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Edge computing with Red Hat OpenShift

Edge computing with Red Hat OpenShift

The team will walk through the initial release of the Industrial Edge Blueprint which is a multi-product integration of a real world implementation based on OpenShift at the edge.

Red Hat Livestreaming

December 10, 2020
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  1. 1
    Edge computing with
    Red Hat OpenShift
    Mark Schmitt
    Principal Product Manager
    Nick Barcet (@nijaba)
    Sr. Director Technology Strategy

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  2. The content set forth herein is Red Hat is provided for discussion purposes only and is
    subject to change for any or no reason. Any forward looking statements or content and
    does not constitute in any way a binding or legal agreement or impose any legal
    obligation or duty on Red Hat.
    2
    DISCLAIMER
    2

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  3. Traditional
    N-Tier Apps
    Cloud Native
    Microservices
    ISV Packaged
    Apps
    Physical Virtual Private cloud Public cloud
    Red Hat Enterprise Linux
    Edge cloud
    Red Hat OpenShift
    Red Hat Open Hybrid Cloud
    Data, Analytics
    & AI/ML
    Edge computing with Red Hat OpenShift

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  4. 4
    Topologies to meet the
    needs of different edge
    tiers
    Edge computing
    architectures

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  5. STRICTLY INTERNAL ONLY
    End-user
    premises
    edge
    Provider edge Provider or 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
    5
    Edge Tiers
    Device
    edge

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  6. Edge computing with Red Hat OpenShift
    6
    Edge gateway/
    edge server
    Small
    bare metal
    footprint
    Infrastructure
    virtualization
    Public/private
    cloud
    A consistent edge platform to meet your needs
    Develop once,
    deploy anywhere
    Meet diverse
    use cases
    Consistent
    operations

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  7. ▸ Available now
    ▸ Available now
    Edge computing with Red Hat OpenShift
    7
    Central data center
    Cluster management and application deployment Kubernetes node
    control
    Single node
    edge servers
    Low bandwidth or
    disconnected sites.
    Regional data center
    Far edge
    CONFIDENTIAL designator
    ▸ Available in 2021
    S W
    Site 1
    W
    Site 2
    S
    S W
    Site 3
    Remote worker
    nodes
    Environments that are
    space constrained
    3 Node
    Small footprint with
    high availability
    Legend:
    S: Supervisor/control nodes
    W: Worker nodes

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  8. Edge computing with Red Hat OpenShift
    8
    Managing the edge, just like the core
    Red Hat Advanced Cluster Management for Kubernetes
    Multicluster lifecycle
    management
    Policy driven governance,
    risk, and compliance
    Advanced application
    lifecycle management

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  9. Edge computing with Red Hat OpenShift
    Connect applications and data at the edge
    9
    Use Cases
    ▸ Create fast and lightweight edge
    applications.
    ▸ Connect, aggregate and transform
    data for real-time data analysis and
    associated business actions.
    ▸ Container-native capabilities for better
    operational and scalable application
    infrastructure
    Red Hat Middleware Sample Industries
    ▸ Event triggered business
    ▸ Data aggregation and real-time
    analysis
    ▸ Data aggregation for AI-models
    Financial services
    Energy
    Healthcare Manufacturing

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  10. 10
    A horizontal platform
    approach to edge
    computing
    Use cases

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  11. 11
    AI at the edge use cases
    Automotive
    Health–life science
    Manufacturing
    Energy
    Retail
    Public sector
    Patient diagnosis/treatment
    Quality assurance
    Sensor-based asset monitoring
    Digital in-store experience
    Predictive maintenance
    Edge computing with Red Hat OpenShift
    Monitoring and control

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  12. AI/ML Lifecycle and Edge Computing
    12
    Gather and
    prepare data
    Develop & train
    ML model
    Integrate ML
    models in app dev
    processes
    Deploy
    Apps & ML
    Inferencing
    ML models
    monitoring &
    management
    Execution Venue
    Data Center X X X X X
    Public Clouds X X X X X
    Edge X X X
    DataOps MLOps
    Edge computing with Red Hat OpenShift

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  13. 13
    ▸ Provides common, automated management
    across large-scale
    ▸ Lowers latency times with more distributed
    network architecture
    ▸ Uses remote worker node topology
    ▸ Deploy radio access network (RAN) functions
    where needed
    5G DU
    Access
    4G DU
    Aggregation
    5G CU
    Red Hat OpenShift runs the
    most demanding workloads
    Telco RAN use case
    Edge computing with Red Hat OpenShift
    Aggregation
    4G CU
    Telco core
    4G/5G Core
    Legend:
    CU: Centralized Unit Access: also known as far edge
    DU: Distributed Unit Aggregation: also known as near edge
    Access

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  14. 14
    Edge computing with Red Hat OpenShift
    Solution Blueprints : Simplifying the creation of edge stacks
    Bringing the Red Hat portfolio and ecosystem together - from services to the infrastructure
    Blueprint 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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  15. 15
    Industrial use case using
    AI/ML
    Solution Blueprint

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  16. Edge computing with Red Hat OpenShift
    16
    Transforming industrial manufacturing
    Capitalize on industry 4.0 technologies
    To achieve successful optimization, planning and control of production
    Transition their IT-OT environment to next generation infrastructure
    Capitalize on edge computing, AI/ML, hybrid cloud, and software-defined technology
    Optimize production at the factory floor
    Use AI/ML intelligent applications for predictive maintenance and higher quality products
    Support future operating environments
    Accelerate the designing, developing, and deploying new apps and services
    Business initiatives creating new opportunities

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  17. Use Case: Predictive maintenance of machinery
    Edge computing with Red Hat OpenShift
    Enable software-driven
    production optimization with
    full visibility
    Leverage big data & ML
    technology for traceability and
    analytics
    Declarative configuration
    management to simplify
    operations at scale
    How edge computing and AI/ML can ensure production by reducing downtime and costs
    Accelerate software
    development
    Automate configuration
    management of production lines
    Use data from the factory
    floor to react proactively

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  18. SENSOR DATA &
    INFORMATION
    19
    W
    Remote
    worker node
    Sensor Simulators
    Core HQ Data Center
    S W
    3 node cluster
    Factory #1 Factory #2
    Sensor Simulators
    MQTT MQTT
    Git
    Quay
    Eclipse Che
    GitOps
    VSCode
    Quarkus
    CODE &
    CONFIGURATION
    High Level Overview of a customer
    Ceph
    AI/ML

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  19. 20

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  20. Edge computing with Red Hat OpenShift
    21
    Solution Blueprint: Edge and AI/ML in industrial manufacturing
    Accelerating time to value using OpenShift at the edge
    Coding, simulation & deployment to production
    Container based CI/CD from data center the edge
    Automated configuration management
    Consistent roll-outs using end to end GitOps for distributed environments
    Data processing from sensors to analytics
    Open source middleware and AI/ML stacks
    ML model training and deployment to production
    Open Data Hub enabled CI/CD
    Bringing OpenShift, the
    Red Hat portfolio and
    ecosystem together
    from the core to the
    factory floor

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  21. 22
    https://youtu.be/mZ71V8RfXSw?t=315
    ● Full blueprint demonstration
    ● Stay tuned to OpenShift TV for a live demo (12/10 1PM EST)
    https://www.twitch.tv/redhatopenshift/
    ● Explore / Contribute
    Next Steps
    https://github.com/redhat-edge-computing

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  22. linkedin.com/company/red-hat
    youtube.com/user/RedHatVideos
    facebook.com/redhatinc
    twitter.com/RedHat
    Red Hat is the world’s leading provider of enterprise
    open source software solutions. Award-winning
    support, training, and consulting services make
    Red Hat a trusted adviser to the Fortune 500.
    Thank you
    23

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  23. 24
    To be used if your
    presentation as needed
    Backup Slides

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  24. Reduced downtime
    Lower OpEx and CapEx
    Lower workforce risk
    Less environmental impact
    Process control
    Environment monitoring
    Autonomous vehicles
    Edge computing with Red Hat OpenShift and ACM
    25
    Edge computing is already being looked into
    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
    Industrial use cases with AI/ML

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  25. We built Red Hat OpenShift
    so any company could thrive
    in a world of hybrid possibility
    26

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  26. We believe Red Hat can help
    27
    Hybrid cloud provides operational
    consistency & flexibility across your
    architecture - including edge
    Open source harnesses 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
    Edge computing with Red Hat OpenShift and ACM
    Portfolio comprised of
    powerful building blocks
    integrated with our partner
    ecosystem

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  27. ▸ Today
    ▸ Today
    Red Hat platforms for the edge
    28
    W
    Central data center
    S W
    S
    Cluster management and application deployment Kubernetes node
    control
    Single-node edge servers
    Low bandwidth or
    disconnected sites
    Regional data center
    Far edge
    S W
    CONFIDENTIAL , under NDA
    Remote worker nodes
    Space-constrained
    environments
    3 node Clusters
    Small footprint with
    high availability
    ▸ 2021
    Small footprint edge OS
    Memory-constrained edge
    servers/Internet of Things
    (IoT) Gateways
    ▸ Today
    Supervisor node Worker node
    S W

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  28. A common platform across hybrid, multi-cloud and edge architectures
    29
    Private cloud Public cloud
    App App App App
    Edge
    Develop once, deploy anywhere - at scale

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  29. Edge computing with Red Hat OpenShift
    Delivering consistency and flexibility
    30
    Cloud-native apps AI/ML, Functions
    Communities of Innovation | Ecosystems of Solutions
    Secure & Automated Infrastructure and Operations
    Traditional apps
    Edge Private Cloud Hybrid Multi-Cloud

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  30. 31
    Vertically integrated
    Continuous open source innovation
    Open and interoperable
    Edge computing with Red Hat OpenShift
    Two approaches to building an edge architecture
    Dedicated point solutions

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  31. Edge computing with Red Hat OpenShift
    32
    Agenda
    ▸ Business goals
    ▸ Red Hat OpenShift and edge computing
    ▸ Edge computing architectures
    ▸ Red Hat OpenShift edge computing use cases
    ▸ Demo

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  32. Business goals
    33
    ▸ Innovation
    ▸ Speed
    ▸ Flexibility
    Organizations are under pressure to offer hybrid customer
    experiences delivered by a hybrid mix of apps, deployed in
    hybrid environments, and developed by hybrid teams.
    Edge computing with Red Hat OpenShift

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  33. Edge computing with Red Hat OpenShift
    34
    The complexities of edge computing
    Need to manage up to
    hundreds of thousands nodes
    and clusters remotely
    Ensure support for a
    heterogenous hardware and
    software environments
    Provide a consistent approach
    for developer and IT
    operations teams
    Scale Interoperability Consistency

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  34. Networking
    Security
    Monitoring & Management
    Storage
    Databases
    DevOps Tools
    Application Runtimes
    Customer
    Code { | }
    AI / ML
    Big Data
    FSI Telco Application Platforms
    SIs
    OEMs
    OpenShift Partner Ecosystem

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  35. 36
    Transforming industries with edge computing
    Telecommunications
    Health–life science
    Manufacturing
    Automotive
    Retail
    Public sector
    Financial Energy Hospitality
    Edge computing with Red Hat OpenShift

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  36. Edge computing and the telecommunications industry
    A transformational opportunity
    Enable the connected economy
    Provide services to increasing number of people, devices, and things
    Deliver enhanced customer experiences
    Respond faster, increase customer satisfaction
    Create new revenue stream opportunities
    Offer cloud services to enterprises at network edge
    37
    Telehealth
    Mobile gaming
    5G
    Smart cities
    Industry 4.0
    Video
    Analytics
    Edge computing with Red Hat OpenShift

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