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Configure Discovery Hub® with Azure SQL Managed Instance, Data Lake, and Azure Analysis Services

Overview

This guide will cover how to deploy and configure your environment using the Azure Marketplace App: Discovery Hub with Azure Data Lake, SQL MI, and AAS

The deployment of the Azure resources will vary depending on Azure resource availability. Deploying Azure SQL Database Managed Instance generally takes 3-6 hours. Configuring your Discovery Hub environment generally takes ~20 minutes.

Complete the following steps to configure Discovery Hub with Azure SQL Managed Instance, Data Lake, and Azure Analysis Services:

  1. Deploy Discovery Hub with Azure Data Lake, SQL MI, and AAS
  2. Configure Accounts and Permissions
  3. On-Premise Data Gateway Setup and Configuration
  4. Register Application
  5. Find the server names
  6. Connect to the virtual machine
  7. Configure the Discovery Hub Environment
    • Activate Discovery Hub
    • Configure the project repository
    • Add a Modern Data Warehouse
    • Add Azure Analysis Service Tabular Model
  8. Configure the ODX Server

1. Deploying Discovery Hub® with Azure Data Lake and Managed Instance and Azure Analysis Services

  1. Go to https://azuremarketplace.microsoft.com/en-us/marketplace/
  2. If you are not signed in to your account, sign in now
  3. In the Azure Marketplace, perform a search for TimeXtender
  4. Select the deployment option from the search results.
  5. Scroll down and select Get it Now and then select Continue. You will be redirected to a page that contains a wizard for creating your resources.
  6. In Step 1 of the wizard, configure basic settings, and then click OK.

 DL__MI__AAS_step_1.png

Setting

Description

Default Value

Requirements

Virtual Machine Name

The name of the virtual machine

Discoveryhub-vm

Must be between 3 and 79 characters long and contain letters, numbers and hyphens only.

Managed Instance Name

The name of the managed instance

dhmanagedinstance

Must be between 3 and 63 characters and contain lowercase letters, numbers, and hyphens only.

Analysis Services Name Prefix

Prefix for the Azure Analysis Services

discoveryhubas

A randomly generated suffix will be applied. Must be between 3 and 24 characters long (with suffix) and only contain lowercase letters.

Subscription

The subscription to place the resources in

 

 

Resource Group

The resources group that will contain all deployment items

 

Must be an empty resource group

Location

Location of the resource group

 

 

 

 7. In Step 2 of the wizard, configure the Analysis Services resources and settings, and then click OK.

DL__MI__AAS_step_2.png

Setting

Description

Default Value

Requirements

Pricing Tier

Choose the tier (size) of Azure Analysis Services

 

Must be a valid Azure Active Directory user

Administrator

Administrator of Azure Analysis Services

 

Must be a valid Azure Active Directory user

 

8. In Step 3 of the wizard, configure the Data Lake resources and settings, and then click OK.

DL__MI__AAS_Step_3.png

Setting

Description

Default Value

Requirements

Data Lake Location

Location of the data lake store

 

 

Enable Encryption

Select whether to enable or disable encryption

No

 

 

9. In Step 4 of the wizard, configure the virtual machine’s resources and settings, and then click OK.

DL__MI__AAS_step_4.png

Setting

Description

Default Value

Requirements

Virtual machine password

Administrator username for the virtual machine

 

Cannot be the name “Administrator”

Administrator’s password

Password for the virtual machine administrator

 

The password must contain at least 12 characters, with at least 1 letter and 1 number

Confirm Password

 

 

Must contain at least 12 characters, with at least 1 letter and 1 number

Virtual Machine Size

Size of the virtual machine

Standard_DS2_V2 

 

Diagnostic storage account

Select an existing storage account or create a new one.

<virtual machine name>-randomly generated number

Must be unique

Public IP Address for the VM

Select an existing IP address or create a new one

<virtual machine name>-ip

 

DNS Prefix for the public IP Address

DNS prefix for the public IP address

<virtual machine name>-randomly generated number

Must be unique

Virtual Network

Select an existing virtual network or create a new one

VirtualNetwork

 

Virtual Network Address Space

Address space for the virtual network

10.0.0.0/16

See networking requirements below

Managed Instance Subnet name

Name of the subnet that will contain the managed instance

miSubnet

 

Managed Instance Subnet Address Prefix

 

 

See networking requirements below

Management Subnet Name

Name of the subnet for the managed instance subnet

managementSubnet

 

Management Subnet Address Prefix

Address range for the management subnet

10.0.1.0/24

See networking requirements below

 Networking Requirements

When designing the Managed Instance network, keep the following in mind:

  • When choosing an existing virtual network, Azure will “grey out” any network that does not satisfy the requirements.
  • The subnet that the Managed Instance is deployed to must be empty
  • If more instances, resources or connections are needed then adequate space is needed for them.
  • When deciding on the virtual network address space, keep in mind that Azure requires the following IP addresses for the Managed Instance subnet:
    • Five addresses for its own needs
    • Each General Purpose instance needs an additional 2 addresses
    • Each Business Critical instance needs an additional 4 addresses
  • The virtual network address space needs a minimum of 64 addresses (/26 prefix)
  • While Azure only requires a subnet size with a minimum of 16 IP addresses, we follow their recommendations and therefore require the managed instance to have at least a /27 prefix (32 addresses).
  • The management subnet has a minimum of a /29 prefix (8 address, 3 usable). Keep in mind that Azure reserves the first 3 possible addresses for its own use.

11. In Step 5 of the Wizard, configure the managed instance resources and settings and click OK.

DL__MI__AAS_Step_5.png

 

  1. In Step 6 of the Wizard, confirm the summary settings by clicking
  2. In Step 7 of the wizard, review the terms of the agreements and click Create to initialize the deployment to the resource group you chose.

*Please note that deployment will vary depending on Azure resource availability. Select the Notifications icon at the top to view the status of your deployment

2.  Configure Accounts and Permissions 

Ensure the users, user groups, and service accounts have the necessary access and rights to the new server. Below are the required access and rights.

Accounts 

User Accounts 

Identify and/or create the following user accounts. Azure Active Directory (AAD), is recommended if using the Hybrid or Cloud configurations but the permissions are the same for local Active Directory (AD). If utilizing Azure Analysis Services then Azure Active Directory is required.  

  1. One user account for each Discovery Hub developer. 
  2. One Service Account must be created for each “non-development” environment. These will be used to run the Discovery Hub Multiple Environment and Scheduler Services. 

Security Group 

Create an Active Directory (AD) Security Group called TXDevelopers and add the developer user accounts. This will make it easier to apply permissions as developers work on and off the project. 

Application Server 

Local or Domain Administrator on the Application Server. This is required to be able to start and stop services. 

Database Permissions 

Azure SQL Managed Instance 

The following permissions are needed when using Azure SQL Managed Instance: 

  • Data sources – db_datareader. 
  • Target databases – sysadmin or dbOwner. Note that if using dbOwner instead of sysAdmin, a user account with at least dbCreator rights must log in and create the project repository database from within the project repository settings dialog. 

Azure Analysis Services 

The following permissions are needed when using Azure Analysis Services (AAS): 

  • Analysis Services Admin permissions based from an Azure Active Directory login.

3. Find the Server Names

1. Once your items have been deployed to your resource group, navigate to the resource group in Azure that contains all of the deployment items. This was assigned when configuring basic settings.

2. While viewing the Resource Group that contains all of your deployment items, find the SQL Managed Instance and click on it.

3. While viewing your managed instance, there will be a field called Host that contains your server name. Save this name somewhere safe because it will be needed for your configuring Discovery Hub®

MI_Host.png

4. To find the server name for Azure Analysis Services, go back to your Resource Group, find your Analysis Services resource and click on it.

5. When viewing the Overview section of the menu bar, there will be a field named Management Server name. Save this name somewhere safe because it will be needed for AAS endpoint.

AAS_Server_Name.png

4. On-Premise data gateway setup and configuration

If you are connecting to on-premises data sources, you will need to configure an on-premises data gateway to provide secure data transfer between on-premises data sources and your Azure Analysis Services servers in the cloud.

1. Follow this Microsoft guide for installing and configuring the on-premise data gateway: https://docs.microsoft.com/en-us/azure/analysis-services/analysis-services-gateway-install

2. Follow this Microsoft guide to configure Azure Analysis Services to communicate with the managed instance: https://azure.microsoft.com/en-us/blog/azure-analysis-services-integration-with-azure-virtual-networks-vnets/

5. Register Application

1. In order to access the data lake resources from Discovery Hub, you will need to register an application. Click on Azure Active Directory in the left column.

2. Click on App Registrations in the menu bar on the left.

3. Click New Application Registration

DL_App_Registration_1.png

4. Choose a new for your application, and select Web app/ API as its Type. The value of Sign-on URL is the URL at which your application is hosted. Click OK. 

5. Go to Settings > Required Permissions > Add > Select an API

App_Add_API.png

6. Find Azure Data Lake and select it. Next, under Select Permission check the box that says Have full access to the Azure Data Lake Service.

Enable_Access.png

7. Click Done to save your changes and go back Settings > Keys to create a new customer key. This key is encrypted after save so the application key needs to be documented somewhere safe. The key value will appear after you click

Customer_Key.png

8. Go back to the resource group and select the Data Lake Analytics resource. In the menu bar on the left select Access Control (IAM) and add a role assignment. Make the app you just created an owner of the resource. Repeat this step for Data Lake Storage Gen 1 in the resource group as well.

DL_Access_Control.png

6. Connect to the Virtual Machine

1. In order to activate and configure Discovery Hub, connect to the application server deployed on Azure. Navigate to the resource group in Azure that contains all of the deployment items. 

2. Locate the Virtual Machine in the resource group and click on it.

3. While viewing the page for the virtual machine, click Connect and download the RDP

4. Open the RDP file once it has downloaded and click Connect

5. Enter in the credentials to connect to the virtual machine that you created earlier and click Ok to connect.

Connect_to_VM.png

7.Configure the Discovery Hub® Environment

Activate Discovery Hub

Once you are connected to the Virtual Machine, activate your Discovery Hub instance following the instructions below to set up the project repository and ensure that the Discovery Hub Scheduler service is up and running. The latest version of Discovery Hub is already downloaded and installed on the virtual machine so you can skip steps 1-7 on the accompanying article.

Configure the Discovery Hub Environment

 

Add a Modern Data Warehouse

1. Once you have created your project, right-click Data Warehouse, and then select Add Data Warehouse

Add_DW_1.png

2. In the Name field, type a name for the data warehouse. The name cannot exceed 15 characters in length

3. In the Server Name field, enter the server name for the managed instance you created.

4. In the Database field, type the name of a new database, and then click Create

5. Select SQL Server Authentication and enter the managed instance credentials that you created earlier.

Add_DW_2.png

6. Click OK to close the window and return to Discovery Hub.

Add an Azure Analysis Services Tabular Model

  1. In Discovery Hub®, go to the Semantic tab, right-click on Models and select Add Semantic Model.
  2. Give your semantic model a name and click OK
  3. Expand your new model, right-click on Endpoints, and select Add Analysis Services Tabular Endpoint
  4. In the Name field, type a name for the endpoint.
  5. In the Server Name field, enter the management server name for the Azure Analysis Services deployed earlier.
  6. In the Database field, type the name of a new or existing database.
    • If you type in the name for a new database, it will not appear in Analysis Services until you deploy your model.
  7. Select SQL Server Authentication and type in the Azure Analysis Services credentials that you assigned earlier.
    • You can use the service account, but only if it has rights on the Azure Analysis Services server.
  8. Click OK to close the window and return to Discovery Hub.

8. Configuring the ODX Server

Please see the article, Configure and Manage the ODX Server, for configuring the ODX Server using Azure Data Lake for data storage.

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