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Updated atOctober 31, 2023   06:09 AM

Creating an MLflow Instance

To create an MLflow instance, go to the "ML Platform" section. Click Add Instance.

When you click on the button, the virtual machine configurator will open in the window, consisting of several stages, as a result of which it determines the parameters of the created VM.

At all stages, the configurator informs about the cost of the created instance, additional features, and also allows you to contact support in case of questions.

During the installation process, you need to enter the following settings:

Parameter
Description
Instance name
The display name of the instance. Also sets the hostname on the OS
Type of virtual machine
Preinstalled VM configuration (CPU and RAM)
Accessibility zone
Selecting the data center where the instance will be launched
Disk size
Sets the VM disk size in GB
Disk type
Type of instance disk to be created, more
Choosing a domain name
Specifies the DNS name of the instance
JupyterHub Instance
Selecting the JupyterHub instance to which the MLflow instance will be connected

The next step is to configure the virtual network. You can select an existing network or create a new one (more details can be found in the article "Creating and deleting networks".

Parameter
Description
Network
Creating a VM in an external (ext-net) or private network. Must match the network where the JupyterHub instance is running
Virtual machine key
Used to decrypt the administrator password

After entering the settings values, click "Create Instance".

The virtual machine will be created within 10-15 minutes. During this period, the operating system is deployed to the disk of the instance, and system tools are running to configure the virtual machine in accordance with the specified parameters.