The Doppler Quarterly Special Edition 2019 | Page 57

Edge computing isn't new, but its cloud
element makes all of the difference.
trally stored, and, ultimately, all of the data sent back to the
centralized system, cloud or not, for permanent storage and
future processing.
Edge processing means that we replicate processing and
data storage that’s close to the source. But it’s more of a
master/slave type of architecture, where the centralized
system ultimately becomes the point of storage for all of
the data, and the edge processing is merely a node of the
centralized system.
that’s overheating, without having to check in with a central
process.
Although this latency reduction can aid all types of sys-
tems, it’s mostly applicable to remote data processing, such
as IoT devices.
Edge computing is not about snapping off parts of systems
and placing them at the edge, but rather about the ability to
look at data processing as a set of tiered components that
interact, one to another, each playing a specific role.
To accommodate edge processing, we need to think a bit
harder about how to build our IoT systems. That means
more money and time must go into the design and develop-
ment stages. However, the performance that well-designed
IoT systems will provide to meet the real-time needs of IoT
will more than justify the added complexity. The data that’s processed and stored at the edge typically
only resides there temporarily. It’s ultimately moved to cen-
tralized processing, such as a public cloud, at certain inter-
vals. That central location’s copy becomes the data of
record, or the single source of truth.
I suspect that computing at the edge architecture will
become more popular as IoT becomes more popular. We’ll
get better at it, and purpose-built technologies will start to
appear. Computing at the edge of an IoT architecture is
something that should be on your radar, if IoT is in your
future. Don’t do edge computing unless you have a specific need
for it. Edge computing is a specialized approach to solving
specialized problems. Enterprises are often guilty of adopt-
ing technology just because it’s mentioned more than once
in the tech press. But doing so will cost you more money
and add risk — and edge computing falls into this
category.
A Few Key Points to Remember
Edge computing is about putting processing and data near
the end points. This saves the information from being trans-
mitted from the point of consumption, such as a robot on a
factory floor, back to centralized computing platforms, such
as a public cloud.
The core benefit of edge computing is to reduce latency,
and, as a result, increase performance of the complete sys-
tem, end to end. Moreover, it lets you respond to critical
data points more quickly, such as shutting down a jet engine
So, What does this All Mean?
Edge computing is a tactical way to solve the latency issues,
built upon many tried-and-true architectures of the past.
However, what’s new is the element of the cloud, and the
ability to leverage edge systems as if they were centralized.
The new cloud element is bringing new relevance to edge
computing.
Written by David Linthicum, former SVP, Cloud Technology
Partners (CTP) and currently Chief Cloud Strategy Officer,
Deloitte
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