these documents carefully, as they describe your rights
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   extracted from this document must include Revised BSD License text as
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   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Datacenter information  . . . . . . . . . . . . . . . . . . .   3
   3.  Relationship between TE and DC Resource Models  . . . . . . .   3
   4.  Model structure . . . . . . . . . . . . . . . . . . . . . . .   4
     4.1.  Cloud technology-specific models  . . . . . . . . . . . .   4
       4.1.1.  Hypervisor-based cloud solutions  . . . . . . . . . .   5
       4.1.2.  Container-based cloud solutions . . . . . . . . . . .   7
     4.2.  Integration with TE model . . . . . . . . . . . . . . . .   8
   5.  Security and operational considerations . . . . . . . . . . .   8
   6.  Informative References  . . . . . . . . . . . . . . . . . . .   8
   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   More and more service providers are deploying cloud computing
   facilities in order to host different kinds of services and
   applications.  Such facilities can be generally referred as
   Datacenter Points of Presence (DC-PoPs).  Those DCs will consist of a
   number of servers and networking elements for connecting all of them
   with the transport network.  Depending on the number of servers in
   the data center, there will be distinct capabilities in terms of
   CPUs, memory and storage available for deploying and running the
   aforementioned services.

   In such distributed and interconnected DC-PoPs, both computing and
   topological information are of interest for determining the optimal
   DC where to deploy a given service or application.

   This document proposes a DC-aware extension for the topology model.
   This model is intended to co-exist and interoperate with existing
   traffic engineering (TE) topology models (e.g. ietf-te-topology
   [RFC8795] and technology-specific augmentations).  It does not re-
   define the TE topology, but rather links cloud/DC resource entities
   to the network via attachment points / circuits, providing a bridge
   between the DC-aware model and the TE domain.




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   Although the model is designed to be compatible with TE aware
   topologies, it can also be applied to non-TE networks.  The TE-
   related leafrefs are optional and only used when integration with TE
   models is required.

2.  Datacenter information

   The relevant information for datacenter capabilities can be described
   in different ways.  One potential manner is to describe resource
   capabilities such as CPU, memory, storage, etc.  This can be done in
   terms of total, used and free capacity for each of the parameters of
   interest.  Cloud management systems allow to obtain such kind of
   information.  For instance, in the case of Kubernetes it is possible
   to retrieve information about the total and allocatable resources in
   a compute node.  Alternatively, in the case of OpenStack it is
   possible to collect information about the total resources and those
   currently in use from such total.

   Another form of populating the information is by describing those
   resource capabilities as a bundled, usually referred as quota or
   flavor.  Well known cloud computing providers like Amazon Web
   Services, Microsoft Azure or Google Cloud Platform follow such
   schema, bundling CPU, RAM and storage units as flavors.  In the case
   of Amazon Web Services the bundle is known as “instance type”, while
   in Microsoft Azure is termed “virtual machine size” and in Google
   Cloud Platform it is called “machine type”.

   Additional information to consider in both cases could refer to the
   management capabilities of the compute infrastructure, such as
   hypervisor details or virtualization technologies available.

   The recent trend of cloud-native approach for the instantiation and
   deployment of service functions has positioned Kubernetes as the de-
   facto standard to manage containerized software in data centers, but
   it is also increasingly being used by telecommunication operators to
   manage compute resources at the edge.

   Finally, all can be complemented with information related to the
   networking details for reaching the aforementioned compute
   capabilities (IP addresses, bandwidth, etc).

3.  Relationship between TE and DC Resource Models

   The modules proposed in this document define a data structure that
   allows a TE or network topology model to associate network nodes and
   links with data-center (DC) computing resources.  The intent is to
   expose the awareness of available compute capabilities within the
   network view, without embedding full compute-domain models.



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   The design follows these principles:

   *  Separation of concerns: the ietf-dc-aware-topology module provides
      references towards cloud technology-specific models such as ietf-
      openstack-info and ietf-kubernetes-info.  This helps to augment
      the model as long as the cloud-related technology evolves along
      the time.

   *  Attachment circuit abstraction [RFC9834]: Each DC reachable from
      the network is represented through one or more attachment circuits
      (ACs).  The AC serves as the conceptual interface between the TE
      node and the computing domain.  An attachment circuit may map to a
      physical port, a virtual link, or a service-level endpoint.  This
      document adopts the AC semantics defined in [RFC9834].

   *  Integration with TE topology models: The model augments TE nodes
      and termination points defined in [RFC8795] (ietf-te-topology)
      with optional containers that reference DC resources connected
      through an attachment circuit.  This allows a TE-aware
      orchestrator to take into account computing capacity, storage, or
      service location when performing path computation or placement
      decisions.

   *  Generic applicability: Although this module integrates with TE
      models, it is applicable to non-TE topologies as well.  The
      augmentation is optional and can be ignored when TE-awareness is
      not required.

4.  Model structure

   This section provides the YANG modules that describe how cloud
   resources which can be associated with nodes in a TE topology.  Three
   modules are defined:

   *  ietf-openstack-info: describes OpenStack-based systems.

   *  ietf-kubernetes-info: describes Kubernetes-based systems.

   *  ietf-dc-aware-topology: provides the augmentation of the TE
      topology model to expose attachment circuits from network nodes to
      the data center systems defined in the previous two modules.

4.1.  Cloud technology-specific models

   According to the distinct approaches for managing cloud-based
   resources different options could exist.





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4.1.1.  Hypervisor-based cloud solutions

   A model structure for hypervisor-based cloud solutions (e.g.,
   OpenStack) can be described in the following manner.















































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module: ietf-openstack-info
  +--rw dcpop
     +--rw dcpop-id?   string
     +--rw dc* [id]
        +--rw id              string
        +--rw attachment-circuit
        |  +--rw ac* [ac-id]
        |     +--rw ac-id            string
        |     +--rw node-ref?        string
        |     +--rw interface-name?  string
        |     +--rw bandwidth?       uint64
        |     +--rw status?          enumeration {up, down, degraded}
        +--rw openstack
           +--rw system
           |  +--rw system-id     string
           |  +--rw name          string
           |  +--rw region        string
           +--rw nodes
           |  +--rw node* [name]
           |     +--rw name       string
           |     +--rw cpu
           |     |  +--rw total        uint64
           |     |  +--rw allocated    uint64
           |     |  +--rw used         uint64
           |     +--rw memory
           |     |  +--rw total        uint64
           |     |  +--rw allocated    uint64
           |     |  +--rw used         uint64
           |     +--rw workloads
           |        +--rw max          uint32
           |        +--rw running      uint32
           +--rw workloads
              +--rw workload* [id]
                 +--rw id              string
                 +--rw name            string
                 +--rw project-id      string
                 +--rw cpu
                 |  +--rw allocated    uint64
                 |  +--rw limit        uint64
                 |  +--rw used         uint64
                 +--rw memory
                 |  +--rw allocated    uint64
                 |  +--rw limit        uint64
                 |  +--rw used         uint64
                 +--rw status
                    +--rw state        enumeration {active, stopped, error}
                    +--rw conditions*  string




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4.1.2.  Container-based cloud solutions

   A model structure for container-based cloud solutions (e.g.,
   Kubernetes) can be described in the following manner.

module: ietf-kubernetes-info
  +--rw dcpop
     +--rw dcpop-id?   string
     +--rw dc* [id]
        +--rw id               string
        +--rw attachment-circuit
        |  +--rw ac* [ac-id]
        |     +--rw ac-id            string
        |     +--rw node-ref?        string
        |     +--rw interface-name?  string
        |     +--rw bandwidth?       uint64
        |     +--rw status?          enumeration {up, down, degraded}
        +--rw kubernetes
           +--rw system
           |  +--rw system-id   string
           |  +--rw name        string
           |  +--rw location    string
           +--rw cluster
              +--rw cluster-id  string
              +--rw name        string
              +--rw location    string
              +--rw nodes
              |  +--rw node* [name]
              |     +--rw name      string
              |     +--rw cpu
              |     |  +--rw capacity      uint64
              |     |  +--rw allocatable   uint64
              |     |  +--rw usage         uint64
              |     +--rw memory
              |     |  +--rw capacity      uint64
              |     |  +--rw allocatable   uint64
              |     |  +--rw usage         uint64
              |     +--rw workloads
              |        +--rw max           uint32
              |        +--rw running       uint32
              +--rw workloads
                 +--rw workload* [id]
                    +--rw id              string
                    +--rw namespace       string
                    +--rw name            string
                    +--rw cpu
                    |  +--rw request      uint64
                    |  +--rw limit        uint64



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                    |  +--rw usage        uint64
                    +--rw memory
                    |  +--rw request      uint64
                    |  +--rw limit        uint64
                    |  +--rw usage        uint64
                    +--rw status
                       +--rw phase        enumeration {pending, running, failed}
                       +--rw conditions*  string

4.2.  Integration with TE model

   The following structure provides the augmentation of the TE topology
   model to indicate the attachment of compute capabilities.

module: ietf-dc-aware-topology
  augment /nw:networks/nw:network/te:te-topology/te:node:
    +--rw dc-awareness?                        // presence container
       +--rw attachment-circuit* [ac-id]
          +--rw ac-id             string
          +--rw (dc-system-ref)?
             +--:(openstack)
             |  +--rw openstack-ref?    -> /os:dcpop/os:dc/os:openstack/os:system/os:system-id
             +--:(kubernetes)
                +--rw kubernetes-ref?   -> /k8s:dcpop/k8s:dc/k8s:kubernetes/k8s:system/k8s:system-id

   The ietf-dc-aware-topology module augments the TE topology model so
   that a TE node can indicate awareness of attached data-center
   systems.  Each attachment circuit (AC) represents a logical or
   physical link between the network domain and a data center of any
   type (i.e., central cloud, edge facilities, etc).  In this way the
   network becomes aware of computing capabilities.

5.  Security and operational considerations

   The model is designed to be accessed via NETCONF [RFC6241], thus the
   security considerations for the NETCONF protocol are applicable here.

6.  Informative References

   [RFC6241]  Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
              and A. Bierman, Ed., "Network Configuration Protocol
              (NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
              <https://www.rfc-editor.org/info/rfc6241>.








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   [RFC8795]  Liu, X., Bryskin, I., Beeram, V., Saad, T., Shah, H., and
              O. Gonzalez de Dios, "YANG Data Model for Traffic
              Engineering (TE) Topologies", RFC 8795,
              DOI 10.17487/RFC8795, August 2020,
              <https://www.rfc-editor.org/info/rfc8795>.

   [RFC9834]  Boucadair, M., Ed., Roberts, R., Ed., Gonzalez de Dios,
              O., Barguil, S., and B. Wu, "YANG Data Models for Bearers
              and Attachment Circuits as a Service (ACaaS)", RFC 9834,
              DOI 10.17487/RFC9834, September 2025,
              <https://www.rfc-editor.org/info/rfc9834>.

Acknowledgements

   The work of L.M.  Contreras has been partially funded by the European
   Union under the Horizon Europe projects NEMO (NExt generation Meta
   Operating system) grant number 101070118, and CODECO (COgnitive,
   Decentralised Edge-Cloud Orchestration), grant number 101092696.

   Young Lee contributed to initial versions of this draft.

Authors' Addresses

   Luis M. Contreras
   Telefonica
   Ronda de la Comunicacion, s/n
   28050 Madrid
   Spain
   Email: luismiguel.contrerasmurillo@telefonica.com
   URI:   http://lmcontreras.com


   Xufeng Liu
   Alef Edge
   Email: xufeng.liu.ietf@gmail.com
















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