Industrial Transformation calling for Next Generation of Cloud

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1 Industrial Transformation calling for Next Generation of Cloud Dr. Azimeh Sefidcon Director Research Cloud Systems and Platforms Ericsson AB Ericsson Research

2 Edge computing for industrial applications

3 Transformation in progress Traditional Industries Digitize & Mobilize Transformed Industries Cloud Network Devices Applications Sara Mazur Ericsson AB

4 Edge computing for industrial applications

5 Cloud 5G Systems IoT Sara Mazur Ericsson AB Machine Intelligence Security

6 Industrial Cloud Context Private Cloud Infrastructure Central Cloud Infrastructure: Central Cloud Infrastructure On-site or Edge Cloud Infrastructure: Fog Infrastructure: Central Cloud Infrastructure Sara Mazur Ericsson AB

7 Industrial Cloud Specification DEVICE ON-PREM LOCAL/ METRO COUNTRY/ REGONAL GLOBAL/ CENTRAL Machine, car, train, Factory, office, power-station, micro datacenter Central office, hub/antenna site, micro datacenter Data Center Data Center Autonomy, extreme low latency Autonomy, security, low latency Resilience, network efficiency Regulatory compliance, Scale, multi-cloud Cost, Efficiency Sara Mazur Ericsson AB

8 Evolution of Cloud Cloud 1.0 Virtualization of servers Cloud 2.0 Centrally controlled services Manual and custom management Complex management stacks Datacenter operator pain-points: Lack of insight from operation metrics Complex maintenance and upgrade of DC management software Cost of low resource utilization Cloud developer pain-points: Efforts spent on infrastructure programming Network management gets in the way

9 Cloud 3.0 design principles Datacenter is abstracted as One Big Machine. All cloud services are fully distributed. Datacenter capacity organically adapts and self-configures. Developer-friendly abstractions capturing non-functional requirements like latency.

10 Industrial Cloud Reuirements 5G IoT Intelligent services Concerns Data Automation Management & Orchestration Edge Integration NFV Future Infrastructure Platform Core Cloud Platform Domain Specific Platforms Service Delivery Platform Solutions HW Driven Optimization Operating System Driven Optimization Application/Context Driven Optimization Service Driven Optimization Ericsson Internal Page 10 Operational Efficiency

11 Leveraging disruptive HW An information model for Cloud Acceleration Copyright Ericsson Internal Ericsson AB Azimeh Sefidcon I

12 DC policy and management Tenant management Integrated Analytics Distributed Operating System Development environments for cloud native applications Application runtime Cloud 3.0 APIs DC boot Compute Messaging Network Storage Accelerator Linux Linux Linux Linux Linux Edge computing for industrial applications :18 0:23

13 Service Composition 3.0 Copyright Edge computing Ericsson for AB industrial 2018 applications Azimeh Sefidcon I

14 Benefits of Cloud 3.0 Moving the cloud native definition back from born in the cloud to gestated in the cloud Lower development cost: Faster development cycles by allowing focus on computation and data handling. Lower operational cost: High level of automation by self-configuration and self-healing. Higher utilization through use of processes as unit of execution. Increased usability and scalability: Compute clusters of all sizes, bringing the cloud model from datacenters towards the edge.

15 Industrial Cloud Cloud 3.0 Lower Operational Cost Lower Development Cost Increased Usability & Scalability DEVICE ON-PREM LOCAL/ METRO Machine, car, train, Factory, office, power-station, micro datacenter Central office, hub/antenna site, micro datacenter COUNTRY/ REGONAL Data Center GLOBAL/ CENTRAL Data Center Autonomy, Including HW driven optimization Operating system level optimization Application specific optimization Service driven optimization extreme low latency Autonomy, security, low latency Resilience, network efficiency Regulatory compliance, multi-cloud Scale, Cost, Efficiency Sara Mazur Ericsson AB

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