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Deploy BDC in Azure Kubernetes Service (AKS) private cluster

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Important

The Microsoft SQL Server 2019 Big Data Clusters add-on will be retired. Support for SQL Server 2019 Big Data Clusters will end on February 28, 2025. All existing users of SQL Server 2019 with Software Assurance will be fully supported on the platform and the software will continue to be maintained through SQL Server cumulative updates until that time. For more information, see the announcement blog post and Big data options on the Microsoft SQL Server platform.

This article explains how to deploy SQL Server Big Data Clusters on Azure Kubernetes Service (AKS) private cluster. This configuration supports restricted use of public IP addresses in enterprise networking environment.

A private deployment provides the following benefits:

  • Restricted use of public IP addresses
  • Network traffic between application servers and cluster node pools remains only on the private network
  • Custom configuration for mandatory egress traffics to fit specific requirements

This article demonstrates how to use an AKS private cluster to restrict the use of Public IP address while respective security strings have applied.

Deploy private big data cluster with AKS private cluster

To get started, create a AKS private cluster to make sure the network traffic between API server and node pools remains on the private network only. The control plane or API server has internal IP addresses in an AKS private cluster.

This section shows you deploy a big data cluster in Azure Kubernetes Service (AKS) private cluster with advanced networking (CNI).

Create a private AKS cluster with advanced networking


export REGION_NAME=<your Azure region >
export RESOURCE_GROUP=< your resource group name >
export SUBNET_NAME=aks-subnet
export VNET_NAME=bdc-vnet
export AKS_NAME=< your aks private cluster name >
 
az group create -n $RESOURCE_GROUP -l $REGION_NAME
 
az network vnet create \
    --resource-group $RESOURCE_GROUP \
    --location $REGION_NAME \
    --name $VNET_NAME \
    --address-prefixes 10.0.0.0/8 \
    --subnet-name $SUBNET_NAME \
    --subnet-prefix 10.1.0.0/16
 

SUBNET_ID=$(az network vnet subnet show \
    --resource-group $RESOURCE_GROUP \
    --vnet-name $VNET_NAME \
    --name $SUBNET_NAME \
    --query id -o tsv)
 
echo $SUBNET_ID
## will be displayed something similar as the following: 
/subscriptions/xxxx-xxxx-xxx-xxxx-xxxxxxxx/resourceGroups/your-bdc-rg/providers/Microsoft.Network/virtualNetworks/your-aks-vnet/subnets/your-aks-subnet

Create AKS private cluster with advanced networking (CNI)

To be able to get to next step, you need to provision an AKS cluster with Standard Load Balancer with private cluster feature enabled. Your command will look like as follows:

az aks create \
    --resource-group $RESOURCE_GROUP \
    --name $AKS_NAME \
    --load-balancer-sku standard \
    --enable-private-cluster \
    --network-plugin azure \
    --vnet-subnet-id $SUBNET_ID \
    --docker-bridge-address 172.17.0.1/16 \
    --dns-service-ip 10.2.0.10 \
    --service-cidr 10.2.0.0/24 \
    --node-vm-size Standard_D13_v2 \
    --node-count 2 \
    --generate-ssh-keys

After a successful deployment, you can go to <MC_yourakscluster> resource group and you'll find the kube-apiserver is a private endpoint. For example, see the following section.

Connect to an AKS cluster

az aks get-credentials -n $AKS_NAME -g $RESOURCE_GROUP

Build Big Data Cluster deployment profile

After connecting to an AKS cluster, you can start to deploy BDC, and you can prepare the environment variable and initiate a deployment:

azdata bdc config init --source aks-dev-test --target private-bdc-aks --force

Generate and config BDC custom deployment profile:

azdata bdc config replace -c private-bdc-aks/control.json -j "$.spec.docker.imageTag=2019-CU6-ubuntu-16.04"
azdata bdc config replace -c private-bdc-aks/control.json -j "$.spec.storage.data.className=default"
azdata bdc config replace -c private-bdc-aks/control.json -j "$.spec.storage.logs.className=default"

azdata bdc config replace -c private-bdc-aks/control.json -j "$.spec.endpoints[0].serviceType=NodePort"
azdata bdc config replace -c private-bdc-aks/control.json -j "$.spec.endpoints[1].serviceType=NodePort"

azdata bdc config replace -c private-bdc-aks/bdc.json -j "$.spec.resources.master.spec.endpoints[0].serviceType=NodePort"
azdata bdc config replace -c private-bdc-aks/bdc.json -j "$.spec.resources.gateway.spec.endpoints[0].serviceType=NodePort"
azdata bdc config replace -c private-bdc-aks/bdc.json -j "$.spec.resources.appproxy.spec.endpoints[0].serviceType=NodePort"

Deploy private SQL Server Big Data Cluster with HA

In case you are deploying a SQL Server Big Data Cluster (SQL-BDC) with high availability (HA), you'll be using deploy aks-dev-test-ha deployment profile. After a successful deployment, you can use the same kubectl get svc command and you'll see an additional master-secondary-svc service is created. You need to configure ServiceType as NodePort. Other steps will be similar to what mentioned in previous section.

The following example sets the ServiceType as NodePort:

azdata bdc config replace -c private-bdc-aks /bdc.json -j "$.spec.resources.master.spec.endpoints[1].serviceType=NodePort"

Deploy BDC in AKS private cluster

export AZDATA_USERNAME=<your bdcadmin username>
export AZDATA_PASSWORD=< your bdcadmin password>

azdata bdc create --config-profile private-bdc-aks --accept-eula yes

Check deployment status

The deployment will take a few minutes and you can use the following command to check the deployment status:

kubectl get pods -n mssql-cluster -w

Check the service status

Use the following command to check the services. Verify that they are all healthy without any external IPs:

kubectl get services -n mssql-cluster

See how to manage big data cluster in AKS private cluster and then the next step is to connect to a SQL Server big data cluster.

See automation scripts for this scenario at SQL Server Samples repository on GitHub.

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