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Step 1. Create Resource Group

Create the resource group where all the LHM dependent resources will reside.

  • 1 Resource Group that contains the following:

    • 1 Azure SQL Server:

      • Recommended Type: S3

    • 1 Azure Key Vault:

      • Recommended Type: Standard

    • 1 Azure Storage Account

    • 1 Service Principal in Azure AD with “ID Token” enabled

Once all deployment steps are complete, the provided resource group will include the following resources:

Storage Account: used for storing all telemetry data from the Databricks workspaces and consumption/cost/usage detail data

KeyVault: used for storing the storage account access key (if enabled for the deployment), the Azure AD App Registration client secret (for Azure AD Single Sign On into the application and optionally for accessing the Azure Blob Storage account), and finally the SQL Server Login password.

SQL Server database: used for storing the output of the analyzer and consumption data processors, feeds all the data required by the reports and dashboards

Step 2. Create Storage Account

Inside that resource group create a storage account

Step 3. Create a KeyVault

Step 4. Create a Azure SQL Server with Azure SQL Database

Create a Azure SQL Server and inside it create a Azure SQL Database with SQL authentication enabled.

Step 5. Create Database secret

The password you will save as a secret in the Key Vault with the following secret name: mssql-password

Step 6. Create a Azure App Registration

Create a Azure App Registration and fill in the Redirect URI with the following value: 

https://<dns label used below>.<location>.azurecontainer.io/login/oauth2/code/azure

Step 7. Edit App Roles

On the App Roles section in the Azure App Registration configuration panel, you can create the LHM admin and user roles which you can later use to control users access to the Lakehouse Monitor.

Step 8. Create Client Secret

Create a client secret for your Application and save the secret in the KeyVault you’ve created with the following secret name msft-provider-auth-secret

Step 9. Create Managed Identity

Create a managed Identity that will be used by the Application to communicate to the keyvault and storage account.

Step 10. Edit Access policies

Add the necessary access policy on the Key Vault so the managed identity is able to list and read secrets from it.

  • In the Azure Portal, go to your KeyVault created in step 3.

  • In the left hand sidebar click on Access Policies

  • Click on Create

  • From the Secrets section check List and Get as the permissions to be added

  • Search for the Managed Identity created on step 9 and select it. Click Next.

  • Skip the Application step as it’s optional

  • Click Create

Step 11. Configure SSL Communication

For SSL communication you can use one of these two options:

  1. https://learn.microsoft.com/en-gb/azure/api-management/api-management-key-concepts

  2. https://learn.microsoft.com/en-us/azure/container-instances/container-instances-container-group-ssl

    1. recommended

Step 12. Create YAML definitions

Create YAML definition for the containers

apiVersion: '2019-12-01'
location: <location>
name: <name of your container instance>
properties:
  containers:
  - name: lakehouse-monitor
    properties:
      environmentVariables:
      - name: APPLICATION_LOG_HTTPHEADER
        value: false
      - name: APPSERVICE_URL
        value: <FQDN>
      - name: AZURE_KEYVAULT_ENABLED
        value: true
      - name: AZURE_KEYVAULT_TENANTID
        value: <KV tenantID>
      - name: AZURE_KEYVAULT_URI
        value: <KV URL>
      - name: AZURE_MANAGED_IDENTITY_ID
        value: <managed identity objectID>
      - name: AZURE_MANAGED_IDENTITY_APP_ID
        value: <managed identity clientID>
      - name: LOG_LEVEL
        value: info
      - name: LOG_LEVEL_APP
        value: info
      - name: LOG_LEVEL_HTTP_HEADERS
        value: error
      - name: USE_SP_FOR_BACKGROUND_PROCESSORS
        value: true
      - name: USE_SP_FOR_STORAGE_ACCOUNT
        value: true
      - name: MICROSOFT_PROVIDER_AUTHENTICATION_SECRET
        value: ${msft-provider-auth-secret}
      - name: SERVICE_PRINCIPAL_CLIENT_SECRET
        value: ${msft-provider-auth-secret}
      - name: SERVICE_PRINCIPAL_CLIENTID
        value: <sp clientID>
      - name: SERVICE_PRINCIPAL_OBJECTID
        value: <sp objectID>
      - name: SERVICE_PRINCIPAL_TENANTID
        value: <sp tenantID>
      - name: SQL_DATABASE
        value: <sql database name>
      - name: SQL_SERVER_HOST
        value: <sql server host>
      - name: SQL_USER
        value: <sql username>
      - name: SQL_PASSWORD
        value: ${mssql-password}
      - name: STORAGE_AZURE_ACCOUNT
        value: <storage account name>
      - name: STORAGE_AZURE_CONTAINER
        value: lakehouse-monitor
      - name: CLOUD_PROVIDER
        value: azure
      - name: AUTHENTICATION_PROVIDER
        value: active-directory
      - name: SERVER_SERVLET_SESSION_PERSISTENT
        value: true
      - name: SERVER_SSL_ENABLED
        value: false
      - name: METRIC_PROCESSING_ENABLED
        value: true
      - name: METRIC_PROCESSOR_DOCTOR_INITIAL_DELAY
        value: PT1M
      - name: CONSUMPTION_USE_PREFILTER
        value: false
      - name: ADMIN_APP_ROLE
        value: <admin role value>
      - name: EXECUTIVE_APP_ROLE
        value: <executive role value>
      - name: AUTHORIZATION_CACHE_TIMEOUT
        value: 1800
      - name: SERVER_PORT
        value: 80
      image: blueprint.azurecr.io/bpcs/lakehouse-optimizer:2.1
      ports:
      - port: 80
      resources:
        requests:
          cpu: 4
          memoryInGB: 8
      volumeMounts:
      - mountPath: /var/log
        name: logs
  - name: nginx-with-ssl
    properties:
      image: mcr.microsoft.com/oss/nginx/nginx:1.15.5-alpine
      ports:
      - port: 443
        protocol: TCP
      resources:
        requests:
          cpu: 1.0
          memoryInGB: 1.5
      volumeMounts:
      - name: nginx-config
        mountPath: /etc/nginx
  imageRegistryCredentials:
  - server: blueprint.azurecr.io
    username: <ACR Username>
    password: <ACR Password>
  osType: Linux
  restartPolicy: Always
  ipAddress:
    type: Public
    ports:
      - port: 443
    dnsNameLabel: <dns label>
  volumes:
  - name: nginx-config
    secret:
      ssl.crt: <BASE64 enc ssl.crt>
      ssl.key: <BASE64 enc ssl.key>
      nginx.conf: <BASE64 enc nginx.conf>
  - name: logs
    azureFile:
      sharename: <name of share for the logs>
      storageAccountName: <storage account name where the share is created>
      storageAccountKey: <storage account key>
tags: {}
type: Microsoft.ContainerInstance/containerGroups

Step 13. Create Containers

Create the containers:

  • recommended minimum 8 cores

az container create --resource-group <resource group name created in step 6> --assign-identity <managed identity to be used> --name <aci name> --file deploy.yaml

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