Research and Markets - Global Orchestration Software in the Mega Data Center Market Report 2017 Featuring Amazon, Uber, Google, IBM, and Microsoft
DUBLIN, May 17, 2017 /PRNewswire/ --
Research and Markets has announced the addition of Wintergreen Research, Inc's new report "Sea Change Series: Orchestration Software in the Mega Data Center" to their offering.
The 2017 module has 115 pages and 74 tables and figures. Orchestration Software in the Mega Data Center is used to tie a fabric architecture together that fills up an entire building with 100,000 processors and 100,001 switches. The mega data center described in the study is effective because it leverages the economies of scale.
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.
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.
Key Topics Covered:
Sea Change Series: Scale in the Mega Data Center Executive Summary
- Amazon, Google, Microsoft, Facebook
- IT Is Better When New Sets Of Servers Can Be Spun With The Push Of A Button
- Aim to Realign IT Cost Structure
- Scale Matters
- Table of Contents
1. Effect of Scale in the Mega Data Center
1.1 Facebook Mega Datacenter Physical Infrastructure
1.1.1 Facebook Automation of Mega Data Center Process
1.1.2 Facebook Altoona Data Center Networking Fabric
1.1.3 Facebook Altoona Cloud Mega Data Center
1.1.4 Facebook Altoona Data Center Innovative Networking Fabric Depends on Scale
1.1.5 Facebook Fabric Operates Inside the Data Center
1.1.6 Facebook Fabric
1.1.7 Exchange Of Data Between Servers Represents A Complex Automation Of Process
2. Applications Customized For Each User
2.1 Customized Back-End Service Tiers And Applications
2.2 Machine-To-Machine Management of Traffic Growth
2.2.1 Facebook Data Center Fabric Network Topology
2.2.2 Building-Wide Connectivity
2.3 Highly Modular Design Allows Users To Quickly Scale Capacity In Any Dimension
2.3.1 Back-End Service Tiers And Applications
2.3.2 Scaling Up As a Basic Function Of The Mega Data Center Network
2.3.3 Facebook Fabric Next-Generation Data Center Network Design: Pod Unit of Network
3. Mega Data Center Server Pods
3.1 Server Pods Permit An Architecture To Implement High-Performance Connectivity
3.1.1 Facebook Sample Pod: Unit of Network
3.1.2 Non-Blocking Network Architecture
3.2 Data Center Auto Discovery
3.3 Facebook Large-Scale Network
3.3.1 Rapid Deployment Architecture
3.3.2 Facebook Expedites Provisioning And Changes
4. Google Mega Data Center Scale
4.1 Google Douglas County Mega Data Center
4.1.1 Google Data Center Efficiency Measurements
4.1.2 Google Programmable Access To Network Stack
4.1.3 Google Software Defined Networking (SDN)-Supports Scale and Automation
4.1.4 Google Compute Engine Load Balancing
4.1.5 Google Compute Engine Load Balanced Requests Architecture
4.1.6 Google Compute Engine Load Balancing Scaling
4.2 Google Switches Provide Scale-Out: Server And Storage Expansion
4.2.1 Google Uses Switches Deployed in Fabrics
4.2.2 Google Mega Data Center Multi-pathing
4.2.3 Google Mega Data Center Multipathing: Routing Destinations
4.2.4 Google Clos Topology Network Capacity Scalability
4.2.5 Google Aggregation Switches Are Lashed Together Through a Set Of Non-Blocking Spine Switches
4.3 Google Network Called Jupiter
5. Microsoft Mega Data Center Scale
5.1 Microsoft Cloud Data Center Multi-Tenant Containers
5.2 Microsoft Azure Running Docker Containers
5.2.1 Microsoft Data Center, Dublin, 550,000 Sf
5.2.2 Microsoft Builds Intelligent Cloud Platform
5.3 Microsoft Server Products And Cloud Services
5.3.1 Microsoft Crafts Homegrown Linux For Azure Switches
5.3.2 Microsoft Azure Has Scale
5.4 Microsoft Azure Stack Hardware Foundation
5.5 Microsoft Azure Stack Key Systems Partners: Cisco Systems, Lenovo, Fujitsu, and NEC
5.6 Microsoft Gradual Transformation From A Platform Cloud To A Broader Offering Leveraging Economies of Scale
5.7 Microsoft Contributing to Open Systems
5.8 Microsoft Mega Data Center Supply Chain
5.9 Microsoft Leverages Open Compute Project to Bring Benefit to Enterprise Customers
5.9.1 Microsoft Assists Open Compute to Close The Loop On The Hardware Side
5.10 Microsoft Project Olympus Modular And Flexible
5.11 Microsoft Azure
5.11.1 Microsoft Azure Active Directory Has Synchronization
5.12 Microsoft Azure Has Scale
6. Mega Data Center Different from the Hyperscale Cloud
6.1 Hyperscale Cloud Computing Addresses The Issues Of Economies Of Scale
6.1.1 Mega Data Center Scaling
6.1.2 Mega Data Center Automatic Rules and Push-Button Actions
6.1.3 Keep It Simple Principle
7. Amazon Capex for Cloud 2.0 Mega Data Centers
7.1 Amazon Capex Dedicated To Support Datacenter
7.2 AWS Server Scale
7.3 Amazon North America
7.4 Amazon North America List of Locations
7.5 Innovation a Core Effort for Amazon
7.6 Amazon Offers the Richest Services Set
7.6.1 AWS Server Scale
7.7 On AWS, Customers Architect Their Applications
7.8 AWS Scale to Address Network Bottleneck
7.9 Networking A Concern for AWS Solved by Scale
7.10 AWS Regions and Network Scale
7.11 AWS Datacenter Bandwidth
7.12 Amazon (AWS) Regional Data Center
7.12.1 Map of Amazon Web Service Global Infrastructure
7.12.2 Rows of Servers Inside an Amazon (AWS) Data Center
7.12.3 Amazon Capex for Mega Data Centers
7.13 Amazon Addresses Enterprise Cloud Market, Partnering With VMware
7.13.1 Making Individual Circuits And Devices Unimportant Is A Primary Aim Of Fabric Architecture
8. Clos Network Architecture Topology
8.1 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
8.1.1 Clos Network
8.2 Digital Data Expanding Exponentially, Global IP Traffic Passes Zettabyte (1000 Exabytes) Threshold
9. Summary: Economies of Scale
For more information about this report visit http://www.researchandmarkets.com/research/xp4srz/sea_change
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