1. IoT at the Edge
Technical guidance deck

2. Table of Contents Overview Scenario Value Technical Overview
Components/Capabilities
Reference Architecture/Design Patterns

3. Waves of innovation Cloud IoT Edge AI
Globally available, unlimited compute resources
IoT
Harnessing signals from sensors and devices, managed centrally by the cloud
Edge
Intelligence offloaded from the cloud to IoT devices AI
Breakthrough intelligence capabilities

4. Why the edge? IoT in the cloud IoT on the edge
Secure Zone
Why the edge?
IoT in the cloud
Remote monitoring and control
Merging remote data from across multiple IoT devices
Near infinite compute and storage to train machine learning and other advanced AI tools
IoT on the edge
Low-latency, tight control loops require near- real-time response
Public Internet inherently unpredictable
Privacy of data and protection of IP

5. Edge processing scenarios and requirements
11/7/2018 7:37 AM
Straightforward
business logic
Smart Building
Protocol
Translation
Industrial
IoT Adapters
Autonomous
Driving
filtering
Batch data
processing
Home Automation
Hubs
Smart
Meeting Solutions
w/ People Recognition
Reliability requirements
Low Medium High
Low
Portable modules/functions
Medium
E.g.: Custom Code in Containers
High
E.g.: ML/DNNs in Containers
Custom code requirements
Interactive tier (Single CPU, 128 MB memory)
Gateway tier or higher
Typical hardware requirements
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

6. Lifecycle management and configuration of edge device
Complex processing
Azure Stream Analytics, Cognitive Services
Enable any service (Microsoft or third-party) to offload intelligence to edge devices
Compose these services in solutions spanning edge and cloud
Declarative configuration of edge
Manage edge configuration, from provisioning to decommissioning, without touching the device
Simple processing
Filtering, batching, compression

7. Azure IoT Edge Secure Cloud managed Cross-platform Portable Extensible
Provides a secure connection to the Azure IoT Edge, update software/firmware/configuration remotely, collect state and telemetry and monitor security of the device
Cloud managed
Enables rich management of Azure IoT Edge from Azure; provides a complete solution instead of just an SDK
Cross-platform
Enables Azure IoT Edge to target the most popular edge operating systems, such as Windows and Linux
Portable
Enables dev/test of edge workloads in the cloud with later deployment to the edge as part of a continuous integration/continuous deployment pipeline
Extensible
Enables seamless deployment of advanced capabilities such as AI from Microsoft, and any third party, today and tomorrow

8. A deeper look

9. High-level topology IoT device Azure IoT Hub Customer solution Azure
IoT Edge
IoT
device
Azure
IoT Edge

10. Azure IoT Hub device management
Telemetry
Telemetry channel
IoT device
Device twin
Device twin
Properties
Properties
Cloud-owned, device visible
Desired
Desired
Device-owned, cloud visible
Reported
Reported
(Sam)
Tags
Cloud-only,
device metadata
Cloud-initiated C2D with response
Methods
Methods
Commands
Cloud-initiated C2D message

11. Azure IoT Hub device management
Jobs
Schedule and broadcast device twin changes
Set desired properties, tags, call methods
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Queries
Query across
device twin state
For business logic, reporting, and compliance
Device Twin
Device Twin
Device Twin
(Sam)
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Device Twin
Device twin

12. Azure IoT Edge Container-based modules
Offline/synchronized device twins
Azure functions
Local storage
Azure stream analytics
Cloud management and deployment
Azure machine learning
High availability/fault tolerance
Cognitive services
Cloud dev/test support
Devices
Azure IoT Edge  
IoT Hub
Azure Machine Learning
(Container)
Azure Stream Analytics
(Container)
Azure Functions
(Container)
Cognitive Services
(Container)
Custom Code
(Container)
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Container
Management
Functions
Runtime
Local Storage
Device
Twin
Device
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin
Module
Twin

13. Hardware for Azure IoT Edge
Ability to run on devices smaller than a Raspberry Pi
128 MB memory
Support best-in-class operating systems such as Windows and Linux

14. Demo outline Edge runtime using Docker for distribution and management
IoT Hub
Edge Hub
Edge ML
Edge ASA
Runs a local version of IoT Hub
Deploy a device sensor module/container
Deploy edge stream analytics module
Edge device
Deploy anomaly detection ML module
Deploy machine shutdown Azure Function module
Deploy an updated Azure Function module