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Last updated
The Azure-WEKA Terraform package contains modules and examples to customize according to your deployment needs. The installation is based on applying the customized Terraform variables file to a predefined Azure subscription.
Applying the Terraform variables file performs the following:
Creates resources in a predefined resource group, such as virtual machines, network interfaces, function apps, load balancer, and more.
Deploys Azure virtual machines.
Installs the WEKA software.
Configures the WEKA cluster.
The total deployment time is about 30 minutes. Half the time is for resource deployment. The second is for the WEKA cluster installation and configuration.
Before installing the WEKA software on Azure, the following prerequisites must be met:
The following must be installed on the workstation used for the deployment:
For an M1-based Mac workstation, see specific instructions below.
Obtain the Azure-WEKA Terraform package from and save it to a local directory. To access the package, a git account is required, and it must be associated with the WEKA git organization.
Initialize the Azure-WEKA Terraform package using terraform init
from the local directory. This command initializes a new or existing Terraform working directory by creating initial files, loading any remote state, downloading modules, and more.
Required permissions on Azure:
Privileged Role Administrator
Storage Blob Data Owner
Storage Account Contributor
Key Vault Administrator
To login to the Azure account using Azure CLI, use the az login command.
An Azure resource group is created within your subscription. The resource group also includes the Azure region.
You can use one of the provided examples as a template for the required deployment.
Go to the relevant directory in the examples directory and customize the Terraform variables file: vars.auto.tfvars
.
Ensure the prefix
and cluster_name
variables are unique across the Azure environment.
Note: The example templates are simplified and have the minimum variable inputs to customize. For additional variable inputs to customize, you can modify their default values in the main variables.tf
file, or add them to the Terraform variables file. See the README in the Azure-WEKA Terraform package for the full list of variable inputs.
To validate the configuration, run terraform plan
.
Once the configuration validation is successful, run terraform apply
.
Terraform applies the configuration on the specified Azure subscription and displays the cluster help commands.
The system displays the cluster help commands enabling you to perform the following:
Get the clusterization status
Get the cluster status
Fetch the WEKA cluster password
View the path to ssh keys
View the virtual machine IP addresses
Resize the cluster
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Once Terraform applies the configuration and deploys all the required resources, you can use the cluster help commands to check the progress of the cluster deployment.
The following is the command syntax for checking the cluster status during the deployment progress:
curl --fail https://<prefix>-<cluster name>-function-app.azurewebsites.net/api/status?code=$function_key
Explore the following phases to check the deployment progress:
Note: You can also track the cluster formation progress on the last backend (in this example, v41-jack-vmss_3
) by opening the /tmp/cluster_creation.log
file.
Once the deployment is completed, access the WEKA cluster GUI using the URL: http://<backend server DNS name or IP address>:14000
and get started with the WEKA cluster.
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If the Terraform deployment fails for any reason, such as dependencies not being present and Azure resource starvation, the destroy
command does not work properly. Manually remove any resources created at the beginning of the Terraform script using the Azure console or Azure CLI before re-running the Terraform script.
If the WEKA cluster is no longer required on Azure or you need to clean up the deployment, use the terraform destroy
action (a token from is required). The object storage and storage account are not deleted.
If you need to preserve your data, create a snapshot using .