IoT

• Devices and sensors
• Connected to each other and the internet
• Examples
  • Smart thermostat
  • Motion sensors and security cameras
  • Sensors in manufacturing machines
  • Sensors embedded in concrete
  • Traffic sensors
  • Sensors in streetlamps
  • Fitness trackers
  • Retail beacons

IoT Services in Azure

• Azure IoT Central
• Azure IoT Hub
• Azure Sphere

Azure IoT Hub

• IoT Hub is a managed service that acts as a central message hub for bi-directional communication between your IoT application and the devices it manages
• PaaS for IoT devices (develope IoT solutions without worrying about underlying infrastructures)
• Use Azure IoT Hub and the Azure IoT device SDKs to build a custom IoT solution from scratch
• Provides the building blocks for:
  • Connecting devices to the cloud
  • Managing devices
  • Ingesting data
• Bi-directional communication
• Automatic provisioning of device objects
• Has SDKs and APIs
• Has Simulated devices for development (so you don’t have to have a huge investment in hardware to get started with prototyping and testing)
• Support multiple Authentication capabilities
  • X.509 certificates
  • Shared Access Signatures

Azure IoT Central

• Managed IoT application platform, to build and deploy a secure, enterprise-grade IoT solution
• A fully managed application platform that you can use to create custom IoT solutions (choose devices from the Azure Certified for IoT device catalog to quickly connect to your solution)
• IoT Central application templates let you deploy an IoT Central application in minutes that you can then customize with themes, dashboards, and views
• Faster to start developing solutions
• Built-in device profiles
• See: https://docs.microsoft.com/en-us/azure/iot-fundamentals/iot-services-and-technologies#azure-iot-central

Azure Sphere

• Microsoft manages hardware, software, and Security Service (unique, integrated approaches to device maintenance, control, and security)
• A secured, high-level application platform with built-in communication and security features for internet-connected devices
• It comprises a secured, connected, crossover microcontroller unit (MCU), a custom high-level Linux-based operating system (OS), and a cloud-based security service that provides continuous, renewable security
• Devices also use Azure Sphere service
  • Verify security of operating system on start-up
  • Microsoft pushes OS updates and security patches

IoT Hub vs IoT Central vs Azure Sphere

• IoT Hub is PaaS
  • use SDK to develop your custom IoT solution.
  • you will build your frontend and everything yourself
  • IoT Hub for device connectivity, management and communication
• IoT Central is SaaS
  • Azure IoT Central is a software as a service (SaaS)
  • Microsoft will keep adding new capabilities and/or update and manage all those above-mentioned bundled services for you
  • Microsoft developed IoT service on top of IoT Hub -> IoT Central
• Azure Sphere (Microsoft controls Hardware and Software)
  • Microsoft manages hardware, software, and Security Service (unique, integrated approaches to device maintenance, control, and security)
  • When you have ‘N’ Crossover microcontroller unit (MCU) (each MCU may have multiple connected IoT devices)
• Links:
  • Azure IoT Hub: https://docs.microsoft.com/en-us/azure/iot-hub/
  • IoT Central: https://docs.microsoft.com/en-us/azure/iot-central/
  • Azure Sphere: https://docs.microsoft.com/en-us/azure-sphere/
  • https://stackoverflow.com/questions/56425557/what-is-the-difference-between-azure-iot-hub-and-azure-iot-central
  • Choosing the right service: https://azure.microsoft.com/en-us/overview/iot/product-selector/

Other IoT services

Azure IoT Edge
“Azure IoT Edge” is similar to Azure IoT Hub and has IoT device management / monitoring functions. The difference from Azure IoT Hub is that the data is analyzed directly on the IoT device side, not on the cloud side. Users don’t have to transfer data to the cloud, reducing the time it takes to gain insights from data analytics. The “Azure IoT Edge runtime”, which is a typical component of Azure IoT Edge, is responsible for managing the dedicated modules (deployed) on each IoT device.

More: https://docs.microsoft.com/en-us/azure/iot-fundamentals/

Big Data

• See: /explain/big-data
• Ingesting data
  • Azure Data Factory
  • Event Hubs
  • IoT Hubs
  • SSIS
  • Azure Synapse
  • Kafka (HDInsight)
• Persisting data
  • Data warehouse (Azure Synapse)
  • Distributed file systems (Hadoop)
  • Azure Blob Storage Data Lake
• Processing data:
  • Azure Stream Analytics
  • Azure Synapse Analytics
  • Azure Analysis Services
• Visualizing data:
  • Power BI
  • Jupyter notebooks

Big Data Solutions in Azure

• Azure Synapse Analytics
  • Latest and greatest from Microsoft
  • Built from ground up
• Azure Databricks
  • Company outside Microsoft
  • Azure has hosted Databricks platform
  • Based on Apache Spark platform
  • Fully-managed Spark Clusters
  • Workspace for visualizing data
  • Serverless option
  • Notebooks
  • Interactive dashboards
  • Integration with other Azure services
• Azure HDInsight
  • Open-source analytics tools
  • Apache Hadoop
  • Clusters of compute nodes
  • On-demand scalability and autoscale
  • Integration with Azure services for building Azure pipelines

Azure Synapse Analytics

Azure Synapse

• Formerly Azure SQL Data Warehouse
• Storage component

Azure Synapse Analytics

• SQL technologies
• Spark analytics
• Pipelines for orchestration
• Serverless or provisioned options
• Spark languages and T-SQL
• ETL (Extract-transform-load) functionality
• Integration with Azure services (i.e. Power BI)
• Built-in support for machine learning tools

Azure AI Suite

• Machine Learning
• Azure Cognitive Services
• Bot Service

Machine Learning in Azure

• Machine Learning Workspace
  • Create workspace: https://portal.azure.com/#create/Microsoft.MachineLearningServices
  • Workspace is a resource in Azure
• Machine Learning Studio
  • https://ml.azure.com
  • Notebooks (Jupyter)
  • Automated ML
  • Designer

Azure Cognitive Services

• Vision
• Speech
• Language
• Decision
• Web Search

(Cognitive services are exposed by REST end points)

Computer Vision

• Process and catalog images
• Generate captions for images
• Optical character recognition
  • Typewriter text
  • Handwritten text
  • Many languages
• Video indexer
• Face API (face recognition)
• Form Recognizer

Speech API

• Speech-to-text
• Text-to-speech
• Speaker recognition
  • Identify speaker by voice
  • Train model by providing samples

Language APIs

• LUIS
  • Language Understanding API
  • Natural language input
  • Used in chat bots
• Sentiment Analysis : Analyze text for positive or negative
• Translator Service: 70+ languages

Decision APIs

• Content Moderator (flags potentially offensive/undesirable content in text, image, video etc.)
• Personalizer (i.e. product suggessions)
• Anomaly API (anomaly detection)

Web Search Service

• Bing Web Search
• Bing Custom Search API
• Bing Image Search
• Bing Entity Search API
• Bing News Search API
• Bing Video Search API
• Bing Visual Search API
• Bing Autosuggest API
• Bing Spell Check API
• Bing Business Search API

Azure Bot Service

• Built on top of cognetive services
• Virtual assistant on the web
• Responds to questions
• Uses natural language processing
• Tools
  • Bot Framework SDK
  • Bot Framework Composer
    • Desktop application
    • Emulator
    • .NET Core SDK 3.1
• Deploy to App Service or Function App

Azure DevOps

See: /azure-devops

Azure DevTest Labs

• Azure DevTest Labs enables developers or teams to efficiently self-manage virtual machines (VMs) and PaaS resources without waiting for approvals
• Base images for virtual machines
• Images pre-configured with tools
• Existing VMs in a pool
• Constraints on resources that can be created by a developer
  • Size of VM
  • Number of VMs
• Auto-start and auto-stop of VMs

Use Cases for DevTest Labs

• Developer Desktops
• Test Environments
• Hands-on Labs
• Sandbox Environment