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Sea Change Series: Enterprise Data Center Bottleneck

Published: May, 2017 | Pages: 139 | Publisher: WinterGreen Research
Industry: ICT | Report Format: Electronic (PDF)

The Enterprise Data Center has become a bottleneck, it needs to be completely replaced.  Category 5 and Category 6 Ethernet cable is spread throughout the existing enterprise data centers and is too slow to handle all the digital data coming through the data center.  Cat 5 and Cat 6 Ethernet utilized by the servers to achieve data transport using that cable does not keep up with the data coming through the data center the way optical cable and optical transceivers do.  The existing servers and cable are a problem because they are too slow for modern systems.  The cable is too slow to handle all the data coming at us in the new digital age, and the associated technology that operates at Ethernet category 5 and category 6 cable speeds is too slow as well, this is why the entire set of existing enterprise data centers is a bottleneck.  

According to Susan Eustis, lead author of the team that prepared the study, “The digital data is expanding exponentially, Global IP traffic passed the zettabyte (1000 exabytes) threshold by the end of 2016 and reach 2 zettabytes per year by 2019. No company is immune from mobile traffic, apps rule the connection to the customers.  Current enterprise data centers are totally outmoded.  In other words, the current enterprise data center is, not acceptable by current standards; no longer usable; obsolete:”

Mobile data traffic is set to increase by a factor of eight between 2015 and 2020.   Growth is anticipated at 53 percent per year, faster than systems revenue or industry revenue.  

From this, any executive can deduce that the existing data center may very well be a bottleneck.  Without revenue increases commensurate with the data volume increases, the data centers need to become far more efficient than they are now.  To compete in a market where so much data moves so fast, businesses need high speed, hyperscale computing and connectivity capabilities.  The existing enterprise networks and data centers are all bottlenecks in this context.  Overall, IP traffic will grow at a compound annual growth rate (CAGR) of 22 percent from 2015 to 2020.  Monthly IP traffic will reach 25 GB per capita by 2020, up from 10 GB per capita in 2015.

The theme of this study is that the pace of data expansion creates the need for more modern means of managing data.  There are some companies that are doing a better job, better than others of adapting to IT infrastructure to the wild influx of data.

The four superstar companies that are able to leverage IT to achieve growth, Microsoft, Google, Facebook, and the leader AWS all use Clos architecture.  What is significant is that systems have to hit a certain scale before Clos networks work   Clos networks are what work now for flexibility and supporting innovation in an affordable manner.  There is no dipping your toe in to try the system to see if it will work, it will not and then the IT says, “We tried that, we failed,” but what the executive needs to understand is that scale matters.  A little mega data center does not exist.  Only scale works.  

Business leaders are challenged to move their enterprises to the next level of competition.  Data security is always an issue.  An effective digital business player, transformer, and disruptor position depends on the effectiveness of employing digital technologies and leveraging connected digital systems.  Organizational, operational, and business model innovation are needed to create ways of operating and growing the business using mega data center cloud technologies, systems are evolving.  It is a journey to achieve the connected enterprise, ultimately connecting all employees and a trillion connected devices.

Many companies are using digital technology to create market disruption.  Amazon, Uber, Google, IBM, and Microsoft represent companies using effective strategic positioning that protects the security of the data.  As entire industries shift to the digital world, once buoyant companies are threatened with disappearing.  A digital transformation represents an approach that enables organizations to drive changes in their business models and ecosystems leveraging cloud computing, and not just hyperscale systems but leveraging mega data centers.  Just as robots make work more automated, so also cloud based communications systems implement the IoT digital connectivity transformation.  

WinterGreen Research is an independent research organization funded by the sale of market research studies all over the world and by the implementation of ROI models that are used to calculate the total cost of ownership of equipment, services, and software.  The company has 35 distributors worldwide, including Global Information Info Shop, Market Research.com, Research and Markets, electronics.ca, and Thompson Financial.  It conducts its business with integrity.  

The increasingly global nature of science, technology and engineering is a reflection of the implementation of the globally integrated enterprise.  Customers trust wintergreen research to work alongside them to ensure the success of the participation in a particular market segment.

WinterGreen Research supports various market segment programs; provides trusted technical services to the marketing departments.  It carries out accurate market share and forecast analysis services for a range of commercial and government customers globally.  These are all vital market research support solutions requiring trust and integrity.

Companies Profiled 

Market Leaders
•	Amazon 
•	Microsoft 
•	Google 
•	Facebook

Key Topics

•	Scale In The Mega Data Center 
•	Realign IT Cost Structure 
•	Mega Datacenter Physical Infrastructure 
•	Automation of Mega Data Center 
•	Networking Fabric 
•	Exchange Of Data Between Servers 
•	Complex Automation Of Process 
•	Applications Customized For Each User 
•	Machine-To-Machine Management of Traffic Growth 
•	Fabric Network Topology 
•	Building-Wide Connectivity 
•	Highly Modular Data Cebter Design 
•	Scale Capacity 
•	Back-End Service Tiers 
•	Applications Scaling 
•	Mega Data Center Network 
•	Fabric Next-Generation Data Center Network Design 
•	Pod Unit of Network 
•	Mega Data Center Server Pods 
•	Non-Blocking Network Architecture 
•	Data Center Auto Discovery 
•	Large-Scale Network 
•	Rapid Deployment Architecture 
•	Expedites Provisioning And Changes 
•	Programmable Access To Network Stack 
•	Software Defined Networking (SDN)-Supports Scale and Automation 
•	Compute Engine Load Balancing 
•	Load Balanced Requests Architecture 
•	Scale-Out: Server And Storage Expansion 
•	Switches and Routers Deployed in Fabrics 
•	Mega Data Center Multipathing 
•	Routing Destinations 
•	Clos Topology Network 
•	Capacity Scalability 
•	Aggregation Switches 
•	Intelligent Cloud Platform 
•	Linux For Azure
 Table of Contents

Sea Change Series: Enterprise Data Center as a Bottleneck
Executive Summary 3
Bottlenecks: Navigating Enterprise Data Center Replacement Is Tricky -- Potentially Dangerous for the Company Well Being 5
Viewed From The Cockpit: The Converging And Diverging Channels Can Look Like A Random Scattering Of Reds And Greens 6
Using the Red and Green Buoys to Navigate 7
Nine-Foot Bay Of Fundy Tide 10
Video and Data Streams Create Bottlenecks: 11
Demand for New Types of Cloud 11
The Right Type of Cloud: Mega Data Centers, Cloud 2.0 12
Table of Contents 13
Mega Data Center Scale and Automation 22
Only Way To Realign Data Center Cost Structure Is To Automate Infrastructure
Management And Orchestration 23
Entire Warehouse Building As A Single System 24
Half a Trillion Dollars 25
Two Tier Architecture to Achieve Simplicity 26
Bandwidth and Data Storage Demands Create Need For
Application Integration 27
Cultural Shift 28
Line of Business Loses Control Of Hardware Servers 29
Cultural Change Needed to Move to Cloud 31
Adjusting to Rapid Change 32
Amazon Web Services (AWS) Fully Automatic, Self-Healing, Networked Mega
Systems Inside A Building. 33
Data Center Design Innovation 34
Shift To An All-Digital Business Environment 35
System Operates As A Whole, At Fiber Optic Speeds, To Create A Fabric 35
Mega Data Center Market Description and Market Dynamics 36
Advantages of Mega Data Center Cloud 2.0: Multi-Threading 37
Cloud 2.0 Mega Data Center Multi-Threading Automates Systems Integration 38
Advantages of Mega Data Center Cloud 2.0: Scale 39
Infrastructure Scale 41
Intense Tide Of Data Causing Bottlenecks 42
Application Integration Bare Metal vs. Container Controllers 43
Workload Schedulers, Cluster Managers, And Container
Controllers Work Together 44
Google Kubernetes Container 45
Google Shift from Bare Metal To Mega Data Center Container Controllers 46
Mesosphere / Open Source Mesos Tool 46
Mega Data Center TCO and Pricing: Server vs. Mainframe vs. Cloud vs. Cloud 2.0 47
Labor Accounts For 75% Of The Cost Of An Enterprise Web Server Center 48
Cloud 2.0 Systems And The Mainframe Computing Systems Compared 49
Cloud 2.0 Mega Data Center Lower Operations Cost 50
Cloud 2.0 mega Data Center Is Changing the Hardware And
Data Center Markets 51
Scale Needed to Make Mega Data Center Containers Work Automatically 52
Multipathing 53
Cloud 2.0 Mega Data Centers Simple Repetitive Systems 53
Simplifying The Process Of Handling Load Balanced Requests 54
Google Servers Are Linked Logically, Each With Their Own Switch 55
Internet Apps Trillion Dollar Markets 56
Clos Simplicity 57
Clos-Based Topologies Increase Network Capacity 59
Mega Data Centers Embrace Open Source: Scale Is Everything 60
Open Cloud Server 61
Mainframe Provides Security 62
IBM Mainframe Handles Transactions, Business Analytics, and Mobile Apps 63
IBM Excels in Mastering Large Size Of Data To Be Managed 64
Transaction Based Mainframe 65
Microsoft Market Presence 66
Observers See Enterprise Data Center Moving to Cloud 67
Public Cloud Adoption 68
Microsoft Positioned To Become A Hyperscaler, Open Sourcing Hardware 69
Google Shift from Bare Metal To Container Controllers 70
Rapid Cloud Adoption: Google Says No Bare Metal 71
IBM Uses Bare Metal Servers: Mainframe Not Dead 72
VMware Photon Controller: Open Source Container Infrastructure Platform 73
Why Mega-Datacenters? 74
Data Center Switching 75
Software-Defined Networks Represent the Future 76
Broadcom 40 Gigabit Ethernet Optical Transceiver 78
40G, 100GBPS Transceivers Evolving Place in Mega Data Center: 79
NeoPhotonics 400 Gbps CFP8 PAM4 80
Applications: Equinix and Oracle 81
Oracle Cloud Platform 82
Reason Companies Move to Cloud 2.0 Mega Data Center 83
System On A Chip (SoAc) 84
New Class of Low-Power Server SoCs 85
Optical Transceiver Vendors Have Noticed That Mega Data Centers Are at the
Center of Modern Processing 86
Fiber High Bandwidth Datacenters 87
400 Gbps Headed For The Data Center 87
100 Gbps Adoption 89
Optical Transceiver Vendors Have Noticed That Mega Data Centers Are at the
Center of Modern Processing 89
Digital Workloads Increasing 90
Optical Transceiver High Growth as Shift to Cloud Occurs 91
Google Disruptive Technology: Base Orchestration Enhancements 92
Digital Realty Trust Lakeside Technology in Chicago: 1.1 Million Square Foot Data Center 93
Cisco Cloud Index: Cloud Replaces Data Centers 94
NTT Has Dominant Market Position 95
Enterprise Networking Rapid Transition 96
Public Cloud Adoption 97
Cisco CRS-3 Core Routing Platform 98
Evolution of Data Center Strategy 99
Systems Integration 101
AWS, Amazon Cloud Services Facebook, Google, and Microsoft: AWS leads in
Mega Data Center Infrastructure 102
Conclusion 103
Cloud 2.0 Mega Data Center Evolution 103
Appendix A 104
Growth of Quantity of Data 104
Data Expanding And Tools Used To Share, Store And Analyze Evolving At Phenomenal Rates 104
Video Traffic 105
Cisco Analysis of Business IP Traffic 105
Increasing Video Definition: By 2020, More Than 40 Percent of Connected Flat-
Panel TV Sets Will Be 4K 113
M2M Applications 115
Applications, For Telemedicine And Smart Car Navigation Systems,
Require Greater Bandwidth And Lower Latency 117
Explosion of Data Inside Cloud 2.0 Mega Data Center with Multi Threading 122
Cloud 2.0 Mega Data Center Multi-Threading Automates
Systems Integration 122
Fixed Broadband Speeds (in Mbps), 2015–2020 123
Internet Traffic Trends 127
Siemens Predicts IoT Growth 130
Appendix B: Things People Already Know About Cloud Computing 132
WinterGreen Research, 133
WinterGreen Research Methodology 134
List of Figures

Enterprise Data Center as a Bottleneck: Think Woods Hole
Figure 1. Existing Enterprise Data Center as a Bottleneck: Think Woods Hole 5
Figure 2. AWS Data Center Image 6
Figure 3. Achieving a Scalable Architecture from Simple Units 7
Figure 4. Facebook Sample Pod: Unit of Network 8
Figure 5. Facebook Data Center Fabric Network Topology 9
Figure 6. Cloud 2.0 Mega Data Center 11
Figure 7. Cloud 2.0 Mega Data Centers Support 1.5 Billion Facebook Users Worldwide. 12
Figure 8. Facebook DuPont Fabros Technology Ashburn, VA Data Center 24
Figure 9. SOA Foundation Business, Infrastructure, and Data Information Architecture 27
Figure 10. AWS Market Leader In Cloud Computing 32
Figure 11. 538,000SF: i/o Data Centers and Microsoft Phoenix One, Phoenix, Ariz. 34
Figure 12. Phoenix, Arizona i/o Data Center Design Innovations 34
Figure 13. Key Challenges Enterprise IT Datacenters: 36
Figure 14. Multi-threading Manages Pathways From One
Node To Another Node 37
Figure 15. Cloud Types of System Implementation 38
Figure 16. Google Mega Data Center Scale 39
Figure 17. Key Advantage of Cloud 2.0 Mega IT Datacenters: 40
Figure 18. NTT RagingWire Ashburn Va2 Data Center 41
Figure 19. AWS Region Diagram 42
Figure 20. Google Shift from Bare Metal To Container Controllers Advantages 45
Figure 21. Cloud 2.0 Mega Data Center Advantages 51
Figure 22. Images for Google Container Cloud 3.0 Mega Data Centers 52
Figure 23. Facebook Fifth Data Center Fort Worth Complex. 53
Figure 24. Google Compute Engine Load Balanced Requests Architecture 56
Figure 25. Google Extends App Indexing 57
Figure 26. Google Clos Multistage Switching Network 58
Figure 27. The Size Of The Basic Switch Element Has An Impact On
The Total Number Of Switching Nodes require Google Clos
Multistage Switching Network 59
Figure 28. Mainframe Security 62
Figure 29. IBM Mainframe System z/OS 63
Figure 30. z13 Server Benefits 64
Figure 31. Aspects of Cloud 65
Figure 32. Observers See Enterprise Data Center Moving to Cloud 67
Figure 33. Broadcom 40 Gigabit Ethernet Optical Transceiver 78
Figure 34. 40G, 100GBPS Transceiver Target Markets 79
Figure 35. NeoPhotonics 400G CFP8 PAM4 80
Figure 36. Neophotonics 400 Gbps CFP8 PAM4 Features 80
Figure 37. Equinix LD6 data center in Slough, England 81
Figure 38. Cloud 2.0 Mega Data Centers Are Demanding Significant
Amounts Of Power And Network Management 85
Figure 39. Flow of Digital Data Creating Bottlenecks In Enterprise Data Center 90
Figure 40. Google Base Orchestration Enhancement Functions 92
Figure 41. Digital Realty Trust Lakeside Technology Center Industrial-
Strength Power And Fiber Infrastructure 93
Figure 42. NTT RagingWire Data Centers Image 95
Figure 43. Google Andromeda Cloud High-Level Architecture 99
Figure 44. Amazon AWS Global Cloud Infrastructure 102
Figure 45. Cisco VNI Forecast Overview 106
Figure 46. The Cisco VNI Forecast—Historical Internet Context 107
Figure 47. Global Devices and Connections Growth 108
Figure 48. Average Number of Devices and Connections per Capita 110
Figure 49. Global IP Traffic by Devices 110
Figure 50. Global Internet Traffic by Device Type 111
Figure 51. Global 4K Video Traffic 113
Figure 52. Global IPv6-Capable Devices and Connections Forecast 2015–2020 114
Figure 53. Projected Global Fixed and Mobile IPv6 Traffic Forecast 2015–2020115
Figure 54. Global M2M Connection Growth 116
Figure 55. Global M2M Connection Growth by Industries 117
Figure 56. Global M2M Traffic Growth: Exabytes per Month 118
Figure 57. Global Residential Services Adoption and Growth 119
Figure 58. Global IP Traffic by Application Category 120
Figure 59. Mobile Video Growing Fastest; Online Video and Digital TV Grow Similarly 121
Figure 60. Global Cord Cutting Generates Double the Traffic 121
Figure 61. Fixed Broadband Speeds (in Mbps), 2015–2020 123
Figure 62. Future of Wi-Fi as Wired Complement 124
Figure 63. Global IP Traffic, Wired and Wireless* 125
Figure 64. Global Internet Traffic, Wired and Wireless 126
Figure 65. Cisco VNI Forecasts 194 EB per Month of IP Traffic by 2020 129
Figure 66. Cisco Forecast of Global Devices and Connections Growth 130
Figure 67. Siemens Perspective of Billions of Things, Trillions of Dollars 131
Figure 68. Benefits of Cloud Computing 132 



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