This add-on has been deprecated

Installation

Important Note:

The seeq-azureml add-on is meant to be used for proof-of-concept models only. There are four significant caveats that users should be aware of when using this add-on:

  1. A new Azure app registration must be set up to provide the identity to Seeq via OIDC (Open ID Connect).
  2. The Azure app registration needs contributor access to the AzureML Studio workspace.
  3. A secret needs to be generated and configured in an ini file as per the instructions on the Seeq Add-on Installation section of the documentation.
  4. This add-on has very limited capability for scalability to multiple assets.

The backend of seeq-azureml requires Python >3.7 or later.

Dependencies

See requirements.txt file for a list of dependencies and versions. Additionally, you will need to install the seeq module with the appropriate version that matches your Seeq server. For more information on the seeq module see seeq at pypi

User Installation Requirements (Seeq Data Lab)

If you want to install seeq-azureml as a Seeq Add-on Tool, you will need:

  • Seeq Data Lab (> R50.5.0, >R51.1.0, >R52.1.0, or >=R53)

  • seeq module whose version matches the Seeq server version, and the version of SPy >= 182.25

  • Seeq server admin access

  • Enable Add-on Tools in the Seeq server

User Installation (Seeq Data Lab)

The latest build of the project can be found here as a wheel file. The file is published as a courtesy and does not imply any guarantee or obligation for support from the publisher.

Pre-requisites

Before installing the seeq-azureml Seeq Add-on, you will have to create an Azure application and service principal. Follow the steps in here to create your application, and choose Option 2 for the Authentication method.

Seeq Add-on Installation

Once the Azure application and service principal have been created. Follow these steps to install the Seeq Add-on:

  1. Create a new Seeq Data Lab project and open the Terminal window

  2. Run pip install seeq-azureml

  3. Run python -m seeq.addons.azureml [--users <users_list> --groups <groups_list>]

  4. Create an aml_config.ini file in the ~/.seeq folder of the Seeq Data Lab Project with the information required to connect to the Azure ML services. The following steps summarized how to create the aml_config.ini file in the correct Seeq Data Lab location and where to get the values required for the configuration.

    1. Download the aml_config.ini configuration file from here

    2. Upload the file to the Seeq Data Lab project using the Upload button located in the top-right corner of the home page of the project.

    3. From the Seeq Data Lab project home page, open the uploaded file and modify the fields appropriately:

      1. The SUBSCRIPTION_ID, RESOURCE_GROUP, and WORKSPACE_NAME can be obtained by logging into the Azure portal and clicking on the Machine Learning service . Once in the Machine Learning service, click on the desired WORKSPACE_NAME from the list. The Overview tab will show a list of Essentials from which you can take the values for SUBSCRIPTION_ID and RESOURCE_GROUP.

      2. The TENANT_ID, APP_ID, and APP_SECRET are obtained when creating the Azure application in the section Get tenant and app ID values for signing in , Option 2 .

      3. Save the aml_config.ini file.

    4. Back to the Terminal window from Steps 1 and 2, run the command mv aml_config.ini .seeq/ to move the aml_config.ini file to the appropriate folder.

Note: If Step 3 gives an error make sure that the seeq module is >= a.b.c.182.25 where a.b.c are explained here