Deploy Azure SQL Managed Instance in directly connected mode on AKS using an ARM Template
The following Jumpstart scenario will guide you on how to deploy a “Ready to Go” environment so you can start using Azure Arc-enabled data services and SQL Managed Instance deployed on Azure Kubernetes Service (AKS) cluster using Azure ARM Template.
By the end of this scenario, you will have an AKS cluster deployed with an Azure Arc Data Controller, SQL Managed Instance, and a Microsoft Windows Server 2022 (Datacenter) Azure client VM, installed & pre-configured with all the required tools needed to work with Azure Arc-enabled data services:
Prerequisites
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Clone the Azure Arc Jumpstart repository
git clone https://github.com/microsoft/azure_arc.git
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Install or update Azure CLI to version 2.49.0 and above. Use the below command to check your current installed version.
az --version
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Generate a new SSH key pair or use an existing one (Windows 10 and above now comes with a built-in ssh client).
ssh-keygen -t rsa -b 4096
To retrieve the SSH public key after it’s been created, depending on your environment, use one of the below methods:
- In Linux, use the
cat ~/.ssh/id_rsa.pub
command. - In Windows (CMD/PowerShell), use the SSH public key file that by default, is located in the
C:\Users\WINUSER/.ssh/id_rsa.pub
folder.
SSH public key example output:
ssh-rsa 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 user@pc
- In Linux, use the
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Create Azure service principal (SP). To deploy this scenario, an Azure service principal assigned with multiple Role-based access control (RBAC) roles is required:
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“Contributor” - Required for provisioning Azure resources
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“Security admin” - Required for installing Cloud Defender Azure-Arc enabled Kubernetes extension and dismiss alerts
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“Security reader” - Required for being able to view Azure-Arc enabled Kubernetes Cloud Defender extension findings
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“Monitoring Metrics Publisher” - Required for being Azure Arc-enabled data services billing, monitoring metrics, and logs management
To create it login to your Azure account run the below command (this can also be done in Azure Cloud Shell.
az login subscriptionId=$(az account show --query id --output tsv) az ad sp create-for-rbac -n "<Unique SP Name>" --role "Contributor" --scopes /subscriptions/$subscriptionId az ad sp create-for-rbac -n "<Unique SP Name>" --role "Security admin" --scopes /subscriptions/$subscriptionId az ad sp create-for-rbac -n "<Unique SP Name>" --role "Security reader" --scopes /subscriptions/$subscriptionId az ad sp create-for-rbac -n "<Unique SP Name>" --role "Monitoring Metrics Publisher" --scopes /subscriptions/$subscriptionId
For example:
az login subscriptionId=$(az account show --query id --output tsv) az ad sp create-for-rbac -n "JumpstartArcDataSvc" --role "Contributor" --scopes /subscriptions/$subscriptionId az ad sp create-for-rbac -n "JumpstartArcDataSvc" --role "Security admin" --scopes /subscriptions/$subscriptionId az ad sp create-for-rbac -n "JumpstartArcDataSvc" --role "Security reader" --scopes /subscriptions/$subscriptionId az ad sp create-for-rbac -n "JumpstartArcDataSvc" --role "Monitoring Metrics Publisher" --scopes /subscriptions/$subscriptionId
Output should look like this:
{ "appId": "XXXXXXXXXXXXXXXXXXXXXXXXXXXX", "displayName": "JumpstartArcDataSvc", "password": "XXXXXXXXXXXXXXXXXXXXXXXXXXXX", "tenant": "XXXXXXXXXXXXXXXXXXXXXXXXXXXX" }
NOTE: If you create multiple subsequent role assignments on the same service principal, your client secret (password) will be destroyed and recreated each time. Therefore, make sure you grab the correct password.
NOTE: The Jumpstart scenarios are designed with as much ease of use in-mind and adhering to security-related best practices whenever possible. It is optional but highly recommended to scope the service principal to a specific Azure subscription and resource group as well considering using a less privileged service principal account
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Automation Flow
For you to get familiar with the automation and deployment flow, below is an explanation.
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User is editing the ARM template parameters file (1-time edit). These parameters values are being used throughout the deployment.
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Main azuredeploy ARM template will initiate the deployment of the linked ARM templates:
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VNET - Deploys a Virtual Network with a single subnet to be used by the Client virtual machine.
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aks - Deploys the AKS cluster where all the Azure Arc data services will be deployed.
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clientVm - Deploys the client Windows VM. This is where all user interactions with the environment are made from.
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logAnalytics - Deploys Azure Log Analytics workspace to support Azure Arc-enabled data services logs uploads.
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User remotes into client Windows VM, which automatically kicks off the DataServicesLogonScript PowerShell script that deploy and configure Azure Arc-enabled data services on the AKS cluster including the data controller and SQL Managed Instance.
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In addition to deploying the data controller and SQL Managed Instance, the sample AdventureWorks database will restored automatically for you as well.
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Deployment
As mentioned, this deployment will leverage ARM templates. You will deploy a single template that will initiate the entire automation for this scenario.
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The deployment is using the ARM template parameters file. Before initiating the deployment, edit the azuredeploy.parameters.json file located in your local cloned repository folder. An example parameters file is located here.
-
sshRSAPublicKey
- Your SSH public key -
spnClientId
- Your Azure service principal id -
spnClientSecret
- Your Azure service principal secret -
spnTenantId
- Your Azure tenant id -
windowsAdminUsername
- Client Windows VM Administrator name -
windowsAdminPassword
- Client Windows VM Password. Password must have 3 of the following: 1 lower case character, 1 upper case character, 1 number, and 1 special character. The value must be between 12 and 123 characters long. -
logAnalyticsWorkspaceName
- Unique name for the deployment log analytics workspace. -
deploySQLMI
- Boolean that sets whether or not to deploy SQL Managed Instance, for this Azure Arc-enabled SQL Managed Instance scenario we will set it to true. -
SQLMIHA
- Boolean that sets whether or not to deploy SQL Managed Instance with high-availability (business continuity) configurations, set this to either true or false. -
deployPostgreSQL
- Boolean that sets whether or not to deploy PostgreSQL, for this scenario we leave it set to false. -
deployBastion
- Choice (true | false) to deploy Azure Bastion or not to connect to the client VM. -
bastionHostName
- Azure Bastion host name.NOTE: In case you decided to deploy SQL Managed Instance in an highly-available fashion, refer to the “High Availability” section in this scenario. Also note that this capability is currently in preview.
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To deploy the ARM template, navigate to the local cloned deployment folder and run the below command:
az group create --name <Name of the Azure resource group> --location <Azure Region> az deployment group create \ --resource-group <Name of the Azure resource group> \ --name <The name of this deployment> \ --template-uri https://raw.githubusercontent.com/microsoft/azure_arc/main/azure_arc_data_jumpstart/aks/ARM/azuredeploy.json \ --parameters <The *azuredeploy.parameters.json* parameters file location>
NOTE: Make sure that you are using the same Azure resource group name as the one you’ve just used in the
azuredeploy.parameters.json
fileFor example:
az group create --name Arc-Data-Demo --location "East US" az deployment group create \ --resource-group Arc-Data-Demo \ --name arcdata \ --template-uri https://raw.githubusercontent.com/microsoft/azure_arc/main/azure_arc_data_jumpstart/aks/ARM/azuredeploy.json \ --parameters azuredeploy.parameters.json
NOTE: The deployment time for this scenario can take ~15-20min
NOTE: If you receive an error message stating that the requested VM size is not available in the desired location (as an example: ‘Standard_D8s_v3’), it means that there is currently a capacity restriction for that specific VM size in that particular region. Capacity restrictions can occur due to various reasons, such as high demand or maintenance activities. Microsoft Azure periodically adjusts the available capacity in each region based on usage patterns and resource availability. To continue deploying this scenario, please try to re-run the deployment using another region.
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Once Azure resources have been provisioned, you will be able to see them in the Azure portal. At this point, the resource group should have 8 various Azure resources deployed (If you chose to deploy Azure Bastion, you will have 9 Azure resources).
Windows Login & Post Deployment
Various options are available to connect to Arc-Data-Client VM, depending on the parameters you supplied during deployment.
- RDP - available after configuring access to port 3389 on the Arc-Data-Client-NSG, or by enabling Just-in-Time access (JIT).
- Azure Bastion - available if
true
was the value of yourdeployBastion
parameter during deployment.
Connecting directly with RDP
By design, port 3389 is not allowed on the network security group. Therefore, you must create an NSG rule to allow inbound 3389.
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Open the Arc-Data-Client-NSG resource in Azure portal and click “Add” to add a new rule.
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Specify the IP address that you will be connecting from and select RDP as the service with “Allow” set as the action. You can retrieve your public IP address by accessing https://icanhazip.com or https://whatismyip.com.
Connect using Azure Bastion
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If you have chosen to deploy Azure Bastion in your deployment, use it to connect to the VM.
NOTE: When using Azure Bastion, the desktop background image is not visible. Therefore some screenshots in this guide may not exactly match your experience if you are connecting with Azure Bastion.
Connect using just-in-time access (JIT)
If you already have Microsoft Defender for Cloud enabled on your subscription and would like to use JIT to access the Client VM, use the following steps:
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In the Client VM configuration pane, enable just-in-time. This will enable the default settings.
Post Deployment
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At first login, as mentioned in the “Automation Flow” section above, the DataServicesLogonScript PowerShell logon script will start it’s run.
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Let the script to run its course and do not close the PowerShell session, this will be done for you once completed. Once the script will finish it’s run, the logon script PowerShell session will be closed, the Windows wallpaper will change and both the Azure Arc Data Controller and SQL Managed Instance will be deployed on the cluster and be ready to use.
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Since this scenario is deploying the Azure Arc Data Controller and SQL Managed Instance, you will also notice additional newly deployed Azure resources in the resources group (at this point you should have 12 various Azure resources deployed. The important ones to notice are:
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Azure Arc-enabled Kubernetes cluster - Azure Arc-enabled data services deployed in directly connected are using this type of resource in order to deploy the data services cluster extension as well as for using Azure Arc Custom locations.
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Custom location - provides a way for tenant administrators to use their Azure Arc-enabled Kubernetes clusters as target locations for deploying Azure services instances.
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Azure Arc Data Controller - The data controller that is now deployed on the Kubernetes cluster.
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Azure Arc-enabled SQL Managed Instance - The SQL Managed Instance that is now deployed on the Kubernetes cluster.
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As part of the automation, Azure Data Studio is installed along with the Azure Data CLI, Azure CLI, Azure Arc and the PostgreSQL extensions. Using the Desktop shortcut created for you, open Azure Data Studio and click the Extensions settings to see the installed extensions.
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Additionally, the SQL Managed Instance connection will be configured automatically for you. As mentioned, the sample AdventureWorks database was restored as part of the automation.
Cluster extensions
In this scenario, two Azure Arc-enabled Kubernetes cluster extensions were installed:
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azuremonitor-containers - The Azure Monitor Container Insights cluster extension. To learn more about it, you can check our Jumpstart “Integrate Azure Monitor for Containers with GKE as an Azure Arc Connected Cluster using Kubernetes extensions scenario.
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arc-data-services - The Azure Arc-enabled data services cluster extension that was used throughout this scenario in order to deploy the data services infrastructure.
In order to view these cluster extensions, click on the Azure Arc-enabled Kubernetes resource Extensions settings.
High Availability with SQL Always-On availability groups
Azure Arc-enabled SQL Managed Instance is deployed on Kubernetes as a containerized application and uses kubernetes constructs such as stateful sets and persistent storage to provide built-in health monitoring, failure detection, and failover mechanisms to maintain service health. For increased reliability, you can also configure Azure Arc-enabled SQL Managed Instance to deploy with extra replicas in a high availability configuration.
For showcasing and testing SQL Managed Instance with Always On availability groups, a dedicated Jumpstart scenario is available to help you simulate failures and get hands-on experience with this deployment model.
Operations
Azure Arc-enabled SQL Managed Instance stress simulation
Included in this scenario, is a dedicated SQL stress simulation tool named SqlQueryStress automatically installed for you on the Client VM. SqlQueryStress will allow you to generate load on the Azure Arc-enabled SQL Managed Instance that can be done used to showcase how the SQL database and services are performing as well to highlight operational practices described in the next section.
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To start with, open the SqlQueryStress desktop shortcut and connect to the SQL Managed Instance primary endpoint IP address. This can be found in the SQLMI Endpoints text file desktop shortcut that was also created for you alongside the username and password you used to deploy the environment.
NOTE: Secondary SQL Managed Instance endpoint will be available only when using the HA deployment model (“Business Critical”).
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To connect, use “SQL Server Authentication” and select the deployed sample AdventureWorks database (you can use the “Test” button to check the connection).
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To generate some load, we will be running a simple stored procedure. Copy the below procedure and change the number of iterations you want it to run as well as the number of threads to generate even more load on the database. In addition, change the delay between queries to 1ms for allowing the stored procedure to run for a while.
exec [dbo].[uspGetEmployeeManagers] @BusinessEntityID = 8
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As you can see from the example below, the configuration settings are 100,000 iterations, five threads per iteration, and a 1ms delay between queries. These configurations should allow you to have the stress test running for a while.
Azure Arc-enabled SQL Managed Instance monitoring using Grafana
When deploying Azure Arc-enabled data services, a Grafana instance is also automatically deployed on the same Kubernetes cluster and include built-in dashboards for both Kubernetes infrastructure as well SQL Managed Instance monitoring (PostgreSQL dashboards are included as well but we will not be covering these in this section).
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Now that you have the SqlQueryStress stored procedure running and generating load, we can look how this is shown in the the built-in Grafana dashboard. As part of the automation, a new URL desktop shortcut simply named “Grafana” was created.
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[Optional] The IP address for this instance represents the Kubernetes LoadBalancer external IP that was provision as part of Azure Arc-enabled data services. Use the
kubectl get svc -n arc
command to view the metricsui external service IP address. -
To log in, use the same username and password that is in the SQLMI Endpoints text file desktop shortcut.
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Navigate to the built-in “SQL Managed Instance Metrics” dashboard.
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Change the dashboard time range to “Last 5 minutes” and re-run the stress test using
SqlQueryStress
(in case it was already finished). -
You can now see how the SQL graphs are starting to show increased activity and load on the database instance.
Cleanup
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If you want to delete the entire environment, simply delete the deployment resource group from the Azure portal.