Sea Change Series: Scale in the Mega Data Center
Next generation mega data center technology is able to leverage scale to implement cloud computing that is better than most of what is out there now. Scale is a vital part of the technology used to support next generation data centers. The study is targeted to C-level executives that need to move quickly and surely to improve IT. Automation of IT depends on understanding the business market opportunity from an independent perspective.
Vendors are smart but they are committed to the technology they are pushing, the Sea Change Series from WinterGreen Research is able to provide a perspective not available anywhere else. Extreme scale is what brings enough pathways inside a Mega data center to create a non-blocking (CLOS) networked server architecture. Non-blocking network architecture benefits the business because it permits launching thousands of virtual severs on demand at the application layer. In this manner, innovation can be made to happen quickly. Using a mega data center, DevOps and/or automated processes can request and deploy additional resource without backing the Dell truck up to the data center every week to provide on-demand capacity.
Automated deprovisioning handles freeing of surplus resources, while being virtual means not having stacks of surplus hardware to dispose of as underutilized capital assets. Modern data centers are organized into processing nodes that manage different applications at a layer above infrastructure. Data is stored permanently and operated on in place. These are the two technologies to check for when choosing a data center. These architectural features provide economies of scale that greatly reduce the IT spend while offering better quality IT. Once scale is in place, then the economies of scale kick in. When negotiating for cloud capability, managers need to check to see that sufficient multiple pathways are available to reach any node in a non-blocking manner.
Non-blocking architecture is more efficient than other IT infrastructure and supports better innovation for apps and smart digitization. Not all cloud architectures offer this business benefit.
The Cloud 2.0 mega data center platform fabric technologies support the digital economy by creating scale with a network internal to the mega data center system image. Without scale, there are not enough pathways inside the data center to enable elimination of bottlenecks.
Access to every node in the fabric, and multiple duplicate pathways to every node are needed to enable real time application connectivity. With sufficient scale, if one pathway is blocked, there are enough other pathways to get to the desired node resources. The theme of this study is that scale matters. Scale can be implemented by IT, but the executive needs to understand that there is a difference between different technologies. In a mega data center, the system is implemented as a fabric: servers are linked to top of rack switches, which are made from merchant silicon chips, mostly Broadcom, some switch ASICs.
A pod of server racks are linked to each other through an edge aggregation switch. A pod of server racks is based on the same ASICs as in the top of rack switches. The importance of nonblocking architecture is compelling. Aggregation switches are lashed together through a set of non-blocking spine switches. All switches are based on the same chip. This is precisely the way Facebook is building its own Wedge and 6-pack open switches– nine years after Google did it. The amazing thing is that Facebook had not done this already.
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.
Maybe scale is not the only answer, maybe in 20 years, Quantum computing will bring a new data center system, but for now, Clos architecture and scale dominate those IT centers that have the strongest growth engine. Business leaders are challenged to move their enterprises to the next level of competition. 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 disruptive strategic positioning. 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. Disruption in the business markets represents major opportunity for vendors with cloud offerings. This is part of a larger digital transformation, a digital approach to interconnecting everything that enables organizations to drive changes in their business models and ecosystems.
Disruptive cloud systems are provided by 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. By leveraging digital competencies, businesses can grow faster than they would otherwise.
A digital strategy, in conjunction with the appropriate unified communications solution permits the implementation of innovative communications services. Digital connectivity with combined voice, video and file transfer can help organizations and their end users innovate and compete more effectively. It is imperative that organizations have a digital communications strategy in place. This is an era where the distinction between the technologies and processes that businesses deploy is tightly linked. Digital technology directly impacts customers and markets.
The boundary between internal operations of the enterprise and its external ecosystem is rapidly disappearing. Customers, markets, competitors, partners, and regulators are inextricably linked. According to Susan Eustis, lead author of the team that prepared the study, “Mega data centers need to be understood by all senior executives whether they move in that direction or not. These are the IT used by the fastest growing organizations Google, AWS, Microsoft, and Facebook. There are 25 Sea Change Data Center study modules describing different aspects of the move to mega data centers.
The Scale module describes that it is not sufficient just to try certain cloud techniques. “Scale is an essential aspect of the data center positioning for these leading companies. These companies use Clos networks as their data center implementations. This module addresses how and why scale in the mega data center is important. The market shift to non-blocking network inside data center building means companies have to hit a certain scale before Clos networks work.”
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.
Vendors are smart but they are committed to the technology they are pushing, the Sea Change Series from WinterGreen Research is able to provide a perspective not available anywhere else. Extreme scale is what brings enough pathways inside a Mega data center to create a non-blocking (CLOS) networked server architecture. Non-blocking network architecture benefits the business because it permits launching thousands of virtual severs on demand at the application layer. In this manner, innovation can be made to happen quickly. Using a mega data center, DevOps and/or automated processes can request and deploy additional resource without backing the Dell truck up to the data center every week to provide on-demand capacity.
Automated deprovisioning handles freeing of surplus resources, while being virtual means not having stacks of surplus hardware to dispose of as underutilized capital assets. Modern data centers are organized into processing nodes that manage different applications at a layer above infrastructure. Data is stored permanently and operated on in place. These are the two technologies to check for when choosing a data center. These architectural features provide economies of scale that greatly reduce the IT spend while offering better quality IT. Once scale is in place, then the economies of scale kick in. When negotiating for cloud capability, managers need to check to see that sufficient multiple pathways are available to reach any node in a non-blocking manner.
Non-blocking architecture is more efficient than other IT infrastructure and supports better innovation for apps and smart digitization. Not all cloud architectures offer this business benefit.
The Cloud 2.0 mega data center platform fabric technologies support the digital economy by creating scale with a network internal to the mega data center system image. Without scale, there are not enough pathways inside the data center to enable elimination of bottlenecks.
Access to every node in the fabric, and multiple duplicate pathways to every node are needed to enable real time application connectivity. With sufficient scale, if one pathway is blocked, there are enough other pathways to get to the desired node resources. The theme of this study is that scale matters. Scale can be implemented by IT, but the executive needs to understand that there is a difference between different technologies. In a mega data center, the system is implemented as a fabric: servers are linked to top of rack switches, which are made from merchant silicon chips, mostly Broadcom, some switch ASICs.
A pod of server racks are linked to each other through an edge aggregation switch. A pod of server racks is based on the same ASICs as in the top of rack switches. The importance of nonblocking architecture is compelling. Aggregation switches are lashed together through a set of non-blocking spine switches. All switches are based on the same chip. This is precisely the way Facebook is building its own Wedge and 6-pack open switches– nine years after Google did it. The amazing thing is that Facebook had not done this already.
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.
Maybe scale is not the only answer, maybe in 20 years, Quantum computing will bring a new data center system, but for now, Clos architecture and scale dominate those IT centers that have the strongest growth engine. Business leaders are challenged to move their enterprises to the next level of competition. 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 disruptive strategic positioning. 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. Disruption in the business markets represents major opportunity for vendors with cloud offerings. This is part of a larger digital transformation, a digital approach to interconnecting everything that enables organizations to drive changes in their business models and ecosystems.
Disruptive cloud systems are provided by 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. By leveraging digital competencies, businesses can grow faster than they would otherwise.
A digital strategy, in conjunction with the appropriate unified communications solution permits the implementation of innovative communications services. Digital connectivity with combined voice, video and file transfer can help organizations and their end users innovate and compete more effectively. It is imperative that organizations have a digital communications strategy in place. This is an era where the distinction between the technologies and processes that businesses deploy is tightly linked. Digital technology directly impacts customers and markets.
The boundary between internal operations of the enterprise and its external ecosystem is rapidly disappearing. Customers, markets, competitors, partners, and regulators are inextricably linked. According to Susan Eustis, lead author of the team that prepared the study, “Mega data centers need to be understood by all senior executives whether they move in that direction or not. These are the IT used by the fastest growing organizations Google, AWS, Microsoft, and Facebook. There are 25 Sea Change Data Center study modules describing different aspects of the move to mega data centers.
The Scale module describes that it is not sufficient just to try certain cloud techniques. “Scale is an essential aspect of the data center positioning for these leading companies. These companies use Clos networks as their data center implementations. This module addresses how and why scale in the mega data center is important. The market shift to non-blocking network inside data center building means companies have to hit a certain scale before Clos networks work.”
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.
SEA CHANGE SERIES: SCALE IN THE MEGA DATA CENTER
Sea Change Series: Scale in the Mega Data Center, Amazon, Google, Microsoft, Facebook
Aim to Realign IT Cost Structure
Scale Matters
Table of Contents
Facebook Mega Datacenter Physical Infrastructure
Facebook Automation of Mega Data Center Process
Facebook Altoona Data Center Networking Fabric
Facebook Altoona Cloud Mega Data Center
Facebook Altoona Data Center Innovative Networking Fabric Depends on Scale
Facebook Fabric Operates Inside the Data Center
Facebook Fabric
Exchange Of Data Between Servers Represents A Complex Automation Of Process
Applications Customized For Each User
Machine-To-Machine Management of Traffic Growth
Facebook Data Center Fabric Network Topology
Building-Wide Connectivity
Highly Modular Design Allows Users To Quickly Scale Capacity In Any Dimension
Back-End Service Tiers And Applications
Scaling Up As a Basic Function Of The Mega Data Center Network
Facebook Fabric Next-Generation Data Center Network Design: Pod Unit of Network
Mega Data Center Server Pods
Facebook Sample Pod: Unit of Network
Non-Blocking Network Architecture
Data Center Auto Discovery
Facebook Large-Scale Network
Rapid Deployment Architecture
Facebook Expedites Provisioning And Changes
Google Douglas County Mega Data Center
Google Data Center Efficiency Measurements
Google Programmable Access To Network Stack
Google Software Defined Networking (SDN)-Supports Scale and Automation
Google Compute Engine Load Balancing
Google Compute Engine Load Balanced Requests Architecture
Google Compute Engine Load Balancing Scaling
Google Switches Provide Scale-Out: Server And Storage Expansion
Google Uses Switches and Routers Deployed in Fabrics
Google Mega Data Center Multipathing
Google Mega Data Center Multipathing: Routing Destinations
Google Clos Topology Network Capacity Scalability
Google Aggregation Switches Are Lashed Together Through a Set Of Non-Blocking Spine Switches
Google Network Called Jupiter
Microsoft Cloud Data Center Multi-Tenant Containers
Microsoft Azure Running Docker Containers
Microsoft Data Center, Dublin, 550,000 Sf
Microsoft Builds Intelligent Cloud Platform
Microsoft Crafts Homegrown Linux For Azure Switches
Microsoft Azure Has Scale
Microsoft Azure Stack Hardware Foundation
Microsoft Azure Stack Key Systems Partners: Cisco Systems, Lenovo, Fujitsu, and NEC
Microsoft Gradual Transformation From A Platform Cloud To A Broader Offering Leveraging Economies of Scale64
Microsoft Contributing to Open Systems
Microsoft Mega Data Center Supply Chain
Microsoft Leverages Open Compute Project to Bring Benefit to Enterprise Customers
Microsoft Assists Open Compute to Close The Loop On The Hardware Side
Microsoft Project Olympus Modular And Flexible
Microsoft Azure
Microsoft Azure Active Directory Has Synchronization
Microsoft Azure Has Scale
Mega Data Center Different from the Hyperscale Cloud
Mega Data Center Scaling
Mega Data Center Automatic Rules and Push-Button Actions
Amazon Capex for Cloud 2.0 Mega Data Centers
AWS Server Scale
Amazon North America
Innovation a Core Effort for Amazon
Amazon Offers the Richest Services Set
AWS Server Scale
On AWS, Customers Architect Their Applications
AWS Scale to Address Network Bottleneck
Networking A Concern for AWS Solved by Scale
AWS Regions and Network Scale
AWS Datacenter Bandwidth
Amazon (AWS) Regional Data Center
Map of Amazon Web Service Global Infrastructure
Rows of Servers Inside an Amazon (AWS) Data Center
Amazon Capex for Mega Data Centers
Amazon Addresses Enterprise Cloud Market, Partnering With VMware
Making Individual Circuits And Devices Unimportant Is A Primary Aim Of Fabric Architecture
Google Clos Network Architecture Topology Allows the Building a Non-Blocking Network Using Small Switches
You Have To Hit A Certain Scale Before Clos Networks Work
Clos Network
Digital Data Expanding Exponentially, Global IP Traffic Passes Zettabyte (1000 Exabytes) Threshold
Summary: Economies of Scale
Sea Change Series: Scale in the Mega Data Center, Amazon, Google, Microsoft, Facebook
Aim to Realign IT Cost Structure
Scale Matters
Table of Contents
Facebook Mega Datacenter Physical Infrastructure
Facebook Automation of Mega Data Center Process
Facebook Altoona Data Center Networking Fabric
Facebook Altoona Cloud Mega Data Center
Facebook Altoona Data Center Innovative Networking Fabric Depends on Scale
Facebook Fabric Operates Inside the Data Center
Facebook Fabric
Exchange Of Data Between Servers Represents A Complex Automation Of Process
Applications Customized For Each User
Machine-To-Machine Management of Traffic Growth
Facebook Data Center Fabric Network Topology
Building-Wide Connectivity
Highly Modular Design Allows Users To Quickly Scale Capacity In Any Dimension
Back-End Service Tiers And Applications
Scaling Up As a Basic Function Of The Mega Data Center Network
Facebook Fabric Next-Generation Data Center Network Design: Pod Unit of Network
Mega Data Center Server Pods
Facebook Sample Pod: Unit of Network
Non-Blocking Network Architecture
Data Center Auto Discovery
Facebook Large-Scale Network
Rapid Deployment Architecture
Facebook Expedites Provisioning And Changes
Google Douglas County Mega Data Center
Google Data Center Efficiency Measurements
Google Programmable Access To Network Stack
Google Software Defined Networking (SDN)-Supports Scale and Automation
Google Compute Engine Load Balancing
Google Compute Engine Load Balanced Requests Architecture
Google Compute Engine Load Balancing Scaling
Google Switches Provide Scale-Out: Server And Storage Expansion
Google Uses Switches and Routers Deployed in Fabrics
Google Mega Data Center Multipathing
Google Mega Data Center Multipathing: Routing Destinations
Google Clos Topology Network Capacity Scalability
Google Aggregation Switches Are Lashed Together Through a Set Of Non-Blocking Spine Switches
Google Network Called Jupiter
Microsoft Cloud Data Center Multi-Tenant Containers
Microsoft Azure Running Docker Containers
Microsoft Data Center, Dublin, 550,000 Sf
Microsoft Builds Intelligent Cloud Platform
Microsoft Crafts Homegrown Linux For Azure Switches
Microsoft Azure Has Scale
Microsoft Azure Stack Hardware Foundation
Microsoft Azure Stack Key Systems Partners: Cisco Systems, Lenovo, Fujitsu, and NEC
Microsoft Gradual Transformation From A Platform Cloud To A Broader Offering Leveraging Economies of Scale64
Microsoft Contributing to Open Systems
Microsoft Mega Data Center Supply Chain
Microsoft Leverages Open Compute Project to Bring Benefit to Enterprise Customers
Microsoft Assists Open Compute to Close The Loop On The Hardware Side
Microsoft Project Olympus Modular And Flexible
Microsoft Azure
Microsoft Azure Active Directory Has Synchronization
Microsoft Azure Has Scale
Mega Data Center Different from the Hyperscale Cloud
Mega Data Center Scaling
Mega Data Center Automatic Rules and Push-Button Actions
Amazon Capex for Cloud 2.0 Mega Data Centers
AWS Server Scale
Amazon North America
Innovation a Core Effort for Amazon
Amazon Offers the Richest Services Set
AWS Server Scale
On AWS, Customers Architect Their Applications
AWS Scale to Address Network Bottleneck
Networking A Concern for AWS Solved by Scale
AWS Regions and Network Scale
AWS Datacenter Bandwidth
Amazon (AWS) Regional Data Center
Map of Amazon Web Service Global Infrastructure
Rows of Servers Inside an Amazon (AWS) Data Center
Amazon Capex for Mega Data Centers
Amazon Addresses Enterprise Cloud Market, Partnering With VMware
Making Individual Circuits And Devices Unimportant Is A Primary Aim Of Fabric Architecture
Google Clos Network Architecture Topology Allows the Building a Non-Blocking Network Using Small Switches
You Have To Hit A Certain Scale Before Clos Networks Work
Clos Network
Digital Data Expanding Exponentially, Global IP Traffic Passes Zettabyte (1000 Exabytes) Threshold
Summary: Economies of Scale
LIST OF FIGURES
Figure 1. Slow Growth Companies Do Not Have Data Center Scale
Figure 2. Mega Data Center Fabric Implementation
Figure 3. Facebook Schematic Fabric-Optimized Datacenter Physical Topology
Figure 4. Facebook Automation of Mega Data Center Process
Figure 5. Facebook Altoona Positioning Of Global Infrastructure
Figure 6. FaceBook Equal Performance Paths Between Servers
Figure 7. FaceBook Data Center Fabric Depends on Scale
Figure 8. Facebook Fabric Operates Inside the Data Center, Fabric Is The Whole Data Center
Figure 9. Fabric Switches and Top of Rack Switches, Facebook Took a Disaggregated Approach
Figure 10. Exchange Of Data Between Servers Represents A Complex Automation Of Process20
Figure 11. Samsung Galaxy J3
Figure 12. Facebook Back-End Service Tiers And Applications Account for Machine-To-Machine Traffic Growth
Figure 1. Facebook Data Center Fabric Network Topology
Figure 13. Implementing building-wide connectivity
Figure 14. Modular Design Allows Users To Quickly Scale Capacity In Any Dimension
Figure 15. Facebook Back-End Service Tiers And Applications Functions
Figure 16. Using Fabric to Scale Capacity
Figure 17. Facebook Fabric: Pod Unit of Network
Figure 18. Server Pods Permit An Architecture Able To Implement Uniform High-Performance Connectivity
Figure 19. Non-Blocking Network Architecture
Figure 20. Facebook Automation of Cloud 2.0 Mega Data Center Process
Figure 21. Facebook Creating a Modular Cloud 2.0 mega data center Solution
Figure 22. Facebook Cloud 2.0 mega data center Fabric High-Level Settings Components
Figure 23. Facebook Mega Data Center Fabric Unattended Mode
Figure 24. Facebook Data Center Auto Discovery Functions
Figure 25. Facebook Automated Process Rapid Deployment Architecture
Figure 26. Google Douglas County Cloud 2.0 Mega Data Center
Figure 27. Google Data Center Efficiency Measurements
Figure 28. Google Andromeda Cloud High-Level Architecture
Figure 29. Google Andromeda Software Defined Networking (SDN)-Based Substrate Functions43
Figure 30. Google Compute Engine Load Balancing Functions
Figure 31. Google Compute Engine Load Balanced Requests Architecture
Figure 32. Google Compute Engine Load Balancing Scaling
Figure 33. Google Traffic Generated by Data Center Servers
Figure 34. Google Mega Data Center Multipathing: Implementing Lots And Lots Of Paths Between Each Source And Destination
Figure 35. Google Mega Data Center Multipathing: Routing Destinations
Figure 36. Google Builds Own Network Switches And Software
Figure 37. Google Clos Topology Network Capacity Scalability
Figure 38. Schematic fabric-optimized Facebook datacenter physical topology
Figure 39. Google Jupiter Network Delivers 1.3 Pb/Sec Of Aggregate Bisection Bandwidth Across A Datacenter
Figure 40. Microsoft Azure Cloud Software Stack Hyper-V hypervisor
Figure 41. Microsoft Azure Running Docker Containers
Figure 42. Microsoft Data Center, Dublin, 550,000 Sf
Figure 43. Microsoft-Azure-Stack-Block-Diagram
Figure 44. Microsoft Azure Stack Architecture
Figure 45. Microsoft Data Centers
Figure 46. Microsoft Open Hardware Design: Project Olympus
Figure 47. Microsoft Open Compute Closes That Loop On The Hardware Side
Figure 48. Microsoft Olympus Product
Figure 49. Microsoft Azure Has Scale
Figure 50. Mega Data Center Cloud vs. Hyperscale Cloud
Figure 51. Amazon Web Services
Figure 52. Amazon North America Map
Figure 53. Amazon North America List of Locations
Figure 54. Woods Hole Bottleneck: Google Addresses Network Bottleneck with Scale
Figure 55. Example of AWS Region
Figure 56. Example of AWS Availability Zone
Figure 57. Example of AWS Data Center
Figure 58. AWS Network Latency and Variability
Figure 59. Amazon (AWS) Regional Data Center
Figure 60. A Map of Amazon Web Service Global Infrastructure
Figure 61. Rows of Servers Inside an Amazon (AWS) Data Center
Figure 62. Clos Network
Figure 63. Data Center Technology Shifting
Figure 64. Data Center Technology Shift
Figure 1. Slow Growth Companies Do Not Have Data Center Scale
Figure 2. Mega Data Center Fabric Implementation
Figure 3. Facebook Schematic Fabric-Optimized Datacenter Physical Topology
Figure 4. Facebook Automation of Mega Data Center Process
Figure 5. Facebook Altoona Positioning Of Global Infrastructure
Figure 6. FaceBook Equal Performance Paths Between Servers
Figure 7. FaceBook Data Center Fabric Depends on Scale
Figure 8. Facebook Fabric Operates Inside the Data Center, Fabric Is The Whole Data Center
Figure 9. Fabric Switches and Top of Rack Switches, Facebook Took a Disaggregated Approach
Figure 10. Exchange Of Data Between Servers Represents A Complex Automation Of Process20
Figure 11. Samsung Galaxy J3
Figure 12. Facebook Back-End Service Tiers And Applications Account for Machine-To-Machine Traffic Growth
Figure 1. Facebook Data Center Fabric Network Topology
Figure 13. Implementing building-wide connectivity
Figure 14. Modular Design Allows Users To Quickly Scale Capacity In Any Dimension
Figure 15. Facebook Back-End Service Tiers And Applications Functions
Figure 16. Using Fabric to Scale Capacity
Figure 17. Facebook Fabric: Pod Unit of Network
Figure 18. Server Pods Permit An Architecture Able To Implement Uniform High-Performance Connectivity
Figure 19. Non-Blocking Network Architecture
Figure 20. Facebook Automation of Cloud 2.0 Mega Data Center Process
Figure 21. Facebook Creating a Modular Cloud 2.0 mega data center Solution
Figure 22. Facebook Cloud 2.0 mega data center Fabric High-Level Settings Components
Figure 23. Facebook Mega Data Center Fabric Unattended Mode
Figure 24. Facebook Data Center Auto Discovery Functions
Figure 25. Facebook Automated Process Rapid Deployment Architecture
Figure 26. Google Douglas County Cloud 2.0 Mega Data Center
Figure 27. Google Data Center Efficiency Measurements
Figure 28. Google Andromeda Cloud High-Level Architecture
Figure 29. Google Andromeda Software Defined Networking (SDN)-Based Substrate Functions43
Figure 30. Google Compute Engine Load Balancing Functions
Figure 31. Google Compute Engine Load Balanced Requests Architecture
Figure 32. Google Compute Engine Load Balancing Scaling
Figure 33. Google Traffic Generated by Data Center Servers
Figure 34. Google Mega Data Center Multipathing: Implementing Lots And Lots Of Paths Between Each Source And Destination
Figure 35. Google Mega Data Center Multipathing: Routing Destinations
Figure 36. Google Builds Own Network Switches And Software
Figure 37. Google Clos Topology Network Capacity Scalability
Figure 38. Schematic fabric-optimized Facebook datacenter physical topology
Figure 39. Google Jupiter Network Delivers 1.3 Pb/Sec Of Aggregate Bisection Bandwidth Across A Datacenter
Figure 40. Microsoft Azure Cloud Software Stack Hyper-V hypervisor
Figure 41. Microsoft Azure Running Docker Containers
Figure 42. Microsoft Data Center, Dublin, 550,000 Sf
Figure 43. Microsoft-Azure-Stack-Block-Diagram
Figure 44. Microsoft Azure Stack Architecture
Figure 45. Microsoft Data Centers
Figure 46. Microsoft Open Hardware Design: Project Olympus
Figure 47. Microsoft Open Compute Closes That Loop On The Hardware Side
Figure 48. Microsoft Olympus Product
Figure 49. Microsoft Azure Has Scale
Figure 50. Mega Data Center Cloud vs. Hyperscale Cloud
Figure 51. Amazon Web Services
Figure 52. Amazon North America Map
Figure 53. Amazon North America List of Locations
Figure 54. Woods Hole Bottleneck: Google Addresses Network Bottleneck with Scale
Figure 55. Example of AWS Region
Figure 56. Example of AWS Availability Zone
Figure 57. Example of AWS Data Center
Figure 58. AWS Network Latency and Variability
Figure 59. Amazon (AWS) Regional Data Center
Figure 60. A Map of Amazon Web Service Global Infrastructure
Figure 61. Rows of Servers Inside an Amazon (AWS) Data Center
Figure 62. Clos Network
Figure 63. Data Center Technology Shifting
Figure 64. Data Center Technology Shift
