mind the gap: from service intent to service instance(s) sir... · 2019. 9. 12. · •traffic...

1Copyright © Ciena Corporation 2019. All rights reserved. Confidential & Proprietary.

Mind the Gap: From Service Intent to Service Instance(s)

Raghu Ranganathan(Office of CTO)

August 2019

Acknowledgements:Cengiz Alaettinoglu


About us

1,500+ customers across

North America, CALA, EMEA and APAC

85% of the world’s largest

service providers being served

6,000+employees

in 35+ countries

We enable you to deliver rewarding experiences for your end-users and drive better outcomes for your organization through the creation and deployment of the Adaptive Network™

We’re a networking systems, services, and software company


Ciena Adaptive Network Architecture Framework


Networks @Scale


Challenge #1: Functional Complexity

Time

Intrinsic SystemComplexity

Com

plex

ity

Extreme Service & Traffic Variances

CONNECTING PEOPLE

CONNECTING PLACES

CONNECTING MACHINES/THINGS

CONNECTING VIRTUAL MACHINES


Challenge #2: Multi-Layer/Domain Operational Complexity

Time


OperationalComplexity

Com

plex

ity

Example: 10x parameters to configure in 5G-NR PHY vs LTE Radio

Service Intent à Multi-Layer/Domain Intents↙ ↓ ↘


Intent-based controlTo meet business objectives

Greater automationTo increase service velocity and decrease errors

Self-optimizationIncrease responsiveness and meet exponential demand

Operators Are Looking for a Way to Thrive, Not Just SurviveThere must be a better way


Can Networking Be That Easy?“Alexa, connect me to AWS EU-West-1.”

UNI ENNI UNI

Cloud Tenant

AT&T EU-West-1

Bus. Apps

Service Orchestration

Bus. Apps


Cloud Orchestration

(Lab) (Production Network) (Production Network)

https://www.ciena.com/insights/articles/Can-networking-be-that-easy-Whats-possible-with-MEF-30-orchestration-and-great-teamwork.html

(Service Provider)(Access Provider) (Public Cloud Provider)(Enterprise)

Service Intent Service Intent

Network Intent

Network Intent

https://www.ciena.com/insights/articles/Can-networking-be-that-easy-Whats-possible-with-MEF-30-orchestration-and-great-teamwork.html


Service Provider Objective: Intent-Based Networking

Why?• OpEx savings: Less time resolving issues and optimizing the network• CapEx savings: More efficient use of the infrastructure

Operational Area Example of Intent: What ..not HowService provisioning and assurance John gets gold serviceTraffic engineering, traffic distribution, caching Run my network uncongestedPolicy engine and optimization Resolve congestion and failuresPredictive Maintenance Protect critical services before failures happen


The Problem with Networks – Abstractions & Composability

• Compute, Storage and Networking have different Models• Networks are opaque to the application• Networks cannot be composed on demand

• Networks can be notoriously hard to operate• Incomplete behavior model when components, e.g., protocols, interact• Manual intervention is often needed to coordinate actions

• Networks are slow to advance• Monolithic designs – eg., Routing algorithms change very slowly (tightly integrated)• Network management/control developed separately for each system/vendor


Intent Abstractions

One Architecture Pattern?


What is Intent?

• Want: [some] service• gold service • Uncongested & 100% Available • …..

• Intent can be at business, service, network, device, and resource levels…

• What is gold service? What is congestion?• AI has a role in intent based networking, but

this is not it• Need technology specific compilers, i.e.,

templates, policies, telemetry/analytics, AI/ML, and algorithms

• Prescriptive Intent, e.g., MEF Service Model


Service Intent [Prescriptive]

Open APIs

Attributes -UNIs

Attributes -EVC/EVC EPs

Business Policies

LowDelay EVP-LAN Service

Data Center Access (DCA) Product

Interface to Network

Automation SW


D2 D3D1

Service Intent à Network Intent - Packet Optical

• Intent - Challenges• Multi-domain• Network is Multi-Layer• Green vs Brownfield

• Example – 2 Service types• Different Models• Both about “forwarding”

• Example – 4 Domains• Different Device Models• Each w/ similar “functions”

D1- Packet Optical Controller

D3 - Legacy NMS

D2- Packet Optical Controller

Orchestratorapps

D4- IP Controller

D4IP-VPN Service

EVP-LAN Service


Service Intent à Network Intent - 5G Networks

CO/PoP Data Center

UE

UPF

Business ApplicationsOpen APIs

Open APIs

Service Provider

[Slice] Service Intent

UPF

UPF(R)AN(R)AN

DNDN

DN(R)AN

AMF

AUSF

UDM

PCF

SMF


[Slice] Resources - distributed

RAN-C Transport-C 5GCore-C

[Slice] Resources - centralized


Service Intent à Network Intent across Multiple Operators

Single Operator/Multi-Domain Multiple Operator Domains

SRV 2

SRV 1

Host 1

SRV 2

SRV 1

Host 1

Service Provider

Bus. Apps

(E2E Slice)Service

Orchestration

AccessOverlay/Underlay

Controller(s)

CoreOverlay/Underlay

Controller(s)

Service Provider

Bus. Apps

(E2E Slice)Service

Orchestration

Partner Provider

Bus. Apps

(Slice-subnet) Service

Orchestration

Slice Product Order

Slice Service Control

Slice Product Order

Slice Service Control

Hosted APP(Edge DC)

Hosted APP(Core DC)

Hosted APP(Edge DC)

Hosted APP(Core DC)

Overlay/Underlay Controller(s)

Overlay/Underlay Controller(s)


Network Intent - Architecture Pattern

Connectivity Abstraction in Management Model

..with Technology specific constraints/policies

Logical Point

Optical

VxLAN/GRE/…etc

Logical Point

EVPN/SR Tunnels

Apps/Processes(VMs/Containers)

Forwarding Domain (FD)

Domain Domain

Node

Domain

Multi-Domain

Recursive AbstractionComponent-System Pattern

https://www.opennetworking.org/software-defined-standards/models-apis/

https://www.opennetworking.org/software-defined-standards/models-apis/


Network Intent – Example Policy

75%


Network Intent à Config….But…?

IP Network A IP Network B

at least 3 redundant paths

Avoid any single points of failure

Example - Design

Example: Maintenance Upgrade of Node

But, Node crashed/re-boot

Failure à Black hole of traffic…for all paths

à Incomplete Model of IGP <> BGP interactions?

Example - Observed


Intent à Instances

Closed-Loop


Abstractions + Intelligence



Com

plex

ity

Can Intelligence bend the complexity curve?

Incomplete Models of Complex System Behaviors

Time


Closed-Loop [Programmable] Networks

Self-Optimization(Closed Loop)

Controller

Infrastructure

Intelligence

Intent-based Control

Telemetry

Automation (Domain à Device/Function)


[Model-Driven] Closed-Loop [Programmable] Networks

Service Models/PoliciesIntent-based Control

OAM Models/PoliciesTelemetry

Self-Optimization(Closed Loop)

Multi-Domain/Technology Models/PoliciesAutomation (Domain à Device/Function)

Controller

Infrastructure

Intelligence

Service Provider

Packet-Optical

NFV Infra

VNF


[Model-Driven] Closed-Loop [Programmable & Federated] Networks

Service Models/PoliciesIntent-based Control

Multiple Loops(Time & Space)

Controller

Infrastructure

Intelligence

OAM Models/PoliciesTelemetry

Service ProviderPartnerProvider

Packet-Optical

NFV Infra

VNFPartnerProvider

Multi-Domain/Technology Models/PoliciesAutomation (Domain à Device/Function)


SDN Traffic Engineering App

TopologiesReal-time physical or virtualLink delay/loss/jitterBaselinesAnomaliesAlerts

Traffic MatricesService awarePeak or current traffic levelsFull-mesh or tactical

Network PoliciesUnder-/over-provisionOptimization criteriaResiliency requirementsEtc.

Policies

PHYSICAL & VIRTUALROUTERS, SWITCHES &NETWORK FUNCTIONS

Closed loop: analytics & intent-based recommendations, provisioning, monitoring

TE RecommendationsAdd, delete, merge,

split tunnels

ProgrammingSDN controllersOrchestrators


On-Demand Multi-Layer Traffic EngineeringIntent Example: Build a gold service with guaranteed physical path diversity

• Traffic engineering at the SR layer• LSP rerouting is faster than optical – in sub-seconds • Optimization algorithm must work in seconds also, not hours

• Optimizing at the SR layer alone insufficient• Especially with fiber cuts

• Optical network can help• Capacity of some optical paths can be adjusted

• Flex-Ethernet, liquid-spectrum, partial restoration • New optical transport paths can be signaled


Compute Paths that Meet Intent


Multi-Layer Telemetry and Automation

No visible issues at the IP layer, but optical link failure is imminent!


Machine Learning for Link Failure Detection and Prediction

• Receive power levels are highly correlated to link failures

• Anomaly detection• Kernel density estimation

• Anomaly prediction• Trending

• Deep learning provides better accuracy

• Trouble tickets provides past service impacting outages

• Few shots learning DNN• 95% Accuracy


Yes, Networking Can Be That Easy!



Com

plex

ity

Intelligence

Time

Example: More complex Smart Phones

….but, Intelligence makes operations simpler/better


Concluding Remarks

• With 5G, network complexity is expected to grow 5 to 10 folds• It will be a challenge to operate such a network

• The new workloads will also be much more dynamic and will require orchestration• Radio, front-haul, mid/back-haul, MEC, edge-cloud, VNFs and CNFs, network slicing, …

• Intent-based automation will empower Service Providers to stay ahead of the game• Service provisioning and assurance• Multi-layer network operation and assurance

• But, mind the [Service, Network, AI Model] gaps

mind the gap: from service intent to service instance(s) sir... · 2019. 9. 12. · •traffic...

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