Set up IoT Edge modules and connections
Important
Azure SQL Edge will be retired on September 30, 2025. For more information and migration options, see the Retirement notice.
Note
Azure SQL Edge no longer supports the ARM64 platform.
In part two of this three-part tutorial for predicting iron ore impurities in Azure SQL Edge, you'll set up the following IoT Edge modules:
- Azure SQL Edge
- Data generator IoT Edge module
Specify container registry credentials
The credentials to the container registries hosting module images need to be specified. These credentials can be found in the container registry that was created in your resource group. Navigate to the Access Keys section. Make note of the following fields:
- Registry name
- Login server
- Username
- Password
Now, specify the container credentials in the IoT Edge module.
Navigate to the IoT hub that was created in your resource group.
In the IoT Edge section under Automatic Device Management, select Device ID. For this tutorial, the ID is
IronOrePredictionDevice
.Select the Set Modules section.
Under Container Registry Credentials, enter the following values:
Field Value Name Registry name Address Login server User Name Username Password Password
Build, push, and deploy the Data Generator Module
Clone the project files to your machine.
Open the file IronOre_Silica_Predict.sln using Visual Studio 2019
Update the container registry details in the deployment.template.json
"registryCredentials": { "RegistryName": { "username": "", "password": "", "address": "" } }
Update the modules.json file to specify the target container registry (or repository for the module)
"image": { "repository":"samplerepo.azurecr.cn/ironoresilicapercent", "tag": }
Execute the project in either debug or release mode to ensure the project runs without any issues
Push the project to your container registry by right-clicking the project name and then selecting Build and Push IoT Edge Modules.
Deploy the Data Generator module as an IoT Edge module to your Edge device.
Deploy the Azure SQL Edge module
Deploy the Azure SQL Edge module by selecting on + Add and then IoT Edge Module.
Set the configuration options in Add IoT Edge Modules page to deploy Azure SQL Edge module. For more information on the configuration options, see Deploy Azure SQL Edge.
Add the
MSSQL_PACKAGE
environment variable to the Azure SQL Edge module deployment, and specify the SAS URL of the database dacpac file created in step 8 of Part one of this tutorial.Select update
On the Set modules on device page, select Next: Routes >.
On the routes pane of the Set modules on device page, specify the routes for module to IoT Edge hub communication as described below. Make sure to update the module names in the following route definitions.
FROM /messages/modules/<your_data_generator_module>/outputs/IronOreMeasures INTO BrokeredEndpoint("/modules/<your_azure_sql_edge_module>/inputs/IronOreMeasures")
For example:
FROM /messages/modules/ASEDataGenerator/outputs/IronOreMeasures INTO BrokeredEndpoint("/modules/AzureSQLEdge/inputs/IronOreMeasures")
On the Set modules on device page, select Next: Review + create >
On the Set modules on device page, select Create
Create and start the T-SQL Streaming Job in Azure SQL Edge.
Open Azure Data Studio.
In the Welcome tab, start a new connection with the following details:
Field Value Connection type Microsoft SQL Server Server Public IP address mentioned in the VM that was created for this demo Username sa Password The strong password that was used while creating the Azure SQL Edge instance Database Default Server group Default Name (optional) Provide an optional name Select Connect.
In the File menu tab, open a new notebook or use the keyboard shortcut Ctrl + N.
In the new Query window, execute the script below to create the T-SQL Streaming job. Before executing the script, make sure to change the following variables:
@SQL_SA_Password
: TheMSSQL_SA_PASSWORD
value specified while deploying the Azure SQL Edge Module.
USE IronOreSilicaPrediction; GO DECLARE @SQL_SA_Password VARCHAR(200) = '<SQL_SA_Password>'; DECLARE @query VARCHAR(MAX); /* Create objects required for streaming */ CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'MyStr0ng3stP@ssw0rd'; IF NOT EXISTS ( SELECT name FROM sys.external_file_formats WHERE name = 'JSONFormat' ) BEGIN CREATE EXTERNAL FILE FORMAT [JSONFormat] WITH (FORMAT_TYPE = JSON) END IF NOT EXISTS ( SELECT name FROM sys.external_data_sources WHERE name = 'EdgeHub' ) BEGIN CREATE EXTERNAL DATA SOURCE [EdgeHub] WITH (LOCATION = N'edgehub://') END IF NOT EXISTS ( SELECT name FROM sys.external_streams WHERE name = 'IronOreInput' ) BEGIN CREATE EXTERNAL STREAM IronOreInput WITH ( DATA_SOURCE = EdgeHub, FILE_FORMAT = JSONFormat, LOCATION = N'IronOreMeasures' ) END IF NOT EXISTS ( SELECT name FROM sys.database_scoped_credentials WHERE name = 'SQLCredential' ) BEGIN SET @query = 'CREATE DATABASE SCOPED CREDENTIAL SQLCredential WITH IDENTITY = ''sa'', SECRET = ''' + @SQL_SA_Password + '''' EXECUTE (@query) END IF NOT EXISTS ( SELECT name FROM sys.external_data_sources WHERE name = 'LocalSQLOutput' ) BEGIN CREATE EXTERNAL DATA SOURCE LocalSQLOutput WITH ( LOCATION = 'sqlserver://tcp:.,1433', CREDENTIAL = SQLCredential ) END IF NOT EXISTS ( SELECT name FROM sys.external_streams WHERE name = 'IronOreOutput' ) BEGIN CREATE EXTERNAL STREAM IronOreOutput WITH ( DATA_SOURCE = LocalSQLOutput, LOCATION = N'IronOreSilicaPrediction.dbo.IronOreMeasurements' ) END EXEC sys.sp_create_streaming_job @name = N'IronOreData', @statement = N'Select * INTO IronOreOutput from IronOreInput'; EXEC sys.sp_start_streaming_job @name = N'IronOreData';
Use the following query to verify that the data from the data generation module is being streamed into the database.
SELECT TOP 10 * FROM dbo.IronOreMeasurements ORDER BY timestamp DESC;
In this tutorial, we deployed the data generator module and the SQL Edge module. Then we created a streaming job to stream the data generated by the data generation module to SQL.