2-611.pptx

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2-611.pptx

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  1. 2-611

    Slide 1 - 2-611

    • Best Practices for Creating IoT Solutions with Azure
    • Kevin Miller
    • Principal Program Manager, Azure IoT
    • Internet of Things
    • //build/ content is being presented by Microsoft Office Mix The video for this session will be available shortly
  2. Slide 2

    • Agenda
    • State of the art for IoT
    • Architecture for building today
    • Patterns and anti-patterns
    • Demo
    • Architecture for the future
  3. Is IoT even a new thing?

    Slide 3 - Is IoT even a new thing?

    • Command and control scenarios have much in common with some parts of IoT.
    • But falling hardware costs, cloud services and relatively ubiquitous communications do enable new approaches.
    • Depending on who you ask, IoT is either:
    • Nothing new
    • A unicorn
    • 1
    • 2
    • Magic, and will soon change everything.
    • We’ve been doing this for 40 years
  4. Most of the early successful IoT deployments were either…

    Slide 4 - Most of the early successful IoT deployments were either…

    • For very complex and expensive devices, where the cost of a custom hardware/software solution is acceptable compared to the cost of the device, or…
    • For high-volume, homogeneous devices, where the software needs are relatively simple..
    • IoT solutions until now
    • Device complexity
  5. Microsoft Azure IoT Services

    Slide 5 - Microsoft Azure IoT Services

    • Devices
    • Device Connectivity
    • Storage
    • Analytics
    • Presentation & Action
    • Event Hubs
    • SQL Database
    • Machine Learning
    • App Service
    • Service Bus
    • Table/Blob Storage
    • Stream Analytics
    • Power BI
    • External Data Sources
    • DocumentDB
    • HDInsight
    • Notification Hubs
    • External Data Sources
    • Data Factory
    • Mobile Services
    • BizTalk Services
    • { }
  6. Build to an architecture that will scale, but start prototyping with a small number of devices.

    Slide 6 - Build to an architecture that will scale, but start prototyping with a small number of devices.

    • It’s hard to predict what data provides value -- which impacts which sensors and devices are necessary -- until you build something.
    • It’s much easier to work through through device identity, management/update and security at small scale.
    • Pattern: Think big. Start small
    • Think big, but start small.
    • Experiment, learn and refine.
  7. IoT architecture requirements

    Slide 7 - IoT architecture requirements

    • Handle extreme hardware and software heterogeneity.
    • Lower barriers to entry: evaluate -> prototype -> deploy.
    • Provide hot-path and cold-path analysis and response.
    • Build for hyper-scale and enable low latency.
    • Be secure by design; support defense in depth.
  8. It is very hard to predict in advance what data will be useful.

    Slide 8 - It is very hard to predict in advance what data will be useful.

    • It is tempting, but likely inefficient to try for business transformation in the first step.
    • Think about not only device telemetry but also diagnostic telemetry.
    • Privacy and security implications of telemetry are generally lesser than for command and control.
    • Pattern: Telemetry first
    • Start with telemetry.
    • The important data may not be what you expected.
    • Address privacy, security and manageability before moving to command and control.
  9. High scale data ingestion via Event Hub.

    Slide 9 - High scale data ingestion via Event Hub.

    • High scale stream processing via Stream Analytics (or HDInsight /Storm)
    • Storage for cold-path analytics
    • Processing for hot-path analytics
    • Telemetry today
    • Event Hub
    • Stream Analytics
    • SQL
    • Blob
  10. Real-time analytics for Internet of Things solutions

    Slide 10 - Real-time analytics for Internet of Things solutions

    • Stream millions of events per second
    • Mission critical reliability, performance and predictable results
    • Rapid development with familiar SQL-based language
    • Event Hubs and Stream Analytics
    • Cloud-scale telemetry ingestion from websites, apps, and devices
    • Compatible with more than a million publishers supporting HTTP, AMQP and MQTT
    • Ingress millions of events per second
    • SAS based security, with unique token per publisher
    • Configurable data retention (1-30 days)
    • Low latency (<10 ms for volatile data)
    • Pluggable with other cloud services like Stream Analytics
    • Event Hub
    • Stream Analytics
  11. Demo Event Hub and Stream Analytics

    Slide 11 - Demo Event Hub and Stream Analytics

    • Event Hub
    • Stream Analytics
    • Website
    • Worker (Node.js)
    • SQL
    • Blob
    • Event Hub
    • Stream Analytics
    • SQL
    • Blob
    • Website
    • Worker (Node.js)
  12. var eventBody = { "reading": x, "device_id": id };

    Slide 12 - var eventBody = { "reading": x, "device_id": id };

    • ehClient = new EventHubClient({
    • 'name': "kevinmil-demo", 'namespace': "kevinmil-demo-ns",
    • 'sasKey': <snipped>, 'sasKeyName': "sendTelemetry",
    • 'timeOut': 10,
    • });
    • var msg = new EventData(eventBody);
    • ehClient.sendMessage(msg, function (messagingResult) {
    • // <body snipped>
    • });
    • JavaScript (to Event Hub)
  13. SELECT

    Slide 13 - SELECT

    • device_id as Device_Id,
    • reading as Reading,
    • EventProcessedUtcTime as UTCDateTime
    • FROM [eventhub]
    • INTO [out2blob]
    • Stream Analytics (to blob)
  14. SELECT

    Slide 14 - SELECT

    • System.TimeStamp as UTCDateTime, device_id as Device_Id,
    • COUNT (*) as Count
    • FROM [iotdemoeventhub] TIMESTAMP BY EventProcessedUtcTime
    • INTO [alertCounts]
    • WHERE ( CAST(reading AS float) > 115.0 )
    • GROUP BY device_id, SlidingWindow(second, 15)
    • HAVING COUNT(*) > 1
    • SELECT
    • device_id as Device_Id, reading as Reading,
    • EventProcessedUtcTime as UTCDateTime
    • FROM [iotdemoeventhub] TIMESTAMP BY EventProcessedUtcTime
    • INTO [stream2sql]
    • Stream Analytics (to SQL)
  15. Think about a scalable architecture, but start small, and start with telemetry.

    Slide 15 - Think about a scalable architecture, but start small, and start with telemetry.

    • It is straightforward to get a telemetry example running with very limited coding.
    • Demo recap
  16. In the telemetry example, Event Hub data flows directly into Stream Analytics.

    Slide 16 - In the telemetry example, Event Hub data flows directly into Stream Analytics.

    • Pattern: Don’t interrupt the fast path
    • Don’t accidentally create processing bottlenecks. (Think carefully before interrupting data flow between high-scale components.)
    • “Don’t stick your head in the fire hose unless you know what you’re doing.”
    • Both components are designed for high scale.
    • Don’t process between high-scale components unless you can handle that scale.
    • Event Hub
    • Stream Analytics
  17. The entire organization needs to be focused on security, and that focus must inform the entire product lifecycle.

    Slide 17 - The entire organization needs to be focused on security, and that focus must inform the entire product lifecycle.

    • Pattern: Defense in depth
    • Think about security, identity and management from the very beginning.
    • Security is a shared responsi-bility between Azure and the customer.
    • Requirements
    • Design & Implementation
    • Verification & Release
    • Response
    • Think about security on the device, at the field gateway (if one exists) and in the cloud.
    • Physical Security, Tamper Detection
    • Hardware & firmware security,
    • secure boot
    • Network, protocol & application security
    • Identity management for devices and users
    • Data Privacy Protection and Controls
  18. Accelerate time-to-value by easily deploying IoT applications for the most common use cases, such as remote monitoring, asset management, and predictive maintenance

    Slide 18 - Accelerate time-to-value by easily deploying IoT applications for the most common use cases, such as remote monitoring, asset management, and predictive maintenance

    • Plan and budget appropriately through a simple predictable business model
    • Grow and extend solutions to support millions of assets
    • Azure IoT Suite
  19. Azure IoT Reference Architecture

    Slide 19 - Azure IoT Reference Architecture

    • Solution Portal
    • Provisioning API
    • Identity & Registry Stores
    • Stream Event Processor
    • Analytics/ Machine Learning
    • Data Visualization & Presentation
    • Device State Store
    • Gateway
    • Storage
    • IP capable devices
    • Existing IoT devices
    • Low power devices
    • Presentation
    • Device and Event Processing
    • Data Transport
    • Devices and Data Sources
    • Cloud Gate-way
    • AgentLibs
    • AgentLibs
    • Control System Worker Role
    • AgentLibs
  20. The forthcoming IoT Suite will ease the design and deployment of IoT applications for the most common use cases.

    Slide 20 - The forthcoming IoT Suite will ease the design and deployment of IoT applications for the most common use cases.

    • Highly portable client libraries support easy cloud connection for devices and gateways.
    • IoT Hub will extend Event Hubs to include device provisioning, identity, command & control, and management.
    • Building to the reference architecture will simplify conversion to the IoT Suite.
    • Pattern: Build to the reference architecture
    • Get started now and convert easily when the IoT Suite is publically available.
  21. Demo 2 Adding a native client and PowerBI

    Slide 21 - Demo 2 Adding a native client and PowerBI

    • PowerBI
    • Client Library
    • Event Hub
    • Stream Analytics
    • SQL
    • Blob
    • Website
    • Worker (Node.js)
  22. Think big (architecture), but start small (experiment, learn and refine).

    Slide 22 - Think big (architecture), but start small (experiment, learn and refine).

    • Start with telemetry. Address privacy, security and manageability before moving to command and control.
    • Don’t interrupt the fast path and create processing bottlenecks.
    • Think about security, identity and management from the very beginning, and through the life of the product.
    • Build to the reference architecture to ease the move to IoT Suite.
    • Summary
    • CONSUMERS
    • DEVICES
    • OBJECTS
    • NETWORK
    • BIG DATA
    • INNOVATION
    • STANDARDS
    • BUSINESS
    • SECURITY
    • Internet
    • of Things
  23. Internet of Things Overview: By Sam George and Steve T @ 5:00PM, 04/29, Room Hall 1A

    Slide 23 - Internet of Things Overview: By Sam George and Steve T @ 5:00PM, 04/29, Room Hall 1A

    • 2. Azure IoT security: By Clemens Vasters @ 2:00PM, 04/29, Room 3014
    • On demand sessions:
    • 1. Designing and sizing a global scale telemetry platform on Azure Event Hubs
    • 2. Connecting your devices to Azure IoT suite
    • Attend IoT sessions at Build
    • Reference talks by Sam, Elio, Clemens and any of the ASA talks, at least.