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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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