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Microsoft

Implement message processing for data storage and analytics by using Azure IoT Hub

Microsoft via Microsoft Learn

Overview

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  • Module 1: This module introduces you to IoT Hub message routing, the common message format implemented by IoT Hub, IoT Hub’s service-facing endpoints, and the message routing query syntax.
  • After you complete this module, you will be able to:

    • Describe message processing concepts.
    • Describe the Azure IoT common message format and features of IoT Hub message routing.
    • Describe the built-in and custom endpoints that can be used with IoT Hub message routing.
    • Describe the message routing query syntax.
  • Module 2: This module introduces you to services and service features that can be used with, or as an alternative to, IoT Hub message routing to process messages, and examines IoT Hub message processing limits.
  • After you complete this module, you will be able to:

    • Describe IoT Hub message routing with Event Grid integration.
    • Describe IoT Hub message enrichment.
    • Describe the IoT Hub messaging quotas and throttling limits.
  • Module 3: This module introduces you to the Azure data storage options that are often used in Azure IoT solutions, and the hot and cold storage paths can be implemented in support of various business requirements.
  • After you complete this module, you will be able to:

    • Describe the lambda architecture for data storage.
    • Describe Azure storage options commonly implemented with IoT solutions.
    • Describe the features provided by specific Azure storage options.
  • Module 4: This module introduces you to the Azure Stream Analytics service and Azure Functions, the capabilities provided by the ASA service, and the configuration options for ASA inputs, outputs, and queries.
  • After you complete this module, you will be able to:

    • Describe Azure Stream Analytics concepts, use cases, and guidelines.
    • Describe Azure Stream Analytics input types and configuration requirements.
    • Describe the Azure Stream Analytics query syntax for simple and complex queries.
    • Describe how Azure Stream Analytics handles time data and the available windowing functions.
    • Describe Azure Stream Analytics output options and the capabilities provided by Azure functions.
  • Module 5: This module provides you with experience analyzing and processing IoT device messages using IoT Hub message routing and the Azure Stream Analytics services, and experience configuring Azure Blob storage for your device data.
  • After you complete this module, you will be able to:

    • Connect a simulated device to Azure IoT Hub and verify that IoT Hub is receiving telemetry.
    • Configure an Azure IoT Hub message route that outputs selected message data to Azure Blob storage.
    • Configure an Azure Stream Analytics job that analyzes message data and routes the selected information to Azure Blob storage.

Syllabus

  • Module 1: Examine IoT Hub message routing
    • Introduction
    • Review message processing concepts
    • Examine the common message format
    • Examine message routing
    • Examine the IoT Hub built-in endpoint
    • Examine routing to multiple endpoints
    • Examine the message routing query syntax
    • Knowledge check
    • Summary
  • Module 2: Consider message processing options and constraints
    • Introduction
    • Compare IoT Hub message routing with Event Grid integration
    • Examine message enrichments for D2C messages
    • Examine IoT Hub quotas and throttling
    • Knowledge check
    • Summary
  • Module 3: Get started with cloud storage for IoT
    • Introduction
    • Examine the IoT Lambda architecture
    • Review cloud storage options for Azure IoT solutions
    • Examine Azure Blob storage and storage accounts
    • Examine Azure Data Lake Gen 2
    • Examine Azure Cosmos DB
    • Examine Azure SQL Database
    • Knowledge check
    • Summary
  • Module 4: Examine Azure Stream Analytics and Azure Functions
    • Introduction
    • Get started with Azure Stream Analytics
    • Examine Azure Stream Analytics use cases
    • Review ASA patterns and guidelines
    • Get started with ASA input types
    • Examine ASA streaming data input
    • Examine ASA reference data input
    • Examine the ASA query syntax
    • Parse complex data types with ASA queries
    • Examine time handling considerations for ASA queries
    • Examine the ASA windowing functions
    • Examine ASA output options
    • Examine features and characteristics of Azure Functions
    • Knowledge check
    • Summary
  • Module 5: Explore message processing tasks
    • Introduction
    • Implement message routing and Azure Stream Analytics
    • Knowledge check
    • Summary

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