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Data Center as A Bottleneck: Market Strategies, Analysis, and Opportunities

February 2017 | 138 pages | ID: DD5E2A31621EN
WinterGreen Research

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This module is part of a study 2,622 pages long, with 1,273 tables and figures that addresses the business issues connected with data center modernization. There are 20 module parts to the larger study comprised of detailed analysis of how new infrastructure layers will work to support management of vast quantities of data.
Worldwide hyperscale data center markets implement cloud computing with shared resource and the aim, more or less achieved of providing foolproof security systems that protect the integrity of corporate data. Cloud data centers are poised to achieve explosive growth as they replace enterprise web server farms with cloud computing and with cloud 2.0 automated process computing. The implementation of secure large computing capability inside data center buildings provides economies of scale not matched by current state of the art enterprise data center standalone server technology.
Economies of scale provide savings of between 50% to 100x less cost. These are savings that cannot be ignored by any person responsible or running a business.
Building size cloud 2.0 computer implementations feature simplicity of design achievable only with scale. These data centers implement cloud 2.0 in a move that works better than much of the current cloud computing. The cloud 2.0 data centers have been reduced to two types of components, an ASIC server: single chip servers and a network based on a matching ASIC switch. Data centers are implemented with a software controller for that ASIC server and switch infrastructure.
The major driving factors for Cloud 2.0 mega data center market are cost benefit, growing colocation services, need for data consolidation, and cloud. Amazon (AWS), Microsoft, Google, and Facebook data centers are in a class by themselves, they have functioning fully automatic, self-healing, networked mega datacenters that operate at fiber optic speeds to create a fabric that can access any node in any particular data center because there are multiple pathways to every node. In this manner, they automate applications integration for any data in the mega data center.
This module addresses the issue of data center bottlenecks initially by drawing the reader’s attention to an analogy: navigating a sailboat through Woods Hole on Cape cos Massachusetts. The navigation is tricky -- potentially dangerous.
The bottleneck is potentially dangerous -- for a combination of reasons. The current routinely flows through at over 4 knots, and can hit 7 knots. Full current on the nose makes transit slow and awkward. Full current from astern where the current runs slightly cross-channel causes awkward transit at an alarmingly rapid pace.
The existing data centers have a lot of entrenched culture and equipment. Mainframes represent 86% of transaction data processing and function generally in a manner separated from web traffic, though they doo handle some web traffic. One issue is, “What to do with the existing mainframes with its separate culture, functioning at 115% of capacity, and utterly impregnable security?”
“The mega data centers have stepped in to do the job of automated process in the data center, increasing compute capacity efficiently by simplifying the processing task into two simple component parts that can scale on demand. There is an infrastructure layer that functions with simple processor, switch, and transceiver hardware orchestrated by software. There is an application layer that functions in a manner entirely separate from the infrastructure layer. The added benefit of automated application integration at the application layer brings massive savings to the IT budget, replacing manual process for application integration. The mainframe remains separate from this mega data center adventure, staying the course, likely to hold onto the transaction management part o data processing.”
The only way to realign enterprise data center cost structures is to automate infrastructure management and orchestration. Mega data centers automate server and connectivity management. Cisco UCS Director illustrates software that automates everything beyond. Cisco UCS automates switching and storage, along with hypervisor, operating system, and virtual machine provisioning.
As IT relies more on virtualization and cloud mega data center computing, the physical infrastructure is flexible and agile enough to support the virtual infrastructure. Comprehensive infrastructure management and orchestration is essential. The enterprise data centers and many cloud infrastructure operations all have similar problems of being mired in administrative expense. This presents a problem for those tasked with running companies.
The Internet has grown by a factor of 100 over the past 10 years. To accommodate that growth, hyperscale data centers have evolved to provide processing at scale, known as cloud computing. Facebook for one, has increased the corporate data center compute capacity by a factor of 1,000. To meet future demands on the Internet over the next 10 years, the company needs to increase capacity by the same amount again. Nobody really knows how to get there. Tis study takes a hard look at the alternatives open to business leaders.
Everyone should know by now that the enterprise data center is dead. It will no longer exist in three years, that is the time it takes servers to become outdated and need replacement. In that timeframe, enterprises will migrate workload from the core enterprise servers to the large data center that can provide processing at half the cost of current processing. Maybe this forecast is too aggressive, but probably not. The mainframe stays around as detailed in a different report.
The Hyperscale Data Centers: market size at $86.9.7 million in 2016 is anticipated to be $359.7 billion in 2023. The market has astoundingly rapid growth for a market that really is not yet well defined. The increasing scope of applications across different industries, manufacturing, medical, retail, game, and automotive, all industries really, is expected to drive demand over the forecast period to these unprecedented levels, reaching into the trillion-dollar market arenas soon.
The hyperscale data centers are position to manage the explosion in web data, including data from IoT technology that is in the nascent stage with a huge growth potential, and has attracted large investments contributing to the industry growth.
Sea Change Series: Cloud 2.0, Mega Data Centers
Executive Summary
Bottlenecks: Navigating Woods Hole Is Tricky -- Potentially Dangerous
Viewed From The Cockpit: The Converging And Diverging Channels Can Look Like A Random Scattering Of Reds And Greens
Using the Red and Green Boys to Navigate
Nine-Foot Bay Of Fundy Tide
Video and Data Streams Create Bottlenecks:
Demand for New Types of Cloud
The Right Type of Cloud: Mega Data Centers, Cloud 2.0
Table of Contents
Mega Data Center Scale and Automation
Only Way To Realign Data Center Cost Structure Is To Automate Infrastructure Management And Orchestration
Entire Warehouse Building As A Single System
Half a Trillion Dollars
Two Tier Architecture to Achieve Simplicity
Bandwidth and Data Storage Demands Create Need For Application Integration
Cultural Shift
Line of Business Loses Control Of Hardware Servers
Cultural Change Needed to Move to Cloud
Adjusting to Rapid Change
Amazon Web Services (AWS) Fully Automatic, Self-Healing, Networked Mega Systems Inside A Building.
Data Center Design Innovation
Shift To An All-Digital Business Environment
System Operates As A Whole, At Fiber Optic Speeds, To Create A Fabric
Mega Data Center Market Description and Market Dynamics
Advantages of Mega Data Center Cloud 2.0: Multi-Threading
Cloud 2.0 Mega Data Center Multi-Threading Automates Systems Integration
Advantages of Mega Data Center Cloud 2.0: Scale
Infrastructure Scale
Intense Tide Of Data Causing Bottlenecks
Application Integration Bare Metal vs. Container Controllers
Workload Schedulers, Cluster Managers, And Container Controllers Work Together
Google Kubernetes Container
Google Shift from Bare Metal To Mega Data Center Container Controllers
Mesosphere / Open Source Mesos Tool
Mega Data Center TCO and Pricing: Server vs. Mainframe vs. Cloud vs. Cloud 2.0
Labor Accounts For 75% Of The Cost Of An Enterprise Web Server Center
Cloud 2.0 Systems And The Mainframe Computing Systems Compared
Cloud 2.0 Mega Data Center Lower Operations Cost
Cloud 2.0 mega Data Center Is Changing the Hardware And Data Center Markets
Scale Needed to Make Mega Data Center Containers Work Automatically
Cloud 2.0 Mega Data Centers Simple Repetitive Systems
Simplifying The Process Of Handling Load Balanced Requests
Google Servers Are Linked Logically, Each With Their Own Switch
Internet Apps Trillion Dollar Markets
Clos Simplicity
Clos-Based Topologies Increase Network Capacity
Mega Data Centers Embrace Open Source: Scale Is Everything
Open Cloud Server
Mainframe Provides Security
IBM Mainframe Handles Transactions, Business Analytics, and Mobile Apps
IBM Excels in Mastering Large Size Of Data To Be Managed
Transaction Based Mainframe
Microsoft Market Presence
Observers See Enterprise Data Center Moving to Cloud
Public Cloud Adoption
Microsoft Positioned To Become A Hyperscaler, Open Sourcing Hardware
Google Shift from Bare Metal To Container Controllers
Rapid Cloud Adoption: Google Says No Bare Metal
IBM Uses Bare Metal Servers: Mainframe Not Dead
VMware Photon Controller: Open Source Container Infrastructure Platform
Why Mega-Datacenters?
Data Center Switching
Software-Defined Networks Represent the Future
Broadcom 40 Gigabit Ethernet Optical Transceiver
NeoPhotonics 400 Gbps CFP8 PAM4
Applications: Equinix and Oracle
Oracle Cloud Platform
Reason Companies Move to Cloud 2.0 Mega Data Center
System On A Chip (SoAc)
New Class of Low-Power Server SoCs
Optical Transceiver Vendors Have Noticed That Mega Data Centers Are at the
Center of Modern Processing
Fiber High Bandwidth Datacenters
Optical Transceiver Vendors Have Noticed That Mega Data Centers Are at the Center of Modern Processing
Digital Workloads Increasing
Optical Transceiver High Growth as Shift to Cloud Occurs
Google Disruptive Technology: Base Orchestration Enhancements
Digital Realty Trust Lakeside Technology in Chicago: 1.1 Million Square Foot Data Center
Cisco Cloud Index: Cloud Replaces Data Centers
NTT Has Dominant Market Position
Enterprise Networking Rapid Transition
Public Cloud Adoption
Cisco CRS-3 Core Routing Platform
Evolution of Data Center Strategy
Systems Integration
AWS, Amazon Cloud Services Facebook, Google, and Microsoft: AWS leads in Mega Data Center Infrastructure
Cloud 2.0 Mega Data Center Evolution
Appendix A
Growth of Quantity of Data
Data Expanding And Tools Used To Share, Store And Analyze Evolving At Phenomenal Rates
Video Traffic
Cisco Analysis of Business IP Traffic
Increasing Video Definition: By 2020, More Than 40 Percent of Connected Flat- Panel TV Sets Will Be 4K
M2M Applications
Applications, For Telemedicine And Smart Car Navigation Systems, Require Greater Bandwidth And Lower Latency
Explosion of Data Inside Cloud 2.0 Mega Data Center with Multi Threading
Cloud 2.0 Mega Data Center Multi-Threading Automates Systems Integration
Fixed Broadband Speeds (in Mbps), 2015–2020
Internet Traffic Trends
Siemens Predicts IoT Growth
Appendix B: Things People Already Know About Cloud Computing


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

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