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Extending open source and
hybrid cloud to drive OT
transformation
John Archer
Senior Principal BDM - AI/Edge
archer@redhat.com
Future Oil & Gas
Nov 16-17, 2021

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Source - https://www.ford.com/trucks/f150/f150-lightning/2022/

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Scope 3 Risk is key to Energy Transition
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Source - http://www.carbon4finance.com/article-scope-3/

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OS-Climate - Data Commons

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Action Plan? How to prioritize?
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Condition Models, Preventative Maintenance, Consumption trends,
Feedstocks
Border Taxes, Pass the Carbon Tax down to customers
Change business lines with Renewables, DER, EV, Storage, Biofuels,
Hydrogen, Ammonia
What is my board thinking? End to end Process impacts
Today this is all in silos, difficult to analysis and culturally and/or
security sensitive in many organizations

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Red Hat OpenShift: Innovation without limitation
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Cloud-native
Internet of things
Digital
transformation
Containers
DevOps
Open organization
Open source communities
Kubernetes
Hybrid cloud
Machine learning
AI
Innovation
Security
Automation
business innovation
Every organization in every geography and in
every industry can innovate and create more
customer value and differentiation with
open source technologies and an open culture.
Big ideas drive...
5G

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Red Hat OpenShift: Delivering innovation without limitation
But innovating
isn’t always easy
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Innovation
Innovate at speed.
Flexibility
Flexibility to adapt to market changes.
Growth
Grow new customer experiences
and lines of business.

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Red Hat industrial edge
Open Source Initiatives around Industrial Edge Computing
Collect and focus the best ideas
A global alliance solving critical
manufacturing challenges
LF Energy is an open source
foundation focused on the power
systems sector
A standards-based, open, secure, and
interoperable process control architecture
Open Source data platform
for the energy industry
The interoperability standard for
secure and reliable information
exchange in industrial automation
Powers the world’s leading
commercial IoT solutions
A framework of open source software
components to build platforms that
support the development of Smart
Solutions faster, easier and cheaper
The cross-vendor open source
connectivity solution for Smart
Factories and Smart Products
We share the vision of a continuous data
exchange for all contributors along the
automotive value chain

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Data in a large enterprise
Data silos
Slow data access puts project at risk
Legacy tech & poor automation
Error-prone, manual process unacceptable in a
modern event-driven environment
Lack of cross-team collaboration
Demands person-in-the-loop with institutional
knowledge. Analysts assemble personal, stale
datasets
No Data Governance process
Without a centralized understanding of company
assets, few models are capable of deployment
Energy organization data challenges
Months of effort Months of effort Months of effort
Sources
Subject Matter
Experts
Data Scientists
Geologists
Geophysicists Models
?
SEISMIC
WELLBORE
FLUIDS
CORE
ANALYSIS
PIPELINE
Business has
a question
Business gets
an answer
80%

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Data in a large enterprise
Silos still exist
Data Warehouses & Lakes leave data in original form.
Little change in time to result
Still need SMEs, manual process, no governance, etc.
Consumers handle data
preparation
Data consumers still responsible for transformations
Lacking business-based data
model
Data should be transformed into the form the
business needs and understands. Automation
required forces global understanding as teams self-
service based on their needs
Consolidating data isn’t sufficient
Sources Warehouse / Lake Data Solutions Consumers
APIs
Intelligent
Applications
Events

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Red Hat industrial edge
The Need
“As shop floor IT person, I want to get rid of all the different bespoke and customized
hardware solutions for PLCs, SCADA, HMI, MES etc. They are expensive, inflexible and
hard to maintain.
I want a single unified software platform based on standard hardware, so I can easily add
new features and functions defined purely in software, even from different vendors.
That would help me to improve the efficiency and agility of my plant”

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Red Hat industrial edge
Our focus use cases
● Standardized distributed operations
● Modernized application environments
(OT and IT)
● Modernized network infrastructure
● Automation/integration of
monitoring & control processes
● Predictive analytics
● Production optimization
● Supply chain optimization
Digital Enterprise Edge
Extend cloud/data center approaches
to new contexts / distributed locations / OT
Operations Edge
Leverage edge/AI/serverless
to transform OT environments
Industrial
Edge
● Aggregation, access and far edge
● Manages a network for others
○ Telecommunications Service Providers
○ Creates reliable, low latency networks
Provider Edge
Network and compute specifically
to support remote/mobile use cases
Provider
Edge
Enterprise
Edge
● Vehicle edge (onboard & offboard)
○ In-vehicle OS
○ Autonomous driving,
Infotainment up to ASIL-B
○ Quality management
Connected Product Edge
Create new offerings or customer/
partner engagement models
Vehicle
Edge

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Central data center
Cluster management and application
deployment
Kubernetes node
control
Regional data center
Edge
CONFIDENTIAL designator
Single node
edge servers
Low bandwidth or
disconnected sites.
C W
Site 3
W
Site 2
C
C W
Site 1
Remote worker
nodes
Environments that are
space constrained
3 Node Clusters
Small footprint with
high availability
Legend:
C: Control nodes
W: Worker nodes
Red Hat Edge Topologies

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S W
Edge clusters
(3+ node HA)
S
W
Remote
worker nodes
S W
Single node
edge servers
Small footprint
device edge
An image-based deployment
option of RHEL, that includes
transactional OS updates,
intelligent OS rollbacks and
intended for, but not limited
to, containerized applications
Red Hat OpenShift
deployment on a single
node (supervisor + worker)
with resources to run a full
Kubernetes cluster as well
as application workloads.
Red Hat OpenShift
supervisors reside in a
central location, with reliably-
connected workers distributed
at edge sites sharing a control
plane.
Red Hat OpenShift
supervisors and workers
reside on the same node.
High Availability (HA) setup
with just 3 servers.
Our edge platforms
Consistent operations at scale

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Overview of Red Hat OpenShift Data Science
Key features of Red Hat OpenShift Data Science
Combines Red Hat components, open source
software, and ISV certified software available
on Red Hat Marketplace
Increased capabilities/collaboration
Model outputs are hosted on the Red Hat
OpenShift managed service or exported for
integration into an intelligent application
Rapid experimentation use cases
Available on Red Hat OpenShift Dedicated
(AWS) and Red Hat OpenShift Service on AWS
Cloud Service
Provides data scientists and intelligent
application developers the ability to build, train,
and deploy ML models
Core data science workflow
Addressing AI/ML experimentation and integration use cases on a managed platform

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And the services and partners to guide you to success
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RED HAT OPEN INNOVATION LABS
RED HAT CONTAINER ADOPTION PROGRAM
CATALYZE INNOVATION
IMMERSE YOUR TEAM
EXPERIMENT
Rapidly build prototypes,
do DevOps, and be agile.
Bring modern application
development back to your
team.
Work side by side with experts
in a residency-style engagement.
FRAMEWORK FOR SUCCESSFUL CONTAINER
ADOPTION AND I.T. TRANSFORMATION
Mentoring, training, and side-by-side collaboration
SYSTEM INTEGRATORS
Or work with our ecosystem of certified systems integrators, including…
Red Hat OpenShift: Delivering innovation without limitation

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Lots of data is collected,
but finding and preparing
the right data across
multitude of sources with
varying quality is difficult
Readily usable data
lacking
Lack of key skills make it
difficult to find and secure
talent to maintain
operations
Talent
shortage
No rapid availability of
infrastructure and software
tools slows data scientists
and developers
Unavailability of
infrastructure & software
Unable to implement
quickly due to slow,
manual and siloed
operations
Lack of collaboration
across teams
Slow CPU
processing
Data sets continue to
increase in size but CPUs
are not getting faster and
not able to parallelize
processes well
AI/ML Key Execution Challenges

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Overview of Red Hat OpenShift Data Science
Our approach to AI/ML
Data as the foundation
Represents a workload
requirement for our
platforms across
hybrid cloud.
Applicable to Red Hat’s existing
core business in order to increase
open source development and
production efficiency.
Valuable as specific services
and product capabilities,
providing an intelligent
platform experience.
Lets customers build
intelligent apps using
Red Hat products and our
broader partner ecosystem.
Hybrid cloud Open source efficiency Intelligent platforms Intelligent apps

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Overview of Red Hat OpenShift Data Science
Depth and scale without lock-in
Complement common data science
tools in Red Hat OpenShift Data
Science with other Red Hat products
and cloud services
Partner ecosystem
Red Hat portfolio and services
Access specialized capabilities by
adding certified ISV ecosystem
products and services from
Red Hat Marketplace
Managed cloud platform
Deployed on Red Hat OpenShift and
managed on Amazon Web Services
providing access to compute and
accelerators based on your workload
Capabilities delivered through the combination of Red Hat and partner ecosystem

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Edge is bringing transformation to operational technology
Red Hat industrial edge
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

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RED HAT+IBM CONFIDENTIAL. For internal use only.
100+ Red Hat OpenShift certified operators
Red Hat Marketplace
Application Runtimes
Customer Code
{ | }
AI / ML
Databases & Big Data
Networking
Security
Monitoring & Logging
DevOps Tools
Storage

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Edge computing simplified deployment
Validated Patterns : Simplifying the creation of edge stacks
Bringing the Red Hat portfolio and ecosystem together - from services to the infrastructure
Config as code From POC to production
Open for collaboration
Highly reproducible
Go beyond documentation using
GitOps process to simplify deployment
So that you can scale out your
deployments with consistency
Ensure your teams are ready
to operate at scale
Anyone can suggest improvements,
contribute to it

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Red Hat is the world’s leading provider of enterprise
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Red Hat a trusted adviser to the Fortune 500.
Thank you
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