Review of approaches for Edge computing architecture with emphasis on improved security for container workloads collecting telemetry from Industrial IoT environments

1. 1
Leveraging IoT as part of
your digital transformation
John Archer
Chief Architect Energy
Red Hat

2. John Archer
Chief Architect Energy
● Edge and Data Science
● Upstream Data Management
● Energy Trading
● DoD/Healthcare/eCommerce/Legal
● OSPO/OSS Strategy
● Standards & Energy Communities
● Nascent Woodworker
● Award winning BJCP 20A Beer

3. 3
The big themes we’re hearing from customers now
Faced with massive
scaling and capacity
demands
Business has dropped off
and our existing business
model is under threat
Working to protect our
current business model
and prepare for future
Reduce costs and liabilities
and maintain business
viability
Respond in an agile way to
market conditions
Accelerate the business
without risking stability

4. 4
How does my organization become
more resilient?

5. 5
It’s creating some knee jerk reactions
“Put it all in the cloud even faster!”

6. of complex large-scale
change programs
FAIL.*
COMMON PITFALLS:
■ Lack of employee engagement
■ Inadequate management support
■ Poor or nonexistent cross-functional collaboration
■ Lack of accountability
*Research by McKinsey

7. 64%
Transparency
69%
Adaptability
Inclusivity
73%
Collaboration
70%
79%
87%
Transformation
leaders are open.
Key cultural characteristics
of transformation:
All respondents Digital transformation leaders
Percentage of respondents who said each
of the following cultural characteristics
was very important in enabling digital
transformation in their organizations.
60%
70%
Source:
(n=734) Harvard Business Review, sponsored by Red Hat. "Reassessing digital transformation," November 2018.

8. 8

9. What happened in Oldsmar, FL?
9
Hacker came in through remote desktop software TeamViewer .
Adjusted the levels of sodium hydroxide (lye) from 100 ppm to over 11K ppm.
Operator was only aware of the activity due to a cursor movement on his screen.
Operator adjusted the level back down - no one was hurt.

10. 10
Source - NY Times - A Cyberattack in Saudi Arabia Had a Deadly Goal. Experts Fear Another Try.

11. Firmware attacks on the rise
11
Source - DarkReading.com
Russia Sednit deployed first firmware rootkit back in 2018
Microsoft Security Signals reports that 83% of businesses have been hit with a firmware
attack in the last two years.
73% of these attacks have been disruptive to the business
Only 29% of organizations have allocated security budget to protect against firmware attacks
“When you start to talk about IoT and embedded devices, firmware looks even worse because there is
no standardized update mechanisms [and] you're dealing with multiple different hardware and software
ecosystems, so that problem is just compounded"
Microsoft Operating System Security Director - David Weston

12. 12

13. Shared responsibility model at the end of the day= security is your problem
13

14. 14

15. Who owns your personal IoT data?
15

16. 16

17. Red Hat OpenShift’s road to the network edge
17
The open hybrid cloud now extends to the edge
Any workload, any footprint, any location
App App App App
Physical Virtual Private cloud Public cloud
Server edge Enterprise edge Provider edge National core
Regional edge

18. 18
Put applications
anywhere
Act with speed and agility
and adapt to the needs of
the business
Edge computing with Red Hat
Eliminate operational
challenges
Provide new solutions for a
variety of distributed
application environments
Developer velocity Operational agility
Address new
opportunities
Drive innovation, increase
productivity, and offer better
products and services
Business innovation

19. Red Hat OpenShift’s road to the network edge
19
The complexities of edge computing
Need to manage 100s to
hundreds of thousands
nodes and clusters remotely
Ensure support for a
heterogenous hardware and
software environment
Provide a consistent
developer and IT operations
and processes
Scale Interoperability Consistency
Protect and patch remotely
while guarding against
physical and full stack attacks
Security

20. Trusted execution environments Unikernels
Hardware attestation
Blockchain
Service mesh
Partitioning hypervisors
Edge-enabled distributed platform
Data and artificial intelligence
Event-triggered business logic
Edge computing with Red Hat
20
Edge computing is part of a broader evolution of cloud native offerings
Common
requirement
patterns
across
industries
Heterogeneous clusters
Quantum computing
RISC-V
Secure multi-party computing FPGAs
x

21. Edge computing with Red Hat
21
Edge computing is already happening
Reduced downtime
Lower OpEx and CapEx
Lower workforce risk
Less environmental impact
Process control
Environment monitoring
Autonomous vehicles
21
Energy
Manufacturing
Telecommunications
Private Networks
vRAN
Distributed Core
Predictive maintenance
Factory automation
AR + remote export
Use cases
Benefits
Better user experience
Scale to meet demand
Greater network flexibility
Improved resilience
Reduced downtime
Increased productivity
Longer asset lifetime
Improved factory safety
… and many more
Industrial use cases with AI/ML

22. Challenge: Stay competitive by reducing the time and cost required to develop
autonomous vehicles, and transform from a “car maker” to a “mobility provider”.
22
Solution
High Performance D3 platform to gather and analyze massive amount of
data from the global BMW test fleet for autonomous driving
Why Red Hat
Relationship, Technology, Open Source principles
Result
Faster autonomous driving development: BMW manufacturing R&D teams
are now able to collect, store, and analyze vehicle sensor data in seconds
rather than days or weeks
Products & Services
Red Hat OpenShift

23. USE
CASES
BMW Group High Performance D3 Platform
23
Source: BMW Press announcement -
https://www.press.bmwgroup.com/deutschland/article/detail/T0293764DE/die-neue-bmw-group-high-performance-d3-plattform-data-driven-development-fuer-das-autonome-fahren?language=de
Platform Figures (Summer 2019)
▸ 1.500TB raw data collected per day
▸ >230 PB platform capacity
▸ >100.000 cores and > 200GPUs
▸ HiL (Hardware in the Loop) Stations reprocess up to 50 PB in 2 weeks
▸ Data transfer over 96 x 100 Gbps fiber reaches ~ 3,75 Terabit/s

24. 24
Success Story: link Video (public)
Overview: Win the race to autonomous driving with Red Hat and DXC Technology
Global automotive group races to automated driving with data platform
Win the race to autonomous driving with Red Hat and DXC Technology
USE
CASES

25. Powered by
25
EDGE/IoT USE CASES
Solution description:
https://www.redhat.com/cms/managed-files/pa-race-to-autonomous-driving-dxc-overview-f21446pr-202004-en.pdf
Solution architecture R&D analytics platform

26. 26
Vertically integrated
Continuous open source innovation
Open & interoperable
Edge computing with Red Hat
Every organization faces a decision about their future
Dedicated point solutions

27. 27
Edge is bringing transformation to operational technology
Edge computing with Red Hat
OT
Software-defined
everything
▸ Real-world, real-time interaction
▸ Convergence of planning & execution
▸ Implementation of data-driven insights
▸ Integration of formerly closed systems
IT
Software-defined
platforms
▸ Standard, scalable hardware
▸ Cloud-native applications
▸ Flexibility and agility
▸ Convergence of data platforms

28. STRICTLY INTERNAL ONLY
Enabling platform for edge(s)
Edge Computing
Telco
5G Edge
Enterprise
Remote Office
Industrial
Manufacturing
Retail
Connected Sensors
And more ...
Public Sector
Disconnected Car
Zero-touch provisioning
Multi-cluster management
Small footprint
Scale
Security (physical, SW)
Automation of operations
Middleware enablement (ML, IoT, ...)
Network disruption tolerance
And more...
80% of edge use case requirements

29. STRICTLY INTERNAL ONLY
End-User
Premises
Edge
Provider Edge Provider/Enterprise Core
“last mile”
FOOTPRINT
SCALE
Red Hat’s focus
Edge
Server/Gateway
Regional
Data Center
Infrastructure
Edge
Provider
Far
Edge
Provider
Access
Edge
Provider
Aggregation
Edge
Core
Data Center
Device or
Sensor
29
Edge Tiers
* Edge computing == Fog computing (there is no real difference other than marketing)
Device
Edge

30. Edge computing with Red Hat
30
Develop once,
deploy anywhere
Meet diverse
use cases
Consistent
operations
Red Hat platforms for edge computing
Edge gateway/
edge server
Bare metal
cluster
Infrastructure
virtualization
Public/private
cloud

31. Bringing Kubernetes to the Edge
Addresses the needs of edge use cases including telco,
industrial manufacturing, AI/ML, ROBO, etc...
Red Hat Advanced Cluster Management for
Kubernetes for core to edge management
Full Kubernetes capabilities in
a 3-node clusters in OCP 4.5
For environments requiring a smaller footprint with remote
worker nodes support coming (currently dev preview)

32. Edge computing with Red Hat
32
Red Hat is focused on four edge architectures
A small footprint deployment
with long-lived release
support. Key building blocks
are Red Hat Enterprise Linux
and a container runtime.
Red Hat OpenShift
deployment on a single box
(master + worker) with
resources to run full
Kubernetes cluster as well as
application workloads.
Red Hat OpenShift masters
and workers reside on the
same node. High availability
(HA) setup with 3 servers.
Red Hat OpenShift masters
reside in a central location,
with reliably-connected
workers distributed at edge
sites sharing a control plane.
Small footprint device edge Single node edge servers Remote worker nodes Edge clusters (3+ node HA)
M
W
M W
M W
Coming soon

33. Red Hat portfolio helps complete the ML architecture
33
Software-defined
Infrastructure
Data Services - Databases (SQL, NoSQL, etc.), Data Lake, etc.
Compute Acceleration (GPU, FPGA, TPU)
Hybrid, Multi Cloud Platform with self service capabilities
ML Software tools
Set
goals
Gather and
prepare data
Develop ML
model
Deploy ML models
in app dev process
Implement
Apps & inference
ML models
monitoring &
management
CONNECTING AI ILT...

34. Edge computing with Red Hat
34
AI/ML
workload
-
Manufacturing

35. 35
Source - Open Data Hub - https://opendatahub.io/
Open Source Projects - I’m grokking and loving
Open Data Hub is a meta-project that integrates open source projects into a practical solution. It aims to foster
collaboration between communities, vendors, user-enterprises, and academics following open source best practices. The
open source community can experiment and develop intelligent applications without incurring high costs and having to
master the complexity of modern machine learning and artificial intelligence software stacks.

36. RED HAT CONFIDENTIAL
Open Data Hub (ODH) is an open source
project that provides open source AI
tools for running large and distributed
AI workloads on OCP.
Reference architecture for how to do
Data Science on top of OpenShift. The
open source community drives
collaboration across Red Hat products,
IBM, Open Source projects, and partner
products.
Sales tool to drive customer
conversations around well understood
best practices across products,
ecosystem, and consulting
36
Open Data Hub - Data and AI Platform for Hybrid Cloud

37. 37
Source - https://skupper.io/index.html
Skupper - Multicloud communication for Kubernetes
● Deploy a multi-cluster network
● Access data in a private cluster
● Multi-cluster microservices
applications
● Transparent HTTP/1.1, HTTP/2, gRPC,
and TCP communication
● Secure access from the public cloud
to private cloud services without
VPNs

38. Partner and Community Ecosystem Momentum
130+
Certified Operators
50+
ISVs on Red Hat Marketplace
20+
Market Segment ISV webinars
7000+
specialists enabled at GSIs
New solutions with technology partners
600+
OpenShift Commons Member Orgs

39. 39
Maturity
Level
Acceleration
Basic Guardrails and Strategy in place for Application Lifecycle
Management, Automation, CI/CD, Security, Source Control and APIs
Work with Infrastructure teams to help adoption of
Infrastructure as Code practices
Build Communities of Practice within customers via enablement workshops
and hand on learning hackathons. OpenShift adoption starts.
Federated Clusters, Microservices Architectures, AI/ML and
CoPs become self sufficient run by customers
Self Sufficient teams delivering iterative
changes regularly into production
Developers start consuming LEGACY infrastructure services on Openshift via
Ansible Tower API, and Infrastructure teams use OCP to host tools
Stage 1
Infrastructure as
Code (Ansible)
Stage 3
Event Streaming,
ACM, ACS,
DataScience and
Edge
Stage 2
DevOps
(Ansible/OCP)
Stage 4
COTS and Red Hat
applications
How to get moving with Red Hat

40. Federal Cybersecurity IoT
40

41. We believe Red Hat can help
41
Hybrid cloud provides
operational consistency across
your architecture
-all the way to the edge
Open source brings the
power of collaboration to
drive innovation and
interoperability
If edge computing is going to be a
realistic future for enterprise IT,
it needs the hybrid cloud and open
source to thrive.
Paul Cormier
Red Hat President and CEO

42. linkedin.com/company/red-hat
youtube.com/user/RedHatVideos
facebook.com/redhatinc
twitter.com/RedHat
Contact me at
archer@redhat.com
@archerj
Thank you!
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