Cisco Global Cloud Index 2015 · PDF fileCisco Global Cloud Index 2015–2020. Cisco Knowledge Network ... Global Cloud Workloads Surpass Traditional Workloads 92% of All Workloads

November 2016

Cisco Global Cloud Index2015–2020Cisco Knowledge Network (CKN) Session

Thomas Barnett, Jr. – Director, SP Industry Forecasts and Trends

Shruti Jain – Senior AnalystArielle Sumits – Senior Analyst

Usha Andra – Senior AnalystTaru Khurana – Senior Analyst

Cisco VNI and Global Cloud IndexVisual Networking Index (VNI)

+ = 2.3 ZBs

Non-Data Center TrafficNOT included in GCI

Data Center-to-User TrafficThis is the overlap between VNI and GCI

Data Center-to-User Traffic (14%)This is the overlap between VNI and GCI

Data Center-to-Data Center Traffic (9%)

+ = 15.3 ZBs+

Within Data Center (77%)

Traffic that flows from data center to data center

Traffic that remains within the data center

Global Cloud Index (GCI)

A0.1 ZBs

B2.2 ZBs

C1.4 ZBs

D11.7 ZBs

A B

A

B

B C D

B

C

D

GCI Forecast Update, 2015–2020 Top 7 Data Center / Cloud Trends

Growth of Global Data Center Relevance and Traffic1

2 Continued Global Data Center / Cloud Virtualization

3 Cloud Service Delivery Models (IaaS, PaaS, SaaS)

4

Global Data Center and Cloud Storage **New 5

Global Digitization—Impact of IoE6

Global Cloud Readiness7

Workloads and Traffic by Application**New

Data Center Growth

259297

346399

447485

0%5%10%15%20%25%30%35%40%45%50%

0

100

200

300

400

500

600

2015 2016 2017 2018 2019 2020

13% CAGR 2015–2020

Hyperscale Data

Centers

% Share of Data Center Servers (Installed

Base)

Source: Cisco Global Cloud Index, 2015–2020, Synergy Research Group

Back to Index

Hyperscale in 2020

Today:

21%

39%

49%

34%

of all data center servers

By 2020, Hyperscale Data Centers Will House:

47%

of all data center processing power68%

of all data stored in data centers57%

of all data center traffic53%

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Regional Growth of Data Centers

0

200

400

600

2015 2016 2017 2018 2019 2020

Middle East and Africa (0%,0.8%)Central and Eastern Europe (0.4%,1.4%)Latin America (3.9%,4.5%)Western Europe (16%,17%)Asia Pacific (29%,33%)North America (51%,43%)

13% CAGR 2015–2020

Note: Percentages within parentheses refer to relative share for 2015 and 2020. Source: Cisco Global Cloud Index, 2015–2020, Synergy Research Group

Hyperscale Data

Centers

Back to Index

Hyperscale Cloud Data CentersLocation by Country—Q2, 2016

Source: Cisco Global Cloud Index, 2015–2020, Synergy Research Group

Other, 7%Hong Kong, 2%

Netherlands, 2%Brazil, 3%

Ireland, 3%UK, 3%

India, 3%Canada, 4%

Germany, 4%

Singapore, 4%

Australia, 5%Japan, 7%

China, 7%

US, 47%

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4.76.5

8.610.8

12.915.3

02468

1012141618

2015 2016 2017 2018 2019 2020

Global Data Center Traffic GrowthData Center Traffic More Than Triples from 2015 to 2020

Zettabytes per Year

27% CAGR 2015–2020

Source: Cisco Global Cloud Index, 2015–2020

Back to Index

2.23.0

4.15.1

6.07.1

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

2015 2016 2017 2018 2019 2020

NA Data Center Traffic GrowthData Center Traffic More Than Triples from 2015 to 2020

Zettabytes per Year

27% CAGR 2015–2020


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Global Data Center Traffic by RegionNorth America to Have Highest Traffic Volume by 2020MEA to Experience Highest Traffic Growth

North America2015: 2.2 Zettabytes2020: 7.1 Zettabytes

CAGR 27%

Latin America2015: 195 Exabytes2020: 533 Exabytes

CAGR 22%

Western Europe2015: 843 Exabytes2020: 2.7 Zettabytes

CAGR 26%

Middle East & Africa2015: 105 Exabytes2020: 451 Exabytes

CAGR 34%

Central & Eastern Europe2015: 191 Exabytes2020: 632 Exabytes

CAGR 27%

Asia Pacific2015: 1.2 Zettabytes2020: 4.0 Zettabytes

CAGR 27%


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Global Data Center Traffic by Destination, 2020Most Data Center Events/Content Stays Within the Data Center

A

B

C

Data Center to User

14% Within Data Center

77%Data Center

to Data Center

9%

Storage, production and development data, authentication


Data Center to Data Center (9%)

Data Center to User (14%)

Replication, CDN, intercloud links

Web, email, internal VoD, WebEx…

Total East-West Traffic Is 86%(Rack-local traffic would add another slice

twice the size of “Within Data Center”)Back to Index

NA Data Center Traffic by Destination, 2020Most Data Center Events/Content Stays Within the Data Center

A

B

C

Data Center to User

9% Within Data Center

81%Data Center

to Data Center

10%

Storage, production and development data, authentication


Data Center to Data Center (10%)

Data Center to User (9%)

Replication, CDN, intercloud links

Web, email, internal VoD, WebEx…

Total East-West Traffic Is 91%(Rack-local traffic would add another slice

twice the size of “Within Data Center”)Back to Index

SDN/NFV Traffic GrowthSDN/NFV To Carry 44% of “Within Data Center Traffic” by 2020

0.81.4

2.2

3.1

4.1

5.2

23%28%

33%37%

41%44%

0%5%10%15%20%25%30%35%40%45%50%

0.0

1.0

2.0

3.0

4.0

5.0

6.0

2015 2016 2017 2018 2019 2020

44% CAGR 2015–2020


Zettabytes per Year

% Share of Within

Data Center Traffic

Back to Index

Potential Impact of SDN on Traffic

Big Data. Traffic engineering supports “elephant” data flows without compromising “mouse” data flows.

Video Bitrates. SDN will allow video bitrates to increase, because SDN can seek out highest bandwidth mid-stream.

Cloud Gaming. SDN can decrease latency, allowing cloud gaming applications to decrease delay by up 10%.

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0

100

200

300

400

500

600

2015 2016 2017 2018 2019 2020

Traditional Data Center (-3% CAGR)Cloud Data Center (26% CAGR)

Global Cloud Workloads Surpass Traditional Workloads92% of All Workloads Will Be in Cloud by 2020

Installed Workloads in Millions

21% CAGR 2015–2020

92%

8%

75%

25%


Back to Index


North America2015: 57.2 Million

2020: 172.1 MillionCAGR 24.6%

Latin America2015: 5.2 Million2020: 16.2 Million

CAGR 25.5%

Western Europe2015: 27.7 Million2020: 76.3 Million

CAGR 22.5%

Middle East & Africa2015: 3.6 Million2020: 11.8 Million

CAGR 26.6%

Central & Eastern Europe2015: 4.0 Million2020: 12.2 Million

CAGR 25.1%

Asia Pacific2015: 38.3 Million

2020: 151.5 MillionCAGR 31.6%

Global Cloud Workload DistributionAsia Pacific Workloads Grow 4-Fold from 2015 to 2020North America Will Maintain Largest Share of Cloud Workloads by 2020

Back to Index

0

10

20

30

40

50

60

2015 2016 2017 2018 2019 2020

Traditional Data Center (-11% CAGR)Cloud Data Center (15% CAGR)

Global Cloud Physical Servers Surpass Traditional Physical Servers77% of All Installed Servers Will Be in Cloud by 2020

Installed Physical

Servers in Millions

4% CAGR 2015–2020

77%

23%

48%

52%


Back to Index

Average Workload Density

Global Workload DensityCloud Will Outpace Traditional Data Center by More Than 3-Fold

2.2 3.5

7.3

11.9

0

2

4

6

8

10

12

14

2015 2016 2017 2018 2019 2020

Traditional Data CenterCloud Data Center

3.4X

3.3X

Workloads per Server

Workloads per Server


Back to Index

3.95.6

7.7

9.8

11.9

14.1

0

2

4

6

8

10

12

14

16

2015 2016 2017 2018 2019 2020

Global Cloud Traffic GrowthCloud Traffic Will Grow 3.7-Fold from 2015 to 2020Cloud Accounts for 92% of Traffic by 2020 Up from 82% in 2015

Zettabytes per Year

30% CAGR 2015–2020


Back to Index

1.92.8

3.8

4.95.8

6.8

0

1

2

3

4

5

6

7

8

2015 2016 2017 2018 2019 2020

NA Cloud Traffic GrowthCloud Traffic Will Grow 3.6-Fold from 2015 to 2020Cloud Accounts for 96% of Traffic by 2020 Up from 88% in 2105

Zettabytes per Year

29% CAGR 2015–2020


Back to Index


Global Cloud Traffic by RegionNorth America to Have Highest Traffic Volume by 2020MEA to Experience Highest Traffic Growth

North America2015: 1.9 Zettabytes2020: 6.8 Zettabytes

CAGR 29%

Latin America2015: 140 Exabytes2020: 448 Exabytes

CAGR 26%

Western Europe2015: 718 Exabytes2020: 2.5 Zettabytes

CAGR 29%

Middle East & Africa2015: 69 Exabytes2020: 304 Exabytes

CAGR 34%

Central & Eastern Europe2015: 124 Exabytes2020: 485 Exabytes

CAGR 31%

Asia Pacific2015: 908 Exabytes2020: 3.5 Zettabytes

CAGR 31%

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Private vs. Public CloudHybrid Cloud is a Combination of Private and Public Clouds

Enterprise Network Service Provider Network

Private Cloud

Public Cloud

Hybrid Cloud

Cisco Cloud owned and managed by Cisco for its own employees, customers and partners.

AT&T, Verizon, Amazon AWS, Microsoft Azure, Salesforce, Google.

Back to Index

050

100150200250300350400450500

2015 2016* 2017 2018 2019 2020

Public Cloud Data Center (35% CAGR)Private Cloud Data Center (15% CAGR)

Global Private Cloud vs. Public CloudBy 2016 Public Cloud will Surpass Private Cloud

26% CAGR 2015–2020

49%

51%

68%

32%

56%

44%



Back to Index

020406080

100120140160180200

2015 2016 2017* 2018 2019 2020

Public Cloud Data Center (34% CAGR)Private Cloud Data Center (15% CAGR)

NA Private Cloud vs. Public CloudBy 2017 Public Cloud will Surpass Private Cloud

25% CAGR 2015–2020

43%

57%

61%

39%



Back to Index

55%

45%

Cloud Service ModelsSoftware as a Service

(SaaS)Platform as a Service

(PaaS)Infrastructure as a

Service (IaaS)

• Cisco WebEx• Google Apps• Salesforce

Generic:• Web• Email• Web Conferencing• Video streaming• More

• Google App Engine• Windows Azure• AWS Elastic Beanstalk

Generic:• DevOps• App deployment• Testing

• Amazon AWS• Rackspace• Google Compute Engine

Generic:• Compute as a service• Virtual desktop

infrastructure

Back to Index

050

100150200250300350400450500

2015 2016 2017 2018 2019 2020

SaaS (30% CAGR)IaaS (17% CAGR)PaaS (24% CAGR)

Global Cloud Workloads SaaS Most Popular Cloud Service Model Through 2020

26% CAGR 2015–2020

9%

65%26%

8%

74%

18%



Back to Index

020406080

100120140160180200

2015 2016 2017 2018 2019 2020

SaaS (29% CAGR)IaaS (13% CAGR)PaaS (20% CAGR)

NA Cloud Workloads SaaS Most Popular Cloud Service Model Through 2020

25% CAGR 2015–2020

10%

64%26%

8%

76%

16%



Back to Index

SaaS Example: Collaboration in the CloudOn a Typical Day

IoS80%

Android 19.6%

Windows Mobile 0.22%

Blackberry 0.09%

Mobile attendees using WebEx are 7% and growing

An Internal Analysis

~40K Meetings ~112K Hours ~150K Attendees

August 2015 to August 2016 5% Increase in video

usage in meetings

An External Analysis

Source: Cisco Tahoe Call Detail Records and Netflow dataCisco Global Cloud Index 2015-2020

Healthcare Engineering Education Banking

Daily End-User Traffic*: Daily Data Center Traffic*:

163 TB373 TB

6 TB15 TB

6 TB13 TB

127 TB290 TB

0

100

200

300

400

500

600

2015 2016 2017 2018 2019 2020

Other Consumer Apps (23% CAGR)Search (25% CAGR)Social Networking (33% CAGR)Video Streaming (32% CAGR)ERP and Other Business Apps (17% CAGR)Database/ Analytics / IoT (22% CAGR)Collaboration (18% CAGR)Compute (21% CAGR)

Global Data Center WorkloadsBusiness Application Workloads Have the Highest Share; Social Networking and Media Streaming Have the Fastest Growth

21% CAGR 2015–2020

Consumer

Business



Back to Index

0% 20% 40% 60% 80% 100%

ComputeCollaboration

Database/ Analytics / IoTERP and Other Business Apps

Video StreamingSocial Networking

SearchOther Consumer Apps

Traditional Private Cloud Public Cloud

Global Data Center Workloads—2015Private Cloud Dominates Enterprise WorkloadsPublic Cloud Dominates Consumer Workloads


Consum

erB

usiness

Back to Index

0% 20% 40% 60% 80% 100%

ComputeCollaboration

Database/ Analytics / IoTERP and Other Business Apps

Video StreamingSocial Networking

SearchOther Consumer Apps

Traditional Private Cloud Public Cloud

Global Data Center Workloads—2020Public Cloud Dominates Consumer Applications


Back to Index

Consum

erB

usiness

Data Center Traffic by Application—2020

22%

22%

10%17%

18%

12%SearchSocial NetworkingVideo StreamingBig DataWebOther

83%

13%

File SharingGamingVideo StreamingWeb/Data

Within Data Center Data Center to End User

Big Data is the fastest growing application within the data center, from 10% in 2015 to 17% in 2020Video is only 10% within the data centers but is 83% of data center to end-user Back to Index


0200400600800

1,0001,2001,4001,6001,8002,000

2015 2016 2017 2018 2019 2020

Public Cloud Data CenterPrivate Cloud Data CenterTraditional Data Center 1,405

Global Data Center Storage: Traditional vs. CloudTotal Data Center Storage Will Grow Nearly 5-fold from 2015-2020Cloud Accounts for Nearly 90% of Installed Storage by 2020

Installed Storage

Capacity in Exabytes

37% CAGR 2015–2020

45%35% 12%

70%

18%20%

1,842

1,065

782

546382


Back to Index

0200400600800

1,0001,2001,4001,6001,8002,000

2015 2016 2017 2018 2019 2020

Other Consumer Apps (33% CAGR)Search (33% CAGR)Social Networking (42% CAGR)Video Streaming (45% CAGR)ERP and Other Business Apps (29% CAGR)Database/ Analytics / IoT (37% CAGR)Collaboration (40% CAGR)Compute (37% CAGR)

Global Data Center Storage by WorkloadsEnterprise Application Workloads Have the Highest Share; Social Networking and Media Streaming Have the Fastest Growth

37% CAGR 2015–2020


Consumer

Business

Installed Storage

Capacity in Exabytes

Back to Index

171 251370

513

689

915

0100200300400500600700800900

1,000

2015 2016 2017 2018 2019 2020

Data Stored in Data CentersData Stored to Quintuple by 2020

Data Stored in Exabytes

40% CAGR 2015–2020


Back to Index

2543

73116

173

247

0

50

100

150

200

250

300

2015 2016 2017 2018 2019 2020

Big Data ForecastBig Data Volume Grows 10-FoldBig Data will Represent a Quarter of All Data in Data Center by 2020

Exabytes

58% CAGR 2015–2020


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Data Stored in Data Centers by Vertical—2015

Public Cloud/Web

Services32%

Government15%

Manufacturing9%

Healthcare8%

Transportation and Communications

6%

Energy5%

Finance5%

Basic Science5%

Education5%

Other4%

Retail3%

Media and Entertainment

3%

Data Center or Data Set Size in PB*Google Data Centers 8,000-10,000

Amazon Cloud Services 7,000-9,000

US Department of Defense 2,000-4,000

Baidu 1,000

Dropbox 500

Bank of America 170

NOAA Weather 120

Large Hadron Collider (CERN) 100

University of Pittsburgh Medical 85

European Bioinformatics Institute 75

Credit Suisse 40

Volkswagon 35

UPS 21

Source: Cisco Global Cloud Index, 2015–2020 and various public sources

* Total data stored at the end of 2015 Back to Index

Total Stored Data

Data Stored on Client Devices (PCs, Tablets, Phones, M2M…)

84% Client Devices or M2M 16% DC

Data Stored in Data Centers

2020

2015

PCs Smartphones + PhabletsTablets M2MExternal Storage Other

88% Client Devices or M2M 12% DC

The volume of all data stored will almost triple by 2020 from 1.4 ZB to 6.2 ZB.Most data is stored on client devices, but more moves to the data center over time.

2015

2020

2020Data at Rest (Stored)Data in Motion (Traffic)

981EBpermo.

1.4 ZB

6.2 ZB

52%

61%

18% 12% 8%915EB

Stored data on M2M modules grows the fastest at 68% CAGR The gap between traffic and stored reduces over the forecast period

5%5%

Back to IndexSource: Cisco Global Cloud Index, 2015–2020

1,329 1,561

1,754 1,926

2,111 2,309

0

500

1,000

1,500

2,000

2,500

2015 2016 2017 2018 2019 2020

Global Personal Cloud StorageMajority, 59%, of Residential Internet Users Will Use Cloud Storage by 2020

Consumers in Millions

12% CAGR 2015–2020

Source: Cisco Global Cloud Index, 2015–2020; Juniper Research

Back to Index

8 14

21 29

37

48

0

10

20

30

40

50

60

2015 2016 2017 2018 2019 2020

Global Personal Cloud Storage Traffic*

Exabytesper Year

42% CAGR 2015–2020

*Personal cloud storage traffic includes personal content lockers, cloud back-up, and does not include cloud DVR


Back to Index

1.12.0

3.04.2

5.6

7.2

0

1

2

3

4

5

6

7

8

2015 2016 2017 2018 2019 2020

NA Personal Cloud Storage Traffic*

Exabytesper Year

45% CAGR 2015–2020

*Personal cloud storage traffic includes personal content lockers, cloud back-up, and does not include cloud DVR


Back to Index

By 2020, 59% (2.3 Billion) of global residential Internet users will use personal cloud storage.The average monthly traffic per user will be 1.7 GB.

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Complexity of Protocol Environment

Focu

s of

D

ata

Anal

ytic

s

Loca

l Le

vel

ProblematicConsolidated

Clo

ud

Leve

lAg

greg

atio

n Le

vel

Manageable

Electricity Metering

Usage-Based

Insurance

Home Automation

Source: Cisco Global Cloud Index, 2015–2020; Machina Research

M2M Applications and Cloud ComputingDifferent levels of Data Analytics Requirements Drive Fog / Cloud

Water Metering

CCTV (Event

Detection)

Smart Grid (Electricity)

Manufacturing (Process)

Oil and Gas (Upstream)

Warehousing and Storage

Building Automation

Manufacturing (Discrete)

Transport (Air)

Venue Management

Parking Space Mgmt

Transport (Road)

Transport (Rail)

Mining Operation

Street Lighting

Healthcare (Equipment)

Transport (Sea)

Connected Car (Autonomous

Driving)

Smart Grid

(Water)

Whether data analytics is done in cloud or at the edge (fog) will be

driven primarily by time-sensitivity and complexity of data analytics

requirements.

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The Data Universe

900 Exabytes of Data in Data Centers

600 Zettabytes of Data Created Everywhere

5.2 Zettabytes of Data Stored in Devices


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What Makes a Smart City?Multiple Applications Create Big Data

Connected Factory

1 PB per day (0.2% transmitted)

Connected Plane

40 TB per day (0.1% transmitted)

Public Safety

50 PB per day (<0.1% transmitted)

Intelligent Building

275 GB per day (1% transmitted)

Smart Hospital

5 TB per day (0.1% transmitted)

Smart Car

70 GB per day (0.1% transmitted)

A city of one million

will generate 200 million gigabytes

of data per dayby 2020

Smart Grid

5 GB per day (1% transmitted)

Weather Sensors

10 MB per day (5% transmitted)


Back to Index

1521

2938

48

60

5 7 9 11 13 15

0

10

20

30

40

50

60

70

2015 2016 2017 2018 2019 2020

Useable Data Created per YearData Center Traffic per Year

Data Created vs. Data Center TrafficData Created Outpaced

Zettabytes per Year

Opportunity for Edge or Fog Computing


Back to Index

Examples of Broad Cloud AdoptionBarriers Overcome and Operational Efficiency Prevails

Netflix Closes Last DC, Completes Cloud Migration

“We rely on the cloud for all of our scalable computing and storage needs—our business logic, distributed databases and big data processing/analytics, recommendations, transcoding, and hundreds of other functions.” —Netflix Representative

Banks to Move 30% of Workloads to Cloud in 3 Years

“Pressure to cut infrastructure costs, increased flexibility, paired with security and compliance services from the cloud vendors has boosted banks’ willingness to explore the technology.” —Wall Street Journal

34.3% of Health Information Exchange is Already in the Cloud

“Healthcare organizations are increasingly willing to trust the cloud with Protected Health Information (PHI). 36.2% of patient engagement tools are in the cloud and 5.3% of the organizations leverage cloud for compute cycles to analyze big data.” —2016 HIMSS Analytics Cloud Survey

More than 50% of Workloads in the Cloud

The integrated oil company is undergoing a large scale migration to public cloud. “Pretty much anything and everything we’re setting up, they have sensors.” —Zhanna Golodryga, Hess CIOGE oil and gas migrated half of it’s core application to the cloud.

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Global Cloud Readiness Business and Consumer Apps/Network Requirements

Basic Cloud Apps Intermediate Cloud Apps Advanced Cloud Apps

Network Requirements:Download Speed: Up to 750 kbpsUpload Speed: Up to 250 kbpsLatency: Above 160 ms

Network Requirements:Download Speed: 751–2,500 kbpsUpload Speed: 251–1,000 kbpsLatency: 159–100 ms

Network Requirements:Download Speed: Higher than 2,500 kbpsUpload Speed: Higher than 1,000 kbpsLatency: Less than 100 ms

Back to Index

Regional End-User Cloud Readiness—2016Supporting Business and Consumer Applications on Fixed Networks*

In 2016, 132 countries met the advanced single application readiness criteria for fixed networks, compared to 119 countrieslast year. * Non-Concurrent Apps

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Regional End-User Cloud Readiness—2016Supporting Business and Consumer Applications on Mobile Networks*

In 2016, 89 countries met the advanced single application readiness criteria for mobile networks, compared to 81 countrieslast year. * Non-Concurrent Apps

Back to Index

Insecurity in the Internet of ThingsDyn, one of the internet's biggest DNS hit with a DDoS

145,000 devices were infiltrated, including security cameras and DVRs in homes and offices around the world.

Largest ever attack recorded, clocking in at 620 Gbps at its peak.

At its peak, equivalent to the entire Internet traffic in Chile, New Zealand, South Africa or Saudi Arabia Back to Index

58%

4%2%8%

28%

Office DocumentsPersonally identifiable informationProtected health informationConfidential dataOther

53%

50%

47%

47%

33%

SaaS

BigData

PaaS

IaaS

IoT

Sensitive Data Use by Enterprises in Cloud53% of Sensitive Data Use in the cloud on SaaS

Source: 2016 Vormetric Data Threat Report, 451 Research Group

Percentage of sensitive data stored in the cloud

Source: SkyHigh Cloud Adoption & Risk Report (2016)

Sensitive Data in the Cloud

Enabling Authentication and Secure Internet Percentage of Secure Internet Servers to All Web-Facing Servers

Western Europe51%

+1% YoY

Asia Pacific24%

+1% YoY

Central and Eastern Europe

34%+5% YoY

Latin America

14%+1% YoY

MEA12%

+2% YoY

North America28%

+1% YoY

Back to IndexSource: Cisco Global Cloud Index, 2015–2020

Cisco Global Cloud IndexWhere to Find More Information / Direct Questions

• Media Release• GCI White Paper• Cloud Readiness Report• GCI Q&A• GCI Highlights Tool• Cloud Readiness Tool

www.cisco.com/go/cloudindex

To further engage and ask questions, please join the GCI community: https://communities.cisco.com/community/solutions/sp/vni-gci

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https://communities.cisco.com/community/solutions/sp/vni-gci

Global Cloud Index Forecast MethodologyProjecting Data Center and Cloud Traffic Growth

The methodology begins with the installed base of workloads categorized by workload type and implementation and then applies the volume of bytes per workload per month to obtain the traffic for current and future years.

Detailed methodology description and specific analyst sources included in complete GCI report

Installed Base of Workloads

Bytes of Traffic per Workload

per Month

Percent Traffic Within Data Center and Data Center to

Data Center

Analyst Data Measured Data Measured Data

Evolution of Data CenterBackup?

Hardware-Defined Network

Purpose-Built AppliancesHigh AvailabilityHigh Reliability

Overprovisioned in the Core

Software-Defined Network and NFV

Traffic EngineeringDynamic Service Chaining

Rapid Provision and Service CreationScaling ServicesWorkload Mobility

High FlexibilityCustomization

Data-Defined Network

Big Data + AI + SDN/NFVPredictive Load Balancing

Intelligent Congestion Management

Cloud Definition by NIST

On Demand/ Self Service

Broad Network Access

Resource Pooling

Rapid Elasticity

Measured Service

Cloud

Back to Index

Containers and VMs—A Comparison

• Application focused • Resource efficient

• don’t need hypervisors • share a single OS

• Faster and efficient provisioning• Suited for deploying similar workloads

simultaneously at scale• Security risk from vulnerabilities in

shared OS version/ kernel• Not suited for multi-tenant environments• Can be migrated to other servers with

compatible OS kernels

• Server focused• Resource heavy

• need hypervisors to emulate the physical server hardware

• need own OS copy• Slower to provision• Vulnerabilities in particular OS versions

cannot be leveraged to compromise other VMs

• Can be migrated from one server to another with suitable hypervisor, without regard for the system’s OS

Containers and VMs Can Coexist—Complimentary Technologies

Containers Virtual Machines