Provisioning Services in the Cloud Environment

This project provisioning all infrastructure to create environment data warehouse in Azure.
In addition, all scripts that support Azure Analysis Services are dynamically generated from a configuration file(set_variables.tfvars).

Below are the steps that must be followed to prepare the environment and run the automation:

1. Clone this project to the user's main directory on the on-premises server, example: C:\Users\PRODUCT_NAME

cd ~

2. At the initial moment, you need to create and configure a user at Azure. Follow the tutorial Azure to create a user that terraform will use.

3. Once you have created a new user at Azure, set some parameters that will be used by the terraform. Open the file set_variables.tfvars which is at the root of the project and edit the variables.

Example of how to configure the file set_variables:

# Azure
subscription_id = "11111111ffff-111b-111b-8a2e-11111111ffff"
client_id = "11111111ffff-111b-111b-8552-11111111ffff"
client_secret = "11111111ffff-111b-111b-9606-11111111ffff"
tenant_id = "11111111ffff-111b-111b-a933-11111111ffff"
6b02-494b-a933-1000020c0aad"

location = "brazilsouth"

tags =  {
    analytics = "bi"
    PRODUCT_NAME = "aa"
}

# User with access in portal Azure. Cannot be terraform user
application_user_login =  "application_user@PRODUCT_NAME.com.br"
application_user_password = "111b111b-111bd"

# Client and product name
client_name = "AA"
client_name_lower = "aa"
product_name = "PRODUCT_NAME"
product_client_name = "PRODUCT_NAME-MPAA"
product_client_name_lower = "PRODUCT_NAME-mpaa"

# If Runbooks fail, send email
email_from = "smtp@company.com.br"
email_to = "brunocampos01@gmail.com"
smtp_server = "email-smtp.com"
smtp_port = "587"

# Data source
data_source = "oracle"

# Analysis Services
large_volume_table = "fact_historic"
column_to_split = "id_column_name"
total_month = "18"

# Acess root in everyone databases of analysis services
list_admins_global = [
    "application_user@PRODUCT_NAME.com.br",
    "brunocampos01@gmail.com"
]

# Thes logins must be separeted without spaces
list_admins =  "brunocampos01@gmail.comr"
# Thes logins must be separeted without spaces
list_readers = "brunocampos01@gmail.com,application_user@PRODUCT_NAME.com.br"

3. Follow the step-by-step below to run automation correctly:

• Open PowerShell as admin
• Run the following commands on PowerShell:

cd PRODUCT_NAME-mp/main
terraform init # download modules terraform
terraform plan -var-file="..\set_variables.tfvars" -out plan.out
terraform apply -var-file="..\set_variables.tfvars" -auto-approve -parallelism=1

• From now on the provisioning and configuration of the services will start in an automated way. Go to Manual Service Provisioning in the Cloud.

Manual Service Provisioning in the Cloud

Once service provisioning has begun, you must perform a task within the cloud environment to provide scripting permission in the automation account. Follow the step-by-step below:

1. Access the Azure
2. Inside the portal go to Home > Automation-Accounts
3. From the left menu, choose Run as accounts and confirm the creation of the certificate.

On-premises Data Gateways

On-premises Data Gateway is required to transfer the data from the data source to Azure Analysis Services.

To set it up it must first be done on the machine running the local Gateway. Then, do the steps below:

1. Access the Azure
2. Wait about 15 minutes and then go to Home > On-premises Data Gateways
3. Click on them + Add

• In the table below are configuration suggestions

Parameters	Values
Resource Name	<product_name>-<client_name>-gw
Location	Brazil South
Installation Name	<product_name>-<client_name>-onpremisesgw

NOTES:

• It is important to use the same account that was logged into the data gateway on the local server.
• The Installation Name field is the name of the local gateway, configured on the local server. It should appear in the list when you click the down arrow.

Link Data Gateway with Azure Analysis Services

1. Access the Azure
2. Inside the portal go to Home > Analysis Services
3. From the left menu, choose On-premises Data Gateway
4. Now select the gateway from the list and then click on Connect Gateway

Data Processing for Azure Analysis Services

After all services are created at Azure, approximately 15 minutes, the automation account runs an update runbook of the Powershell modules and then runs the creation of the Azure Analysis Services database.

As of 40 minutes, the database is already created. To be able to process data you need to set the data source password via Visual Studio (SSDT). Follow the step-by-step below:

1. Check that Azure Analysis Services is on. To do so, access the Azure

2. Inside the portal go to Home > Analysis Services

If it's paused, just click the Start and wait for the service to begin.

3. Copy the link as indicated in the image below.

4. Open the SSDT and start a new projectto

5. Choose the option: Analysis Services > Import Tabular and renamed the project name to the standard <product_name>-<client_name>

6. The endpoint of the database will then be requested. Then at this time paste the link copied from Azure and wait for the environment preparation.

7. In the right menu, open directory Data Sources and open the connection with 2 clicks. Enter the password of the source database and test the connection. If everything goes right, confirm and save the password..

8. To avoid having to bring the data into Visual Studio (SSDT), change the following project properties. Debug > TabularProject1 Properties > Deployment Options > Processing Option > Do Not Process In this same window, change the name of the Server field to Azure Analysis Services endpoint. '

9. Build and deploy by clicking the Start button

10. Finished. The Azure Analysis Services database can now process data from data sources.

Automated Processing

From 55 min, if the data source password has been set, all partitions except the large volume partition will be processed through the automation account. In the sequence, the automation account creates and processes the large volume table partitions, makes a backup, and turns off Azure Analysis Services.

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