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.
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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.
Existing Enterprise Data Center
as a Bottleneck: Think Woods Hole
Viewed From The Cockpit: The Converging And Diverging Channels Can
Look Like A Random Scattering Of Reds And Greens
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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?”
According to Susan Eustis,
principal author of the study, “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 WinterGreen Research
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.
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