Rural areas in the cloud Digital transformation beyond cities

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1 Rural areas in the cloud Digital transformation beyond cities 1 Balthasar Weitzel AWS Berlin Summit 2017

2 Fraunhofer IESE 2

3 This Talk Architecture of a crowd logistics app ecosystem -orientation as key architectural style Usage of AWS for quick feedback cycles 3

4 4

5 Betzdorf Donnersbergkreis (Göllheim/Eisenberg) 5

6 Digitale Dörfer Plattform 6

7 Digitale Dörfer Application Landscape Additional Services Concepts Partners FahrBar Taschen App Admin UI DigiTaler Motivation HeilBar CarUnity 7

8 Crowd Logistics 8

9 Crowd Logistics 9

10 10

11 Pooling Station 11

12 Webshop and Apps 12

13 s in Logistics Scenario Purchase Order Received Delivery Ready Transport Selected Delivery Received Delivery Picked Up 13 Delivery Delivered Delivery Picked Up Transport Selected Delivery Ready Door Closed Door Opened Delivery Scanned

14 -Driven Architecture 14

15 Basic Architecture of Logistics System -Oriented Mobile Device Logistics App Browser Shop Web- UI Pooling Station Control SW API Gateway Backend 15 Processor Processor -Bus Processor

16 s: Types Client Logistics App Delivery Ready Transport Selected Delivery Received Typed Domain Data API Gateway Backend -Bus Technical (Reactor) Typed Domain Data 16 Processor Processor Processor

17 Interfaces between Clients and Backend Client Logistics App Client DB Backend API Gateway -Bus Receiving API Sending Data API Read-Only 17 Processor Backend DB

18 Impact on Client Architecture Minimal logic in client (3 clients) Logistics App s created on real-world interaction s queue for offline interactions Screen Data Client Queue No direct data manipulation (via backend) 18 Client DB

19 Technical Realization 19

20 Technologies AWS Runtime Devtime 20

21 Deployment Overview Clients External Services Shop WebApp Android ios Pooling Station Authentication Provider Load Balancer AWS Elastic Beanstalk Environments (dev/stage/prod) Environments (dev/stage/prod) Environments (dev/stage/prod) SQS Queue AWS SQS Queue AWS Mobile Services Cognito SNS Service AWS EC2 Instance Spring Buckets (dev/stage/prod) Buckets (dev/stage/prod) Worker AWS EC2 Instance Spring GCM Push Services APNS service business Jackson Reactor datamanagement Swagger Hibernate worker business datamanagement Twitter Social Media Facebook AWS RDS Buckets (dev/stage/prod) Buckets (dev/stage/prod) MySQL DB (dev/stage/prod) AWS S3 Buckets (dev/stage/prod) Buckets (dev/stage/prod) Buckets (dev/stage/prod) Wordpress digitaledoerfer.de Twilio SMS GMail 21

22 Time Triggered s via Elastic Beanstalk Workers Handling of deadlines for business processes TransportWaitingForDeliveryExpired Service Instance Worker Instance Processor Waiting Processor WaitingForXE xpired Backend Persist deadline Expiry Worker Backend DB Regularly check deadline 22

23 Pooling Station: Reverse Communication Queues via SQS In unknown network, unknown IP address Backend Pooling Station API Gateway Receiving AWS SQS API Control Software Command Sending AWS IoT Data API Read-Only 23 -Bus

24 s from Backend to Clients via SNS Backend Mobile Device API Gateway ios Logistics App APNS AWS SNS Receiving API Data Sending GCM Android Logistics App Data API Read-Only 24 -Bus

25 Scaling of Backend Services via Elastic Beanstalk Client Elastic Beanstalk Instance 1 API Gateway -Bus Processor Logistics App 3 1 API 2 Elastic Load Balancer 3 Data API 1 Elastic Beanstalk Instance 2 Logistics App 2 API Gateway -Bus Processor API Logistics App Data API 25 Backend DB

26 Lessons Learned -orientation fits well as paradigm for logistics but needs a lot of concretization Running a system of that size within a research project only works with prefabricated high quality services Operation still requires significant knowledge, automation is the key for success 26

27 Key Takeaways Running a research prototype in production is possible Simple AWS services like Elastic Beanstalk and RDS are well suited for a learning team 27

28 Balthasar Weitzel Phone: Steffen Hess Phone: architecture.iese.fraunhofer.de