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Beyond MPLS: The Network as the Cloud- Computing Delivery Platform A Light Reading Webinar Sponsored by

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Beyond MPLS: The Network as the Cloud-

Computing Delivery Platform

A Light Reading Webinar

Sponsored by

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Welcome to Today's Light Reading Webinar

Participate in the webinar: Ask questions, share

feedback via the survey, and access the Information

panel.

Personalize your experience: Click the buttons at

the bottom of your screen to open supporting content

and user tools at your own convenience.

Technical Issues: Ask the support team for live

assistance in the ask-a-question window.

Enjoy the webinar and thank you for viewing!

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Today’s Presenters

Mitchell H. Auster Senior Advisor

Market Development

Ciena

Sarah Wallace Analyst

Heavy Reading

David White Senior VP Global

Business Development

Ipanema Technologies

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About This Webinar

This webinar is intended for Carriers, Network Service Providers

and Network Managers who are considering offering cloud services

as part of their revenue stream. This webinar will discuss:

Why service providers are unique in offering cloud services

What challenges may come in preparing their networks to offer

cloud-based services

How cloud computing increases the complexity of enterprise

WANs

How MPLS is a 15-year old technology and under threat of

revenue erosion from enterprise IT transformations and a

commoditization of MPLS services

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solutions?

Why Cloud

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The Appeal of Cloud Services

• Reduction of cost

- Operations

- Maintenance

- Paid for incrementally

• Increased Storage

- Organizations can store

more data than on

private computer systems

• More resources and staff

- Agility

- Security

- Privacy

• Scalability

- Multi-tenant environment

- From 1,000 clients to 10,000

very quickly

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Amazon

(EC2)

New York Times

FourSquare Hootsuite Quora Reddit SCVNGR

“Cloudpocalypse” … When the cloud fails

Amazon reports trouble due to “excessive re-mirroring of its Elastic Block Storage (EBS) volumes and that a “networking event” caused a domino effect across availability zones in that region, in which many of its storage volumes created new backups of themselves.

That filled up Amazon’s available storage capacity and

prevented some sites from accessing their data.

These sites supported by Amazon‟s EC2 experienced outages, some up to 36 hours.

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solutions?

Hence: The Time is Right for Service Providers

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INFRASTRUCTURE

STORAGE

Service Providers can provide…

Service Providers are in a prime position to capitalize

on the cloud revolution because they can provide the following

compared to traditional cloud vendors:

MANAGEMENT

VALUE-ADDED VPN SERVICES

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The Challenge for Service Providers

Use the existing network infrastructure to offer value

added services

Offer new cloud services using traditional data transport

Meanwhile, delivering all these cloud services in an

environment that is:

Secure

Scalable

In real-time

Reliable

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The Key

The key for service providers who want to provide

superior cloud services will be to: Have Superior WAN Optimization and Management

Have Superior Bandwidth Management

Move Beyond Dated MPLS

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Beyond MPLS:

Optimizing the Cloud Backbone

www.ciena.com

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12 © Ciena Confidential and Proprietary

Key Messages

The ability to place and/or migrate workloads (VMs) in arbitrary data

centers improves resiliency, efficiency and application performance

Before migrating a VM, the associated data store must be reachable at

new DC

Trend to active-active data replication among 2 or more DCs

The ability to migrate a Live VM is becoming table stakes

Minimizing interruption (pause) is critical

The cloud backbone network is a critical determinant of success

Two broad requirements for the inter-DC Cloud Backbone:

Virtualization for scalable multi-tenancy

Orchestrated QoS to optimize profitability

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13 © Ciena Confidential and Proprietary

Cloud Service Driven Inter-DC Traffic

Traffic Type Quantity of

Instances

Flow Duration

per Instance

Bandwidth

per Instance

QoS

Sensitivity

Total WAN

Bandwidth

Data Storage Migration Low Short-to-Medium Very High Medium High

Live Virtual Machine Migration Low-High Short-to-Medium Medium High Medium-

Very High

Data Storage

Update/Replication

Medium Medium-to-Long Medium High Very High

Distributed vApp Inter-VM

traffic, VM mgmt (VM-VPN)

Medium Short-to-Long Low Medium Low

Tra

nsactio

nal

perm

an

en

t S

em

i-

High Peak-to-Valley pairwise DC-DC bandwidth demand, especially

driven by high-bw, short-medium duration, QoS-sensitive flows

• Disaster avoidance, DC consolidation or geographic re-location

• ~5000 VMs @ 20 GB 100 TB (~10x to move datastore) Bulk VM Migration

• Workload balancing – capacity, follow sun/moon, power cost

• ~500 VMs @ 20 GB 10 TB (~10x to move datastore) Periodic VM Migration

• Cloudbursting for capacity enhancement • ~50 VMs @ 20 GB 1 TB (~10x to move datastore)

Unplanned VM Migration

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14 © Ciena Confidential and Proprietary

0

100

200

300

400

500

600

0 0.5 1 2 3 4 5 6 10 20 50

Latency (ms)

Latency Effect on VMM Completion Time

Completion time increases with network latency

Frame loss rapidly compounds the effect of network latency

Loss %

Loss Effect on VMM Completion Time

(e.g. @ 5 msec RTT) 2500

2000

1500

1000

500

0

0 0.1 0.2 0.3 0.4 0.5 1

VM

M c

om

ple

tio

n T

ime

(s

ec

s)

Bandwidth Effect on VMM Pause Time

Client-Server Business App

Development Workload

Retail Web Server w/ 600 Users

VM

M C

om

ple

tio

n T

ime

(s

ec

s)

VM Migration Performance Effects of Latency, Loss, Bandwidth

Cloud backbone must deliver high bandwidth,

and minimize loss & latency

100

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15 © Ciena Confidential and Proprietary

General purpose IP/MPLS Core (typical 99.95% PDR)

ill-suited for certain Inter-DC traffic

High bandwidth, QoS-sensitive flows must be traffic-engineered to ~zero loss

“Real-time traffic like storage replication or live migration requires dedicated

bandwidth, meaning that an optimization solution must be able to prioritize traffic

flows, and prevent them from being pushed aside by other applications.” (Forrester)

TCP/IP flows of

equivalent CoS

Congestion High bandwidth

transactional QoS-

sensitive flows

Low bandwidth,

semi-permanent

QoS-tolerant flows

General Purpose

IP/MPLS Core

TCP is aggressively

egalitarian

each session gets the

same bandwidth 0

500

1000

1500

2000

2500

3000

3500

4000

4500

Packet Delivery Ratio (1 - Loss%)

RTT =1ms

RTT =2ms

RTT =5ms

RTT =10ms

TCP Throughput vs. PDR [RFC 5348]

TC

P t

hro

ug

hp

ut

(Mb

ps)

X

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16 © Ciena Confidential and Proprietary

Typical Constrained DC Resource Sharing

X1 = no capacity available, need to burst to provider IaaS cloud service

X2 = no capacity available at local provider DC

X3 = insufficient bandwidth/QoS to migrate live VMs/storage to distant DCs

Compute

Resource capacity

Resource used Storage

Enterprise DC

Compute Storage

Compute Storage

Provider DC 2

(Distant) Compute Storage

User

Provider DC N

(Distant)

Provider DC 1

(Local)

General Purpose IP/MPLS Core

New

workload

X1

X2

X3

X3

Underutilized resources and unmet demand

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17 © Ciena Confidential and Proprietary

Cloud Service Provider Inter-DC backbone Elastic, On-Demand, High-Performance Packet-Optical mesh

L1 or L2 Packet Transport Server Connections

L2 S

erv

ice F

low

s

DC-A

DC-B

DC-C

Point-to-Point

Static and On-

Demand

Any-to-Any CBE

CBE

shared

uplink

Common Packet-

Optical Mesh

Converged Data Center Fabric

Virtualized Workloads

VM VM VM

CBE

Extended VM-VPN (E-LAN)

Re-directed User-vApp (E-LAN)

Distributed File System (E-LAN)

VM Migration traffic (E-Line)

Storage Replication (E-Line, OTN)

Storage Migration – (E-Line) Transactional

Static/Semi-permanent

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18 © Ciena Confidential and Proprietary

Data Center Without Walls Enables global efficient workload distribution

X1 = no capacity available, need to burst to provider IaaS cloud service

X2 = no capacity available at local provider DC

= performance on-demand to migrate VMs/storage to distant DCs and provide user-to-vApp QoS

Compute Storage

Enterprise DC

Compute Storage

Compute Storage

Provider DC 2

(Distant) Compute Storage

User

Provider DC N

(Distant)

Provider DC 1

(Local)

New

workload

X1

X2

General Purpose IP/MPLS Core

Minimize capacity required; maximize resource utilization & maximize

fulfilled demand Anywhere, anytime provision of resources

Performance On-Demand

Cloud Backbone

Enterprise DC

Compute Storage

User

New

workload

Compute

Storage

Performance On-Demand

Cloud Backbone

Resource capacity

Resource used

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19 © Ciena Confidential and Proprietary

Guarantee High Performance to Increase Resource Efficiency

DC

1

DC

2

DC

3

DC

4

DC

5

DC

6

DC

7

DC

9

DC

10

DC

11

Disparate DCs/Resources Resource capacity

Resource used

Virtual DC without Walls –

shared global resource pool

DC

1

DC

2

DC

3

DC

4

DC

5

DC

6

DC

7 DC

8 DC

9

DC

10

DC

11

DC

8

Ensure high BW

and minimize

inter-DC latency

& loss

Increase radius

of candidate

DCs for Live VM

Migration

Increase shared

resource pool

utilization

Minimize

resource

requirement in

each DC

Minimize cost of

total resource

pool required

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20 © Ciena Confidential and Proprietary

… but how to address the high peak-to-valley

pairwise DC-DC bandwidth demand?

build full fixed mesh for sum of each

pairwise daily peak?

build stat-mux mesh for daily peak

sum of total forecast demands?

>95% of time

Low: Y Mbps

Cloudburst –

live VM, storage

migration

<5% of time

High: NxY Gbps

En

terp

ris

e Ia

aS

Clo

ud

Pro

vid

er

Fixed connection –

sized for peak

•Wasted bandwidth, $$$

En

terp

ris

e Ia

aS

Clo

ud

Pro

vid

er

Fixed connection –

sized for median

•Insufficient bandwidth

•Low performance, protracted cloudburst

Inter-DC Bandwidth Demand (Enterprise to Provider)

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21 © Ciena Confidential and Proprietary

Inter-DC Bandwidth Demand (Provider to Provider)

High pairwise (DCa – DCz) peak-to-valley (& mean) ToD bandwidth variation

DC

DC

DC

DC DC

Window 1 peaks

Sum = X Tbps

DC

DC

DC

DC DC

Window 2 peaks

Sum = 1.5X Tbps

DC

DC

DC

DC DC

Window 3 peaks

Sum = 2X Tbps

DC

DC

DC

DC DC

Window 4 peaks

Sum = 0.25X Tbps

How to

build?

Fixed mesh of

wavelengths/circuits,

sized for pairwise peaks?

DC

DC

DC DC

DC Severely underutilized

bandwidth for large windows

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22 © Ciena Confidential and Proprietary

Inter-DC Bandwidth Demand (Provider to Provider)

High pairwise (DCa – DCz) peak-to-valley (& mean) ToD bandwidth variation

DC

DC

DC

DC DC

Window 1 peaks

Sum = X Tbps

DC

DC

DC

DC DC

Window 2 peaks

Sum = 1.5X Tbps

DC

DC

DC

DC DC

Window 3 peaks

Sum = 2X Tbps

DC

DC

DC

DC DC

Window 4 peaks

Sum = 0.25X Tbps

How to

build?

Fixed packet access

wavelengths/circuits, sized

for DCn peak sum + pairwise

stat-mux mesh (e.g. LSPs)?

1) Stat-mux mesh CIRs

sized for pairwise peak

underutilized core

bandwidth, or

2) Stat-mux mesh CIRs

sized for pairwise mean

packet loss on

congested links

DC

DC

DC

DC DC

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23 © Ciena Confidential and Proprietary

… how to address the high peak-to-valley pairwise DC-DC

bandwidth demand? Build orchestrated Performance on

Demand for daily peak sum of actual, smoothed demands!

„Network Hypervisor‟

FC

Virtual Machine (VM)

applications

Enterprise Data Center Provider Data Center

Ethernet

FC

Ethernet

FC

SAN

SAN

Ethernet

FC

SAN

Server

SAN

Switch

SAN

Storage

SAN

Server

VPLEX

SAN

Switch

SAN

Storage

VPLEX

Control Plane

Provider “Cloud OS” Billing Systems

Network Hypervisor enables automated performance on demand

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24 © Ciena Confidential and Proprietary

Cloud Backbone Comparison – IP/MPLS vs.

Ciena’s Dynamic Converged Optical Ethernet Large Carrier Cloud Economic Analysis

53%

Less

Point-to-Point

On-Demand

Any-to-Any CBE

CBE

Common

Packet-

Optical Mesh

CBE

No

rma

lize

d N

ew

Eq

uip

me

nt

Cap

ex

to

20

15

IP/MPLS

Greenfield

IP/MPLS

Brownfield

Dynamic COE

Greenfield

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Beyond the Network…

www.ipanematech.com

Beyond the Network…

www.ipanematech.com

Beyond MPLS Optimizing Performance in the Cloud

2

5

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www.ipanematech.com

Headquartered in Paris, France

Globally, our systems support over 100,000 sites

Leading “Visionary” in Gartner WOC Magic Quadrant

Market leader for application aware network services

26

Ipanema Overview

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www.ipanematech.com

Networks move from MPLS

to hybrid MPLS + Internet

Internet applications move from

recreational to business tools

Standard applications move to SaaS

In-house applications and resources

move to IaaS/PaaS

Unified Communications and video

become critical business applications

Users access applications from

everywhere: branch, home, hotel…

27

The Cloud Changes Network Requirements

MPLS

Cloud

Internet

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www.ipanematech.com 28

Networks Must Support New and Traditional Business Applications!

Internal business applications (SAP, Oracle, homegrown…)

Financial consolidation and reporting (Oracle Hyperion, SAP Cartesis…)

SaaS collaboration (Office 365, Google Apps, LotusLive…)

Telepresence (Cisco, Polycom…)

SaaS CRM, ERP (SalesForce, Oracle On Demand…)

HighDef video delivery

(eLearning, Digital Signage…)

Unified Communications (MS Lync, Cisco UC…)

Social media as business tools (Facebook, Twitter, YouTube)

MPLS / Ethernet

Cloud Computing

Internet

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www.ipanematech.com 29

Increasing Demands on Branch Locations The New Branch Communication Hub for Global Organizations

The changing traffic matrix

Networks are moving from point to point to any-to-any

Collaborative apps have multiple flows to each branch

Hosted virtual desktops do not “require” routing from the

desktop to the data center

Tremendous demand on the access and

distribution of data to and from branch locations

Business continuity requires making real-time

decisions & adjustments to session connectivity

Dynamically manage and control competition

between critical and less-critical applications

MPLS is inadequate

Service providers own only 1-2 access points

in a meshed, cloud network

CoS cannot address multiple critical application

traffic streams

Stateless QoS will be inadequate; per destination

QoS with fairness is required

Application SLAs are required

SaaS

IaaS/PaaS

International

Branch

Domestic Branch

Private DataCenter

Ethernet

MPLS

Internet Main site HQ

Private DataCenter

Public Internet

Cloud

Computing

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www.ipanematech.com

The network is more business critical than ever

30

The Result Cloud computing shifts application delivery complexity to the network

Cloud Impact IT Network

Application

Delivery

Complexity

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www.ipanematech.com 31

The Challenge

How do you cost optimize your WAN?

Take advantage of the Internet as a business network

Get global control without deploying technology everywhere

Reduce your WAN bandwidth requirements now and plan for tomorrow

Discover applications and their resources usage

Understand the root cause of application slowdowns

Communicate clear data about application performance

How do you get full visibility over your global network?

How do you guarantee application performance?

Control private and public applications over a hybrid network

Ensure excellent application performance to your distributed workforce

Manage social media and recreational applications

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www.ipanematech.com 32

The Ipanema Autonomic Networking System (ANS

TM)

Autonomic

Global, distributed coordination between appliances guarantees performance

“Sense and Respond" dynamically adapts to traffic and network changes

Full control requires only 10-20% of sites with an appliance

Tightly coupled Application Visibility, QoS & Control, WAN Optimization and Dynamic

WAN Selection

Optimizes data transfers (CIFS...), interactive flows (Citrix...) and real-time flows

(Videoconference...)

All-in-one

Service Framework

Unified management GUI for all features

Objective based control enabling global WAN Governance

Multi-tenant platform (SALSA) that scales up to 10MM‟s users & 100K‟s sites

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www.ipanematech.com

Guaranteed performance for business critical applications based on customer specific SLAs

Complete “autonomic” application management, visibility and control across an enterprise network

based upon global user defined objectives

Dynamic traffic optimization (session-by-session) across hybrid networks; both public or private

Control and optimization with absolutely no decisions or actions required; zero demands placed upon

IT staff resources

Multitenant Central Management System that scales to very large networks and large numbers of

customer domains

The Autonomic Network System Delivers

Enterprise Branch

SaaS

Data Center Service Provider

Data Center

Enterprise Data Center

Business

VPN

Internet @

33

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www.ipanematech.com 34

Guaranteed Performance Over Any Topology

Autonomic Control Agent (ACA) Real-time Cooperation among ACA

One to Any

Tele-optimized Branch Offices

Single Data Center

Any to Any

Branch Offices

w/ inter-site traffic

Multiple Data Centers

Some to Many

Tele-optimized Branch Offices

Multiple Data Centers

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www.ipanematech.com 35

Dynamic WAN Selection Guarantees Application Performance Across Hybrid Networks

Appliances cooperate to analyze available

bandwidth and quality for each path

Automatic path selection based on

bandwidth and congestion

Flows are automatically adjusted to

guarantee performance according to

individual SLAs

Dynamically selecting the network to match

performance objectives for each application

Paths are instantly adjusted to adapt to any

change in network and traffic conditions

Significant Benefits

Use broadband links in branches

Eliminate complex policy based routing

Increased reliability with dual

operators/networks

Datacenter #1

SAP

Datacenter #2

Sharepoint

Internet MPLS

Branch Office

XaaS

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www.ipanematech.com

Complete visibility and control of

application performance

Global view of application usage and

performance across the enterprise network

Application SLAs are provisioned and

analyzed through clear KPIs (AQS, MOS)

Global application performance objectives

applicable throughout the entire network

Multi-tenant capability provides separation

between customer domains

Proven scalability, tested to 400,000+ sites

Customer web-based portal

KPIs, reports, analysis

Real time view of data

Help desk access

iPhone application

36

SALSATM

Scalable Application Level Service Architecture

Enterprise Applications

Applications Criticality

SAP

IP Telephony

Telepresence

CRM/Citrix

CIFS

Salesforce

Gmail

Sharepoint

Skype

YouTube

Top

Top

High

High

Med.

Med.

Med.

Med.

Low

Low

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www.ipanematech.com

Fast to deploy

Network Transparency

Fully transparent at Layers 2 and 3

Fully compatible with Classes of Service

Provisioning

Install plug & play appliances in a few key locations

Use pre-defined application performance objectives

Get meaningful KPIs in a few days (MOS, AQS)

Then one click to activate control and optimization

over the global network

Easy to operate

Zero day-to-day adjustments: ANS™ automatically controls application

performance across the network

Application performance objectives are automatically enforced for new sites

Set SLAs for new applications and automatically enforce them over your

global network

You need only a few minutes per month to check application SLAs thanks

to simple KPIs

37

Fast to Deploy, Easy to Operate

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www.ipanematech.com

Business Continuity

Guaranteed performance for critical business applications; now and as you

implement Cloud based solutions

Raw Performance

Improve application response times 10X or more

Bandwidth management

Delay bandwidth upgrades by 24 months

Divide by 3 the cost to transfer a Gbyte of data across the network

Service Provider Benefits

Get away from MPLS commoditization and margin erosion

Increase VPN profitability

Reduce churn and acquire new customers by selling value!

Deliver highly differentiated cloud services enabled by a Cloud-ready network

38

The Bottom Line

Have Superior WAN Optimization and Management

Have Superior Bandwidth Management

Move Beyond Dated MPLS

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Q&A Session

Mitchell H. Auster Senior Advisor

Market Development

Ciena

Sarah Wallace Analyst

Heavy Reading

David White Senior VP Global

Business Development

Ipanema Technologies

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