2017 Global Data Center as a Bottleneck Market Players Attract More Investors.

The study on Data Center as a Bottleneck Market makes a detailed analysis of the upstream raw materials demand, downstream client demand and future industry growth prospects. The study explores the profile of manufacturing plants across major regions in terms of their raw materials analysis, technology sources along with R&D status of the key products. The study highlights the pricing structure of the product offerings of the major companies across different countries and the reasons responsible for the change. The study provides segmentation and market share in major geographical locations along with a detailed market forecast of the market in the aforementioned regions amid the period 2017-2023.

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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.

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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 of 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.
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