INTELLIGENT DATA CENTRES
Finding the right datacentre
model for your business
How do datacentre managers decide when and how to evolve their datacentres?
Naturally, there are pros and cons to each datacentre model says James Young, Director of
CommScope's Data Center Practice in Asia Pacific.
T
here’s no question: the datacentre
needs change as business
applications change direction,
grow or die off. Managers can align their
datacentre capacity, choosing to stay with
their own on-site capacity or migrate all of
their applications to a public, shared cloud.
Some may also choose to rent space in a
multi-tenant datacentre (MTDC), moving
away from their own facilities. There’s
also a happy medium in which businesses
mix all of these alternatives into their
own unique blended solution. So how do
datacentre managers decide when and how
to evolve their datacentres? Naturally, there
are pros and cons to each datacentre model.
On-site datacentres
In this scenario, managers control their
datacentre at their own location. An on-site
datacentre improves efficiencies for some
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business needs. Of course, it also carries
maintenance requirements. With no crystal
ball as to what will happen in the future,
it’s more difficult to scale this investment
up or down: guess wrong and the cost of
this alternative can be much higher than
other choices.
All of the activity around cloud
computing makes it seem like on-site
datacentres are dinosaurs, but there are a
couple of different reasons why companies
choose to own their own datacentres. For
example, some companies have static
requirements and perform a significant
amount of processing on an ongoing basis,
and they have invested in the datacentre
capacity to do just that. Over time, they
might make changes to the datacentre, but
it ends up being more expensive to go into
a leased facility or into the cloud unless
there’s a good reason to do it, such as
changes in operations or technology.
Insurance companies and banks,
for example, have been using the same
applications for a long time; they’re part
of the organisation’s core capabilities and
are considered to be a strategic advantage.
There are also companies that work with
large data sets, like oil and gas firms.
Moving those large data sets around to
different locations – like into the cloud – is
very expensive and time-consuming.
Also, many enterprise workloads aren’t
built or designed for cloud or can’t be
virtualised, such as applications written in
COBOL for mainframes. Changing those
applications and replicating that software
in a different environment is a very large
and expensive undertaking. At some point,
of course, legacy applications such as
this will end up being rewritten to run in
virtualised or cloud-native environments
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