Disoriented about all the Azure services in the IoT and Industrial IoT that you can use for building a modern Architecture on the Cloud and on the Edge? Well, this session aims to describe a reference architecture like Lambda and to map it to Azure services like Event Hubs, IoT Hubs just to mention a few. It also presents different approaches on how to handle communication from a more commercial devices to discrete manufacturing ones, with different standards like OPC UA. All those bricks will also help you to use already-build solutions like our Accelerators and IoT Central.

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saturday 2019
Internet of Things
Architecting Azure (I)IoT solutions
Pietro Brambati, Microsoft
Twitter:@pietrobr
pietrobr@microsoft.com

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Azure IoT portfolio
Device SDKs Azure Sphere Windows IoT Data Box Edge
Certified
Devices
IoT Edge
Stream
Analytics
Azure ML Azure SQL Functions
Cognitive
Services
IoT Hub Event Hub IoT Hub Device
Provisioning Service
Time Series
Insight (TSI)
Maps
Stream
Analytics
CosmosDB Logic Apps Cognitive / AI Web Apps
PowerBI
Azure IoT Solution Accelerators Azure IoT Central
AzureSecurityCenterforIoT
App Insight Blob Service Bus

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IoT Logical Architecture
IoT DeviceIoT DeviceIoT Device
IoT DeviceIoT Device
IoT Edge
Device
Cloud
Gateway
Stream
Processing
Data
Transformation
Warm
Store
Cold
Store
UI &
Reporting
User
Management
Business
Integration
Machine
Learning
Fast path – real time processing
Slow path – Batch processing

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Azure IoT Architecture – simplified view
IoT DeviceIoT DeviceIoT Device
IoT DeviceIoT Device
IoT Edge
Device
Stream Processing UI & Reporting
Machine Learning
Fast path – real time processing
Slow path – Batch processing
Cloud
Gateway
IoT Hub
Data Transformation
Functions
Warm
CosmosDB
Cold
Blob
Azure Stream Analytics Power BI
Business Integration
Logic Apps
User Management
Azure Active Directory
Machine Learning

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Lambda Architecture
A generic, scalable, robust and fault-tolerant data processing architecture
New
data
Storage
(HDFS)
Real-time
view
Batch layer
Batch view
Batch view
Query
Real-time
view
Pros
Increase throghput
Reduce latency
Negligible errors
Useful with event sourcing
Serving layer
Speed layer
Cons
Different tecnologies
No easy to mantain
Process
(Map Reduce)
Process
(Spark/Storm)

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Kappa Architecture
Real-time processing of live streaming data - an alternative to Lambda, not a replacement
Pros
Focus on speed
Less code resource
Fewer resources: ML done in real-time
Re-processing only if code changes
Cons
More errors, no batch layer
New
data
Real-time
view
Query
Real-time
view
Serving layer
Process
(Spark/Storm)
Speed layer

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Slow path – batch processing
Fast path – real-time processing
Azure IoT Logical Architecture – Lambda
Recommended data flow
Cloud
GatewayIoT DeviceIoT DeviceIoT Device
Route
Analyze
(low latency)
Store Display
Action
Analyze
(complex)
Action
Store Display
Partitioning
Message props.

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Azure IoT Physical Architecture – Lambda
Stateless and Static rules, no reference to external data
Scheduled batch processing (training , Machile Learning)
Real-time device telemetry (visualization)
IoT Hub
IoT DeviceIoT DeviceIoT Device
IoT Hub Route
IoT Hub Route
Event Hub Functions
Logic App
IoT Hub Route
Blob/ADL
(Cold)
Azure ML
CosmosDB
Real-time analytics (Alert, Actions)
Event Hub Functions
When to use:
Processing rule with no history
Records in JSON
Small number of rules required
Define conditions in payload of IoT Hub Route

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Azure IoT Physical Architecture – Lambda
Statefull and Dynamic rules, ability to reference external data
Scheduled batch processing (training , Machile Learning)
Real-time device telemetry (visualization)
IoT Hub
IoT DeviceIoT DeviceIoT Device
IoT Hub Route Event Hub Functions
Logic App
IoT Hub Route
Storage
(Cold)
Azure ML
CosmosDB
Real-time analytics (Alert, Actions)
Azure Stream
Analytics
FunctionsWhen to use:
Complex analysis: time windows, join
with external data source
Processing logic consists of severval
rules that can grow
Input data in binary format (like Avro)

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Ops….

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IoT and Industrial IoT (IIoT)
Industrial ready solutions
IoT
Consumer apps and device
Good Internet connectivity
Well know set of protocols
«Close enough» for good latency
Usually no real-time requirements
Simple application with low-risk impact
Industrial IoT
Industrial apps (agricaulture and manifacturing, etc.)
Low internet connectivity
A «junglue» of communication protocols
lack of interoperability and legacy technologies:
SCADA, M2M, etc
Security is a major complain (e.g take down an
electrical grid)
Must integrate with ERP
Precision is business as usual
Low latency for near-real-time operations
Reliability and Resilence: 20-30 years, e.g. loss of
sensors, loss of connectivity

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Edge Connectivity
IP-based communication
Device
IoT Client
Device
Device
Device
IoT Client
Device
Device
Field gateway
IoT Client
Cloud
Gateway
(IoT Hub)
AMQP, MQTT, HTTPS
AMQP, MQTT, HTTPS
Custom Cloud
Gateway
Custom protocols
Field gateway OPC, HTTP, CoAP
VPN/ExR
CoAP,AllJoyn, OPC
CoAP,AllJoyn, OPC

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OPC Unified Architecture(UA)
Local network communication
OPC «Classic»
Object Linking and Embedding for Process Control, first defined in 1995.
A Client/Server based communication architecture
Evolved over the years adding more functionalities (protocols): Data Access, Alarm & Events, etc..
OPC Unified Application
Secure, platform-independent, SOA, in 2008
OPC-UA gateway read from OPC-UA server via Publish/Subscribe (JSON payload over MQTT or AMQP)

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Field Gateway
(IoT Edge)
OPC UA with Microsoft Technologies
Microsoft invests heavily in OPC-UA by providing several solutions
IoT DeviceIoT Device
Industrial
Device
OPC UA Server
OPC Publisher «Container» Cloud
Gateway
OPC Client
OPC Server
Cert. Store
Telemetry Data Flow Scenario
OCP-UA Publish/Subscribe

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MIRAI

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Security
Connected device – some consideration
Inexpensive device trading away cryptographic capability
They should be constrained on local network
used by field gateway
Use device that support cryptographic capabilities
Encryption algorithms
Digital signature
TLS 1.2, DTLS 1.2
Updatable key-store per device and firmware must allow updates
Choose MCU with TPM
Secure boot loader
Sensor to detect intrusion attemps
Use a relay service to remote connect to a device
No direct SSH to it

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IoT Hub
Ingestion to the cloud
Event processing
Device provisioning
and management
Device business logic,
connectivity monitoring

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IoT Device Provisioning Service (DPS)
Zero touch, just in time device provisioning to the right IoT Hub
No hard-coding IoT Hub into device at
the factory
Load balancing
Lowest latency
Connect to the right IoT Hub in
Mutitenancy scenario
Roll Certificate (e.g in case of a breach)
Reprovisioning
IoT DeviceIoT Device
IoT Edge
Device
Device Provisioning Service (DPS)
Enrollment List Cloud
Gateway
(IoT Hub)
X509, TPM, Sym. Key
1
2
3
4
5
6
7-8

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Event Hub
Architecture- event ingestor at high-scale
HTTPS
AMQP
Kafka
Consumer group
Consumer group
Event Producers
MB/s → GB/s
Event Receivers
Each consumer app its own cursor/offset
Durable:
1-7 days for Standard, 90 days Dedicated

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Event Hub
Scenario : Clean Event Hubs

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Event Hub
Scenario : Checkpoints
It doesn’t start from the beginning

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Azure Stream Analytics
event-processing engine
IoT Hubs
Archiving for long term storage/
batch analytics
Real-time dashboard
Stream
Analytics
Automation to kick-off
workflowsMachine LearningReference Data
(Blobs and SQL DB)
Event Hubs
Blobs
Devices &
Gateways
Power BI
Applications

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Azure Stream Analytics
event-processing engine
Stream UnitInput Stream output Stream
stream
From With
Into
Stream UnitInput Stream output Stream
From With
IntoJoin

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SAQL
Query Language
Scaling Extensions
WITH
PARTITION BY
OVER
Windowing Extensions
TumblingWindow
HoppingWindow
SlidingWindow
Aggregate Functions
Sum
Count
Avg
Min
Max
StDev
StDevP
Var
VarP
String Functions
Len
Concat
CharIndex
Substring
PatIndex
Temporal Functions
Lag, IsFirst
CollectTop
DML
SELECT
FROM
WHERE
GROUP BY
HAVING
CASE WHEN THEN ELSE
INNER/LEFT OUTER JOIN
UNION
CROSS/OUTER APPLY
CAST
INTO
ORDER BY ASC, DSC
Date and Time Functions
DateName
DatePart
Day
Month
Year
DateTimeFromParts
DateDiff
DateAdd

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Azure Stream Analytics
Tumbling Window
Tell me the count of tweets per time zone every 10 seconds
1 5 4 26 8 6 5
Time
(secs)
1 5 4 26
8 6
A 10-second Tumbling Window
3 6 1
5 3 6 1
1 5 4 26
1
SELECT TimeZone, COUNT(*) AS Count
FROM TwitterStream TIMESTAMP BY CreatedAt
GROUP BY TimeZone, TumblingWindow(second,10)

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Azure Stream Analytics
Hoping Window
SELECT Topic, COUNT(*) AS TotalTweets, AVG(SentimentScore)
FROM TwitterStream TIMESTAMP BY CreatedAt
GROUP BY Topic, HoppingWindow(second, 10 , 5)
Every 5 seconds give me the count
of tweets and the average
sentiment score over the last 10
seconds
1 5 4 26 8 7
A 10-second Hopping Window with a 5-second “Hop”
4 26
8 6
5 3 6 1
1 5 4 26
8 6 5 3
6 15 3

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Azure Stream Analytics
Sliding Window
SELECT Topic, COUNT(*) FROM TwitterStream
TIMESTAMP BY CreatedAt
GROUP BY Topic, SlidingWindow(second, 10)
HAVING COUNT(*) > 10
Give me the count of tweets for all
topics which are tweeted more than
10 times in the last 10 seconds
1 5
A 10-second Sliding Window
8
8
51
9
51 9
1

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Azure Stream Analytics
Session Window
Tell me the count of
tweets that occur within
5 minutes each other
1 5
A 10-second Sliding Window
9
5
76 8
1
6 7 8
9

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Event Grid
event routing service for publish and subscribe model
Retry mechanism
Filter to route events
to different endpoints
single endpoint for
SaaS apps. Fine-
grained auth with AAD
Dead-letter
Events != Messages

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Time Series Insights
Analytics for Industrial IoT
Analytics, storage and visualization service for time series data
Operation Analysis for both warm and cold data
Storage in-memory and SSD
Easy connection with IoT Hub
SQL like filtering and aggregation
Data explorer dashboard and API,
JavaScript library
Latency 30-60 seconds

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The Edge

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Why Azure IoT Edge?

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IoT Edge runtime
Installs and updates workloads on the device.
Maintains Azure IoT Edge security standards on the device.
Ensures that IoT Edge modules are always running.
Reports module health to the cloud for remote monitoring.
Facilitates communication between downstream leaf devices and the IoT Edge device.
Facilitates communication between modules on the IoT Edge device.
Facilitates communication between the IoT Edge device and the cloud

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IoT Edge runtime
Standard deployment model
Azure IoT Hub
Azure IoT Edge
Device
IoT Edge Runtime

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IoT Edge runtime
Kubernetes integration
Kubernetes Cluster
Devices
Azure IoT Hub
IoT Edge Runtime
Kubernetes
IoT Edge Runtime
Kubernetes
IoT Edge Runtime
Kubernetes

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9 BILLION new MCU devices
built and deployed every year
Microcontrollers (MCUs)
low-cost, single chip computers

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Fewer than 1% of MCUs are connected today.

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Azure Sphere

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Solution accelerators

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Azure IoT solution
accelerators
Dashboards, visualization and insights
Completely customizable
Command and control
Device connectivity and management
Predictive Maintenance
Connected FactoryRemote Monitoring
Workflow automation and integration
Preconfigured solutions
End-to-end implementation
Device Simulation
Open-source microservices based architecture

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Azure IoT central
Analytics, dashboards and visualization
Extensibilities (Flow, Dynamics, Webhooks, etc.)
Monitoring rules and triggered actions
Fully hosted and managed by Microsoft
Device connectivity and management
Risk-free trial with simplified pricing
No cloud development expertise required

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Summary
IoT projects are complex, but…
Azure Reference Architecture
+ PaaS Service
+ Accelerators
+ IoT edge
+ Edge components
= make them simpler!

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Grazie e buona continuazione
Pietro Brambati, Microsoft

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Resources
• Microsoft Azure IoT Reference Architecture pdf
• IoT PaaS Services
• Lambda architecture
• Lamba vs K architecture
• OPC UA Publisher
• Connected Factory solution accelerator walkthrough