[Edge-computing] Edge Blog text

Cohen, Beth F beth.cohen at verizon.com
Mon May 24 16:35:22 UTC 2021

Folks -
Here is the cleaned up text for our first Blog.  Plenty of materials and
follow up here.

Ildiko:  I assume you will be taking it to get it posted on the Super User

Tangled Up in Edge

A Blog by the Open Infra Edge Working Group

Edge computing has been part of the emerging technology landscape for
coming up on 5 years now, yet somehow, it remains somewhat of a mystery (or
possibly just a Byzantine maze). The OpenInfra Edge Computing Group has
been working towards understanding what edge computing is and what it is
not. To demonstrate the crux of the issue, according to the telecoms and
their analysts, it is a way of delivering low latency (something that
telecom will tell you is REALLY important) to applications such as some
Industrial IoT (autonomous vehicles, UAV),
VR/AR, gaming, and telematics applications; these use cases are clearly
dependent on low latency for their performance.  On the other hand, another
way of looking at Edge is use cases such as video processing, AI/ML, IoT
monitoring for maintenance and diagnostics, where the objective is to use
limited bandwidth capacity more effectively by shifting information
processing closer to where the data is generated (the Edge).

Since defining what exactly edge is, borders on the futile, that does not
mean that there is not plenty to talk about.  The group stepped away from
creating a definition, as in our experience pinpointing exactly what
industry and analysts mean when they talks about edge computing is
rather elusive.  Far more interesting Edge topics are what is happening to
Edge adoption as the technology, use cases and tooling mature.  The working
group will be sharing our findings and thoughts on some of the more knotty
Edge issues that we have encountered, and with that, a blog is born.

The OpenInfra Edge Computing Group will be publishing a series of blog
posts to address some of the thornier aspects of edge computing as it
enters the mainstream adoption cycle. We will focus on the far more
interesting discussion of the technology and architectures needed to
support edge workloads – in whatever form or criteria is required for the
given use case.  There is no question that there are many edge use cases,
ranging from content delivery to tracking data from IoT devices. However,
the deeper into the use cases you get, the more it becomes apparent
that there are multiple edge related efforts each with their own
definitions, architectures and requirements.  That does not mean that there
are no common criteria and features, it just shows that they are slippery
and constantly evolving, depending more on the specific industry  use
cases and perspective of the related user community ecosystem.

Some common Edge considerations that will be explored in more depth

   - *Workload latency (to end users)* – This metric can vary from under 2
   ms to orders of magnitude higher. This criteria is often most touted by
   telecom operators as being the most important factor to consider, but that
   is more a function of their strong network bias than any requirement for
   any give Edge use case.  Yes, there are use cases that are heavily
   dependent on low latency and they are worthy of more exploration

   - *Network Transport Considerations* – How does the underlying transport
   affect use cases and the thinking about Edge?   This is a rich area to dig
   into as it has been somewhat overlooked. In short, it is much harder to
   actually manage in real life so to speak.

·         Edge should be transport agnostic, so why is it not?

·         MEC/Edge/5G are not the same thing at all, how did they get so

   - *Where are my Edge workloads?* -- Where are the workloads and how are
   they moved around on the Edge and between the Edge and
   Center -- some workloads will need to be located at the edge for reasons of
   reducing backhaul and latency to varying degrees, while others can be moved
   between Edge and Center to offload from Edge or the Center.  Determining
   the best option for a given use case can be tricky.

   - *How do constraints affect Edge architectures?* – One major criteria,
   which is often overlooked is that Edge, by its very nature, is defined by
   the constraints set by its environment and infrastructure.

·         *Edge Infrastructure and Platform issues* -- There is wide
variability in infrastructure specs, hardware and tooling. Some factors
that affect deployments include:

·         Node Size: from single CPU to multiple racks (e.g., hyperscalers)

·         Does Edge require special hardware, such as accelerators?

   - *Does Edge work when multi-clouds are required? *– Can the Edge
   support multiple platforms or does that quickly become a nightmare of
   mismatched tools and bad integration?

   - *Day 2 Operations of Edge deployments* – When a deployment can range
   from 10s of sites to thousands or even millions if you count IoT devices as
   Edge, how does deployment scale affect architecture, management and
   application decisions?


[image: Verizon] <http://www.verizon.com/>

*Beth Cohen*
*DMTS - *NFV/SDN Network Product Strategy
Verizon Business Group
M 781.434.8553

[image: Facebook] <http://www.facebook.com/verizon>  [image: Twitter]
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