My presentation for IgooConf 2018, here we dive into the edge capabilities provided by IoT Edge, combined with IoT Hub and other Edge and Azure services to create a complete and powerful solution. IoT Edge makes hybrid IoT solutions a reality, allowing us to seamlessly deploy and run AI, Azure Services and custom logic directly on our devices. And all this is done while giving us the option manage and administrate it all from and communicate with Azure.

1. IoT on the Edge
Eldert Grootenboer

2. Cloud Solution Architect
Microsoft Azure MVP
SME IoT
Blogger
Published Author
International Speaker
Global Integration Bootcamp
Azure IoT Community
TechNet / MSDN / GitHub
Boat enthusiast

8. Cloud
IoT
Edge
AI

9. IoT in the Cloud and on the Edge
IoT in the Cloud IoT on the Edge
Symmetry

10. Things
IoT Pattern
Insights Actions
Cloud
Gateway
Azure IoT Hub

11. Cloud
Gateway Insights ActionsThings
IoT Pattern + Edge
Azure IoT Hub
Insights Actions

13. Secure
Cloud managed
Cross-platform
Portable
Extensible
Azure IoT Edge
Design Principles

14. Edge Runtime
Azure IoT Edge Runtime
Azure IoT Edge device
🗴
Edge Runtime provides
fundamental services
Security
Multiplexing
Store and forward (Offline)
Management for devices
otherwise isolated from
internet

15. Modules
Edge Runtime manages modules
Modules add capabilities to the
runtime
Each module performs an action
Chain of modules can be thought
of as a data processing pipeline,
solving an end to end scenario
Modules are Docker containers
Custom modules can be written in
the language of your choice
Azure IoT Edge Runtime
Azure IoT Edge device
Scenario: Find insights in the cloud from telemetry sent by a
device that does not speak an internet ready protocol.
Protocol
ingestion
Module
Data
formatting
Module
ML
Telemetry
Telemetry

16. Cloud off load
Modular architecture for cloud
offload
Azure services provide AI
modules which provide true
edge analytics
Ecosystem for 3rd party edge
services
Azure IoT Edge Runtime
Azure IoT Edge device
Scenario: Find insights locally from telemetry data and only
send insights to the cloud.
Ingest
Module
Format
Module
ML
Insights
Telemetry

17. Cloud configurability and Monitoring
Runtime + IoT Hub provide
full control of device lifecycle
Configure a workflow
Target a device
Deploy
Monitor
Azure IoT Edge Runtime
Azure IoT Edge device
Scenario: Find insights locally from telemetry data and only
send insights to the cloud.
Ingest Format
ML

18. @egrootenboer

25. Scenario – Custom Module

26. Scenario – Automate

27. Scenario – Analyze

28. Azure IoT Edge IoT Hub
Devices
Local Storage
Functions
RuntimeContainer
Management
Device
Twin
Device
Twin
Azure Stream
Analytics
(Container)
Azure Functions
(Container)
Cognitive Services
(Container)
Azure Machine
Learning
(Container)
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Custom
(Container)

29. @egrootenboer
eldert.grootenboer@motion10.com
http://blog.eldert.net/
http://blogs.biztalk360.com
Getting started
https://docs.microsoft.com/en-us/azure/iot-edge/
https://docs.microsoft.com/en-us/azure/iot-edge/quickstart
https://sandervandevelde.wordpress.com/category/iot/
Thank You