EDITOR’S QUESTION
of raw data onsite before sending it, in
a more refined state, efficiently to the
central data centre.
Edge Computing brings with it the need to
deploy many micro data centres of varying
sizes and a platform that can scale in both
directions to accommodate businesses
digitalisation needs.
Essentially, a good Edge deployment can be
looked at as a micro data centre combined
with intelligent automation. Data centre
functions such as compute, storage,
backup, disaster recovery and application
virtualisation can be consolidated into
a single, integrated platform – this is a
hyperconverged infrastructure.
JEFF READY,
CEO, SCALE
COMPUTING
ccording to a study from
IDC, 45% of all data
created by IoT devices
will be stored, processed,
analysed and acted
upon close to, or at, the
edge of a network by 2020. So, as IoT and
the growing global network of sensors
add more data than the average cloud
has ever had to handle, Edge Computing
will increasingly take on workloads that
struggle on hosted cloud environments.
It will move them towards more efficient
technologies for local data storage and
processing, like HCI platforms.
A
While the rolling out of new data centres
will be partly driven by the uptake of
Edge Computing, the very concept of
the traditional data centre will likely also
be re-written.
This is because Edge Computing allows
organisations to process large amounts
www.intelligentdatacentres.com
AS IOT AND THE
GROWING GLOBAL
NETWORK OF
SENSORS ADD
MORE DATA THAN
THE AVERAGE
CLOUD HAS
EVER HAD TO
HANDLE, EDGE
COMPUTING WILL
INCREASINGLY
TAKE ON
WORKLOADS
THAT STRUGGLE
ON HOSTED
CLOUD
ENVIRONMENTS.
Infrastructure silos that are difficult to
manage in a centralised data centre
become unmanageable at the Edge and
thus convergence of these into a single
platform is both efficient and cost effective.
It doesn’t always make sense to send
data all the way back to the traditional
central data centre only to be processed
and sent back to the same site where it
was generated.
Unlike full data centre implementations,
Edge Computing is small enough to
not warrant dedicated IT staff. Due to
this, the infrastructure needs to be easy
to implement and manage, and easily
connected back to the primary data centre
or even the cloud as needed.
There are exceptions to this, such as
automated video surveillance use-cases.
A network of surveillance cameras will
create a massive volume of valuable and
sensitive data every second.
To action intelligent automation in
real-time, Edge Computing devices can
harness the data collected from the
cameras remotely.
But, in order to store this data long-term,
traditional data centres still remain a big
part of the picture, as the data is fed back
to the data centre from the Edge device.
Issue 07
31