To deploy your MATLAB® Production Server™ (BYOL) environment on Azure®, launch the Azure solution template to provision cloud resources. Once deployment to Azure is complete, use MATLAB Production Server on Azure by logging in to the MATLAB Production Server cloud console and uploading your licensing file.
Before you can deploy resources on Azure and configure your server environment, you need an Azure account and a MATLAB Production Server license.
You can upload the MATLAB Production Server license file only after provisioning the cloud resources. For more information on licensing on the cloud, see Choose an Option to Activate Your License (Licensing on the Cloud).
You are responsible for the cost of the Azure services and resources used in the deployment.
Follow these steps to deploy your server environment on Azure.
Click Create on the MATLAB Production Server (BYOL) offering page in the Azure portal. This launches the solution template where you provide values to configure your server environment.
Provision Cloud Resources. Creating resources on Azure can take up to 30 minutes.
Upload a License File using the cloud console.
You are now ready to use MATLAB Production Server (BYOL) on Azure.
To run applications on MATLAB Production Server, you will need to create applications using MATLAB Compiler SDK™. For more information, see Create a Deployable Archive for MATLAB Production Server.
If your solution uses persistence, see Edit the Azure Cache for Redis Configuration.
You need an Azure subscription before you start deploying cloud resources for MATLAB Production Server (BYOL) on Azure. Launch the MATLAB Production Server (BYOL) solution template to configure and deploy cloud resources. Click OK at the end of each step to proceed to the next step.
First, you must choose an Azure subscription, specify a resource group to hold the resources you provision, and specify a location to start your resources in.
|Subscription||Choose an Azure subscription to use for purchasing resources.|
Choose a name for the resource group to hold the resources.
Creating a new resource group for each deployment is recommended. Doing so enables you to delete all the resources for each deployment easily.
Choose the location to start resources in.
Select a location that supports your requested virtual machine (VM) instance types. For a list of resources that are supported, see Azure Region Services.
Next, you configure the server VM and data persistence. Each MATLAB Production Server instance runs on a VM and each instance runs multiple workers. To deploy a server instance, you must specify parameters for the VM, such as the size, number of VMs, and operating system.
|Server VM Size|
Specify the size of the VM to use for the server.
VM size where the number of cores on your VM matches the number of workers per
VM that you plan on using. The template defaults to
|Number of Server VMs|
Specify the number of VMs to run MATLAB Production Server instances.
The deployment template sets the default to 2 VMs for load balancing. Because the number of server instances is limited to 24, you can provision a maximum of 24 VMs.
For example, if you have
a standard 24 worker MATLAB
Production Server license and select
You can always underprovision the number of VMs. If you do so, you can end up using fewer workers than you are licensed for.
You can change the number of VMs after the initial deployment. For more information, see Change the Number of Virtual Machines.
|Server VM Operating System|
Choose the server VM operating system.
Windows® (Windows Server®) and Linux® (Ubuntu®) are the only available options.
|Create Azure Cache for Redis™|
Choose whether you want to create an Azure cache for Redis.
Creating this service allows you to use the persistence functionality of the server. Persistence provides a mechanism to cache data between calls to MATLAB code running on a server instance. For more information, see Use a Data Cache to Persist Data.
You can provision an Azure cache for Redis after the initial deployment. For setup instructions, see Azure documentation.
After you deploy the server VMs, you can manage the server using the MATLAB Production Server cloud console, which provides a web-based interface to configure and manage server instances on the cloud. Specify the login credentials for the cloud console.
Specify the admin user name to log in to the MATLAB Production Server cloud console.
Specify the admin password to log in to the MATLAB Production Server cloud console.
You can specify which IP addresses can access the cloud console, whether your solution should use a public IP address, and configure a virtual network (VNet).
|Allow Connections From IP address|
Specify the IP address or range of IP addresses that is permitted to connect to the cloud console that manages the server.
If you specify a range of IP addresses, use CIDR notation, which provides the IP address before the slash and mask after the slash. The mask determines the number of IP addresses to include.
You can use a CIDR calculator to determine the CIDR notation for a range of IP addresses.
|Make Solution Available over Internet|
Make your solution available over the Internet by setting this
If you set this parameter to
Create a new VNet or choose an existing one.
The template defaults to a creating a new VNet with predefined values. These are the values that Azure defaults to while creating a new VNet. You can use the default values or enter new values based on your network setup.
If you are using an existing VNet, you need to open the following ports.
Specify the subnet name and subnet address prefix for a new or existing subnet.
The first subnet hosts the cloud console. The second subnet hosts the application gateway.
The template defaults to creating new subnets with predefined values. You can use the default values or enter new values based on your network setup.
After you enter all the values required to configure the server environment, Azure runs a final validation. Click OK after validation passes.
Accept the Terms and Conditions. Click Create to begin the deployment. The deployment can take up to 30 minutes.
After the deployment finishes, the next step is to connect and login to the cloud console.
The MATLAB Production Server cloud console is a web-based interface to configure and manage server instances on the cloud.
The Internet Explorer® web browser is not supported for interacting with the cloud console.
Connect and log in to the cloud console. Complete these steps only after your resource group has been successfully created. This workflow assumes that your solution uses public IP addresses.
In the Azure portal, click Resource groups.
Select the resource group you created for this deployment.
Select the resource labeled servermachine-public-ip. This resource contains the public IP address of the MATLAB Production Server cloud console.
Copy the IP address from the Public IP address field.
In your browser, connect to the cloud console using the IP address. Example: https://126.96.36.199
Use the admin user name and password that you specified in Cloud Console Login to log in.
The cloud console uses a self-signed certificate, which you can change. For information on changing the self-signed certificate, see Upload an HTTPS Certificate.
The next step in the deployment is to upload a MATLAB Production Server license file.
Use the MATLAB Production Server cloud console to upload your MATLAB Production Server license file. You need a fixed MAC address to get a license file from the MathWorks® License Center. The license server MAC address for MATLAB Production Server on Azure is available only after you deploy the solution. For more information on configuring your license on the cloud, see Choose an Option to Activate Your License (Licensing on the Cloud).
Upload a new license file or replace an existing license file.
In the cloud console, select Administration > License.
Click Browse License File, select the license file you want to upload, and click Open.