//ABSTRACT Edge computing is rapidly on the rise. In this Meetup, we will explore the business drivers, technological changes, and global trends that are making edge computing the next must-have infrastructure. We will discuss the challenges that make edge computing unique in relation to cloud and data center. We will finish our exploration with real-world use cases from a variety of industries, showing how edge computing results in immediate business opportunities that you can leverage. //SPEAKER Kilton Hopkins, Edgeworx

1. Exploring the Trend Toward the Edge

2. Farah (Giga) Papaioannou
Co-Founder & President
3x Degrees from Stanford
VC at Amplify, DCVC, Valhalla Partners
Product Management + M&A @ HPE
First investor in SolidFire, Qumulo
Eclipse Board of Directors
Who Am I?

3. The Edge is Different

4. Connectivity & Bandwidth
Cloud:
High - Speed
vs.
Edge:
Limited/
Sporadic

5. Cloud:
Homogeneous/
Virtualized
Edge:
vs.
Heterogeneous/
Targeted
Compute Hardware

6. Security
Publicly
Accessible
Edge:
vs.
Physical Security/
Firewalls
Cloud:

7. Power
Cloud:
Massive Power
Consumption
vs.
Edge:
Finite/Scarce

8. The Edge is Big

9. We are undergoing a transformation
MAINFRAME
CLIENT/SERVER
CLOUD
Decentralized
Centralized
EDGE

10. The Edge Market is Vast
IDC estimates that only 1% of all data
generated at the Edge will be processed,
but that 20% actually has value.
Powering that 1-20% will dwarf all other
markets opportunities.
The Edge is BIG
50B
SMART “THINGS”
CONNECTED BY 2025
163ZB
TOTAL DATA GENERATED
A YEAR BY 2025
$19.4B
SIZE OF EDGE MARKET
BY 2023
35.4%
CAGR OF EDGE MARKET
THROUGH 2023

11. The Edge is IOT

12. Cloud to Edge
Continuum
#IOT
EDGE

13. The Edge is Hard

14. Running REAL software
at the Edge is HARD!
• The roll out of Edge computing devices has begun
• Security, Connectivity, Latency, Storage and Power are problems
• Traditionally, every device had a single vertical siloed purpose
• This leads to inflexible devices and applications that are costly to deploy and manage
• Existing Edge software solutions enforce bringing data back to the Cloud
• This legacy architecture is too costly and too slow with the volume of edge data

15. WANT:
Platform
Stability

16. Vertical Silos
GET:

17. Redneck
Architecture!
GET:

18. Seamless Dev
Experience
WANT:

19. GET:
Homebrew
Computing Club

20. What Developers Need

21. Patterns for the edge require intelligent, connected, managed and secure.
B.Y.O.E.
(Bring Your Own Edge)
People should be able to bring any
hardware and turn it into a compute
platform that can run any application
or microservice at the Edge.

22. Run any software, on any hardware
Remotely deploy and run apps
Add, update, and roll-back microservices. Edgeworx
monitors the health and resources for you so you can
operate your edge effectively at scale.
Write code once run it anywhere
Common compute platform allows you to run to the
same code on any hardware.
Build for the Edge as easy as for the Cloud
Our container-based architecture allows you to
leverage any language, framework, and SDK.

23. Edgeworx ioFog Engine turns
your compute hardware into an
intelligent edge device capable
of remotely deploying and
managing microservices.
Rapidly create Edge Compute
Networks between all of your
devices. Policy driven and geo-
fenced data routing. No trips to
the cloud required and no more
VPNs and NAT layers to deal
with.
Pure Edge Security creates MicroVPNs
overlays between all nodes, utilizing
dynamic cryptographic signing to
secure all traffic. Real time attestation
of microservices and automatic
identification and quarantine of rogue
nodes.
Intelligent Connected Secure
Patterns for the Edge
Edge Management gives you
command over any number of
edge compute devices.
Everything from provisioning
and policies to health
monitoring and alerting is all in
one place.
Managed

24. The Edge is Everywhere

25. Telco
Wired Use Case
ioFog enables deployment of
microservices to Consumer
Broadband devices

26. Telco
ioFog in a Wired Topology

27. Telco
Smart City

28. Hospitality
Gym of the Future

29. Let’s dig in…

30. AUTOMATED FIRE DETECTION
Challenge
Fire can be a real hazard when drilling
for oil or gas, causing damage to
expensive equipment, requiring costly
shutdowns
Edge Solution
Run machine learning algorithms on smart
cameras to proactively identify fires and
smoke in remote environments

31. EMISSIONS MONITORING
Challenge
Identify harmful gas emissions, reduce
workplace hazards and improve safety
Edge Solution
Collect wide-scale sensor and video data,
analyze in real-time and take immediate
action to avoid escalating problems

32. HARD HAT DETECTION
Challenge
Hard hats are a requirement for
protection of many workers in
dangerous locations
Edge Solution
Run AI on smart cameras to identify workers
not wearing a hat, and prevent workplace
accidents and increase safety

33. PIPELINE MONITORING
Challenge
Pipeline maintenance via “walk downs” rely on
unreliable humans, timing and experience
Edge Solution
Run machine learning to identify faults, listen
for noise level changes or identify vibrations
to automate shut down or alert for
inspection. Seconds can count in response
times!

34. LIFE EXTENSION OF EQUIPMENT
Challenge
Offshore drilling equipment is massively
expensive to install, service and replace
Edge Solution
Real-time collection of sensor information for
machine learning and predictive inspection
enables planned interventions of 1 day, not
unplanned shutdowns of 30 days

35. THERMAL MONITORING
Challenge
Offshore drilling is highly complex. Often
small variations in data can predict
failures.
Solution
Collect, analyze and run predictive AI to look
for thermal fluctuations that indicate a flaring
event, reducing costly shutdowns and
improving drilling safety

36. Any Questions?