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Building Apps with Azure IoT Edge

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Presentation deck used for the Global Azure Bootcamp 2018 Sydney event. https://global.azurebootcamp.net/locations/australia-sydney-2/

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Building Apps with Azure IoT Edge

  1. 1. 21 April 2018 | Rahul Rai | Consultant Cloud Technologies https://rahulrai.in
  2. 2. 01 What is Edge Computing? 02 IoT Pattern with Edge 03 Scenarios 04 IoT Edge Features 05 Key Concepts & Exercise for You 06 Demo
  3. 3. What is Edge Computing? Computing infrastructure that exists close to the data Enables analytics and data aggregation to happen close to the data Reduces data transmission latency Improves time to respond to issues Reduces network bandwidth and cloud computation cost April 18 2
  4. 4. April 18 3 Cloud Gateway Insights ActionsThings Azure IoT Hub Insights Actions IoT Pattern with Edge
  5. 5. Scenarios Real life use cases of IoT Edge Remote Monitoring: Mining, Oil and Gas operations Industry 4.0 Manufacturing: Predictive maintenance Agriculture: Crop and livestock analytics Smart Home Entertainment: Home automation Logistics and Transportation: Fleet management April 18 4
  6. 6. Azure IoT Edge Key Features Why are organizations building applications on Azure IoT Edge? Secure: Connectivity, Remote Updates, Remote Monitoring Cloud Managed: SDK + Rich Management Capability Cross Platform: Windows, Linux Portable: Enables DevOps on Edge Workloads Extensible: Deploy AI and Third Party Capabilities April 18 5
  7. 7. Key Concepts – Edge Runtime Provides essential services to the Edge device Security Multiplexing Store and forward (Offline) Management for devices otherwise isolated from internet April 18 6 Azure IoT Edge Runtime Azure IoT Edge device 🗴
  8. 8. Key Concepts – Modules Modules add capabilities to runtime Managed by runtime Each module performs an action Modules are Docker containers Can be chained to build a data processing pipeline Can be written in language of choice April 18 7 Azure IoT Edge Runtime Azure IoT Edge device Protocol ingestion Module Data formatting Module ML Telemetry Telemetry
  9. 9. Key Concepts – Cloud Offloading Act locally on telemetry data and send insights to cloud Modular architecture Azure modules such as AI and Azure Functions provide edge analytics Easy to add 3rd party edge services April 18 8 Azure IoT Edge Runtime Azure IoT Edge device Ingest Module Format Module ML Insights Telemetry
  10. 10. Key Concepts – Configuration & Monitoring Configure and monitor edge device from cloud Runtime + IoT Hub provide full control of device lifecycle Configure a workflow Target a device Deploy Monitor April 18 9 Azure IoT Edge Runtime Azure IoT Edge device Ingest Format ML
  11. 11. Exercise For You Arrange the following edge modules in sequence to efficiently send insights to cloud Aggregation Module: Aggregate multiple data packets over a period of time. Filter Module: Remove redundant non critical information from payload. Compression Module: Apply compression e.g. Gzip on the payload. Batching Module: Aggregate logically coupled data into a single payload packet. e.g. data from all thermal sensors in a boiler unit. April 18 10
  12. 12. Answer The following arrangement of edge modules will efficiently send insights to cloud April 18 11 Filter Module Batching Module Aggregation Module Compression Module
  13. 13. Demo Application Architecture April 18 12 Azure IoT Edge Runtime Azure IoT Edge device FilterModule (Custom C#) FlagFunction (Azure Function)
  14. 14. Thank you | readify.net

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