Deploy an Azure SQL Edge container in Kubernetes

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.

Azure SQL Edge can be deployed on a Kubernetes cluster both as an IoT Edge module through Azure IoT Edge running on Kubernetes, or as a standalone container pod. For the remainder of this article, we will focus on the standalone container deployment on a Kubernetes cluster. For information on deploying Azure IoT Edge on Kubernetes, see Azure IoT Edge on Kubernetes (preview).

This tutorial demonstrates how to configure a highly available Azure SQL Edge instance in a container on a Kubernetes cluster.

• Create an SA password
• Create storage
• Create the deployment
• Connect with SQL Server Management Studio (SSMS)
• Verify failure and recovery

Kubernetes 1.6 and later has support for storage classes, persistent volume claims, and the Azure disk volume type. You can create and manage your Azure SQL Edge instances natively in Kubernetes. The example in this article shows how to create a deployment to achieve a high availability configuration similar to a shared disk failover cluster instance. In this configuration, Kubernetes plays the role of the cluster orchestrator. When an Azure SQL Edge instance in a container fails, the orchestrator bootstraps another instance of the container that attaches to the same persistent storage.

In the preceding diagram, azure-sql-edge is a container in a pod. Kubernetes orchestrates the resources in the cluster. A replica set ensures that the pod is automatically recovered after a node failure. Applications connect to the service. In this case, the service represents a load balancer that hosts an IP address that stays the same after failure of the azure-sql-edge.

In the following diagram, the azure-sql-edge container has failed. As the orchestrator, Kubernetes guarantees the correct count of healthy instances in the replica set, and starts a new container according to the configuration. The orchestrator starts a new pod on the same node, and azure-sql-edge reconnects to the same persistent storage. The service connects to the re-created azure-sql-edge.

In the following diagram, the node hosting the azure-sql-edge container has failed. The orchestrator starts the new pod on a different node, and azure-sql-edge reconnects to the same persistent storage. The service connects to the re-created azure-sql-edge.

Prerequisites

• Kubernetes cluster

  • The tutorial requires a Kubernetes cluster. The steps use kubectl to manage the cluster.

  • For the purpose of this tutorial, we are using Azure Kubernetes Service to deploy Azure SQL Edge. See Deploy an Azure Kubernetes Service (AKS) cluster to create and connect to a single-node Kubernetes cluster in AKS with kubectl.

  Note

  To protect against node failure, a Kubernetes cluster requires more than one node.

• Azure CLI

  • The instructions in this tutorial have been validated against Azure CLI 2.10.1.

Create a Kubernetes namespace for SQL Edge deployment

Create a new namespace in the kubernetes cluster. This namespace is used to deploy SQL Edge and all the required artifacts. For more information on Kubernetes namespaces, see namespaces.

kubectl create namespace <namespace name>

Create an SA password

Create an SA password in the Kubernetes cluster. Kubernetes can manage sensitive configuration information, like passwords as secrets.

The following command creates a password for the SA account:

kubectl create secret generic mssql --from-literal=MSQL_SA_PASSWORD="MyC0m9l&xP@ssw0rd" -n <namespace name>

Replace MyC0m9l&xP@ssw0rd with a complex password.

Create storage

Configure a persistent volume and persistent volume claim in the Kubernetes cluster. Complete the following steps:

1. Create a manifest to define the storage class and the persistent volume claim. The manifest specifies the storage provisioner, parameters, and reclaim policy. The Kubernetes cluster uses this manifest to create the persistent storage.

   The following yaml example defines a storage class and persistent volume claim. The storage class provisioner is azure-disk, because this Kubernetes cluster is in Azure. The storage account type is Standard_LRS. The persistent volume claim is named mssql-data. The persistent volume claim metadata includes an annotation connecting it back to the storage class.

   kind: StorageClass
   apiVersion: storage.k8s.io/v1
   metadata:
        name: azure-disk
   provisioner: kubernetes.io/azure-disk
   parameters:
     storageaccounttype: Standard_LRS
     kind: managed
   ---
   kind: PersistentVolumeClaim
   apiVersion: v1
   metadata:
     name: mssql-data
     annotations:
       volume.beta.kubernetes.io/storage-class: azure-disk
   spec:
     accessModes:
     - ReadWriteOnce
     resources:
       requests:
         storage: 8Gi
   

   Save the file (for example, pvc.yaml).

2. Create the persistent volume claim in Kubernetes.

   kubectl apply -f <Path to pvc.yaml file> -n <namespace name>
   

   <Path to pvc.yaml file> is the location where you saved the file.

   The persistent volume is automatically created as an Azure storage account, and bound to the persistent volume claim.

   

3. Verify the persistent volume claim.

   kubectl describe pvc <PersistentVolumeClaim>  -n <name of the namespace>
   

   <PersistentVolumeClaim> is the name of the persistent volume claim.

   In the preceding step, the persistent volume claim is named mssql-data. To see the metadata about the persistent volume claim, run the following command:

   kubectl describe pvc mssql-data  -n <namespace name>
   

   The returned metadata includes a value called Volume. This value maps to the name of the blob.

   

4. Verify the persistent volume.

   kubectl describe pv -n <namespace name>
   

   kubectl returns metadata about the persistent volume that was automatically created and bound to the persistent volume claim.

Create the deployment

In this example, the container hosting the Azure SQL Edge instance is described as a Kubernetes deployment object. The deployment creates a replica set. The replica set creates the pod.

In this step, create a manifest to describe the container based on the Azure SQL Edge Docker image. The manifest references the mssql-data persistent volume claim, and the mssql secret that you already applied to the Kubernetes cluster. The manifest also describes a service. This service is a load balancer. The load balancer guarantees that the IP address persists after Azure SQL Edge instance is recovered.

1. Create a manifest (a YAML file) to describe the deployment. The following example describes a deployment, including a container based on the Azure SQL Edge container image.

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: sqledge-deployment
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: sqledge
     template:
       metadata:
         labels:
           app: sqledge
       spec:
         volumes:
           - name: sqldata
             persistentVolumeClaim:
               claimName: mssql-data
         containers:
           - name: azuresqledge
             image: mcr.microsoft.com/azure-sql-edge:latest
             ports:
               - containerPort: 1433
             volumeMounts:
               - name: sqldata
                 mountPath: /var/opt/mssql
             env:
               - name: MSSQL_PID
                 value: "Developer"
               - name: ACCEPT_EULA
                 value: "Y"
               - name: MSSQL_SA_PASSWORD
                 valueFrom:
                   secretKeyRef:
                     name: mssql
                     key: MSSQL_SA_PASSWORD
               - name: MSSQL_AGENT_ENABLED
                 value: "TRUE"
               - name: MSSQL_COLLATION
                 value: "SQL_Latin1_General_CP1_CI_AS"
               - name: MSSQL_LCID
                 value: "1033"
         terminationGracePeriodSeconds: 30
         securityContext:
           fsGroup: 10001
   ---
   apiVersion: v1
   kind: Service
   metadata:
     name: sqledge-deployment
   spec:
     selector:
       app: sqledge
     ports:
       - protocol: TCP
         port: 1433
         targetPort: 1433
         name: sql
     type: LoadBalancer
   

   Copy the preceding code into a new file, named sqldeployment.yaml. Update the following values:

   • MSSQL_PID value: "Developer": Sets the container to run Azure SQL Edge Developer edition. Developer edition isn't licensed for production data. If the deployment is for production use, set the edition to Premium.

     Note

     For more information, see How to license Azure SQL Edge.

   • persistentVolumeClaim: This value requires an entry for claimName: that maps to the name used for the persistent volume claim. This tutorial uses mssql-data.

   • name: MSSQL_SA_PASSWORD: Configures the container image to set the SA password, as defined in this section.

     valueFrom:
       secretKeyRef:
         name: mssql
         key: MSSQL_SA_PASSWORD
     

     When Kubernetes deploys the container, it refers to the secret named mssql to get the value for the password.

   Note

   By using the LoadBalancer service type, the Azure SQL Edge instance is accessible remotely (via the internet) at port 1433.

   Save the file (for example, sqledgedeploy.yaml).

2. Create the deployment.

   kubectl apply -f <Path to sqledgedeploy.yaml file> -n <namespace name>
   

   <Path to sqldeployment.yaml file> is the location where you saved the file.

   

   The deployment and service are created. The Azure SQL Edge instance is in a container, connected to persistent storage.

   To view the status of the pod, type kubectl get pod -n <namespace name>.

   

   In the preceding image, the pod has a status of Running. This status indicates that the container is ready. This may take several minutes.

   Note

   After the deployment is created, it can take a few minutes before the pod is visible. The delay is because the cluster pulls the Azure SQL Edge container image from the Docker hub. After the image is pulled the first time, subsequent deployments might be faster if the deployment is to a node that already has the image cached on it.

3. Verify the services are running. Run the following command:

   kubectl get services -n <namespace name>
   

   This command returns services that are running, as well as the internal and external IP addresses for the services. Note the external IP address for the mssql-deployment service. Use this IP address to connect to Azure SQL Edge.

   

   For more information about the status of the objects in the Kubernetes cluster, run:

   az aks browse --resource-group <MyResourceGroup> --name <MyKubernetesClustername>
   

Connect to the Azure SQL Edge instance

If you configured the container as described, you can connect with an application from outside the Azure virtual network. Use the sa account and the external IP address for the service. Use the password that you configured as the Kubernetes secret. For more information on connecting to an Azure SQL Edge instance, see Connect to Azure SQL Edge.

Verify failure and recovery

To verify failure and recovery, you can delete the pod. Do the following steps:

1. List the pod running Azure SQL Edge.

   kubectl get pods -n <namespace name>
   

   Note the name of the pod running Azure SQL Edge.

2. Delete the pod.

   kubectl delete pod sqledge-deployment-7df66c9999-rc9xl
   

   sqledge-deployment-7df66c9999-rc9xl is the value returned from the previous step for pod name.

Kubernetes automatically re-creates the pod to recover an Azure SQL Edge instance, and connect to the persistent storage. Use kubectl get pods to verify that a new pod is deployed. Use kubectl get services to verify that the IP address for the new container is the same.

Summary

In this tutorial, you learned how to deploy Azure SQL Edge containers to a Kubernetes cluster for high availability.

• Create an SA password
• Create storage
• Create the deployment
• Connect with Azure SQL Edge Management Studios (SSMS)
• Verify failure and recovery

Related content

• Introduction to Kubernetes
• Machine Learning and Artificial Intelligence with ONNX in SQL Edge.
• Building an end to end IoT Solution with SQL Edge using IoT Edge.
• Data Streaming in Azure SQL Edge