KDB.AI Version Upgrade

This section details the steps to upgrade the KDB.AI Version on Azure Machine Learning Studio.

Pre-requisites

Before you can start the upgrade process of KDB.AI on Azure Machine Learning Studio, ensure you have the following:

• An active account for Azure Machine Learning Studio.
• The correct role-based access control permissions - you need a Key Vault Administrator or Owner role in the Resource group tab, so you can view, edit, and create secrets.
• Optionally, check your current version of KDB.AI.

How to check your user permissions.

1. Go to the Resource group where your KDB.AI instance is deployed and select Access Control (IAM).
2. In the Check access tab, click View my Access, to view the level of access assigned to you.
3. To Add a new role, select Add from the top panel.

Steps to upgrade

1. Go to the Resource group where KDB.AI is deployed and access the Key vault.
2. On the left panel, go to Secrets. Make sure you have a role that allows you to view, edit, and create secrets.
3. Select crImageVersion from the list.
4. Click on New Version from the top panel.

5. To upgrade your current version, you have to complete the following fields:

   Field name	Field value
   Upload options:	Manual
   Secret value:	input the version you want to upgrade to (for example 1.0.1)
   Content type (optional):	text/plain
   Enabled:	YES (if you would like to automatically update the running version)

   When completed, click on Create.

6. Now you need to restart the KDB.AI instance. To do so, go back to the Resource group and access the KDB.AI service.

7. Click on the Launch studio button.
8. From the left panel, access Compute.
9. Tick your KDB.AI instance and press Restart.
10. To verify if the upgrade is successful, follow the instructions below:

How to check your current version of KDB.AI.

How to check version

1. Go to the Resource group where KDB.AI is deployed and access the ml-kdbai service.
2. Click on the Launch studio button.
3. Access Notebooks from the left panel.
4. Go to the Logs folder and click on the stdout file to open it.
5. Search for kdbai-db: (the set of digits next to it shows the KDB.AI version that's currently deployed).