Businesses can harvest analytics by using
sensors at the edge of the network explains
Gartner’s Santhosh Rao.
any digital business projects
create data that can be
processed more efficiently
when the computing power is close to the
person generating it. Edge computing
solutions address this need for localised
computing power. IT infrastructure and
operations leaders tasked with managing
these solutions should understand the
associated business value and risks.
Gartner defines edge computing as
solutions that facilitate data processing at
or near the source of data generation. For
example, in the context of the Internet of
Things, the sources of data generation are
usually things with sensors or embedded
devices. Organisations that have embarked
on a digital business journey have realised
that a more decentralised approach is
required to address digital business
infrastructure requirements. As the
volume and velocity of data increases, so
too does the inefficiency of streaming all
this information to a cloud or data centre
for processing. Edge computing serves as
the decentralised extension of the campus
networks, cellular networks, data centre
networks or the cloud.
Currently, around 10% of enterprise-
generated data is created and processed
outside a traditional centralised data
centre or cloud. By 2022, Gartner predicts
this figure will reach 50%.
Edge computing solutions can take
many forms. They can be mobile in a
Santhosh Rao, Research Director, Gartner.
as solutions that
the source of
vehicle or smartphone, for example.
Alternatively, they can be static, such
as when part of a building management
solution, manufacturing plant or offshore
oil rig. Or they can be a mixture of
the two, such as in hospitals or other
medical settings. The capabilities of edge
computing solutions range from basic
event filtering to complex-event processing
or batch processing.
A wearable health monitor is an
example of a basic edge solution. It
can locally analyse data like heart
rate or sleep patterns and provide
recommendations without a frequent
need to connect to the cloud.
More complex edge computing
solutions usually involve gateways.
In a vehicle, for example, an edge
solution may aggregate local data from
traffic signals, GPS devices, other vehicles,
proximity sensors and so on, and process
this information locally to improve safety
More complex still are edge servers,
such as those that are part of next-
generation 5G mobile communication
network architectures. Servers deployed
in 5G cellular base stations will host
applications and cache content for local
subscribers, without having to send traffic
through a congested backbone network.
In especially complex applications,
edge servers can form clusters or micro
data centres where more computing power
is needed locally. Examples can be found
in offshore oil rigs and retail outlets.
As with all rapidly evolving
technologies, evaluating, deploying and
operating edge computing solutions has its
risks. Risks come in many forms, but a key
one relates to security.
Using edge computing particularly
for IoT, exponentially increases the
surface area for attacks. A nascent vendor
landscape compounds this risk. Unsecure
endpoints are already used in distributed
denial-of-service attacks or as entry points
to core networks.
Another concern is that the cost
of deploying and managing an edge
computing environment can easily exceed
the project’s financial benefits. Moreover,
projects can become victims of their own
success; scalab ility can become a serious
issue as IoT endpoints proliferate.
Edge computing has enormous
potential to enable digital initiatives
supported by IoT, but I&O leaders need to