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Version: 10.3

Deploy Python environment

To set up a custom Python environment in a cluster and enable running a model in it, follow the instructions below.

Set up environment​

To set up a custom Python environment in a cluster, act as follows:

  1. Prepare Python for your cluster OS (Centos OS, by default) with all dependencies (libraries).

    Alternatively, you can pack the libraries as wheels and add them to your Python model. For detailed instructions, refer to Build custom Python model.

  2. Install Python.

    When a cluster runs a new model, it can choose any node based on the resouce allocation strategy. Therefore, install Python on each node, except for Master. The recommended installation path is as follows: /opt/workfusion/python/.

Enable model running with custom environment​

To enable running a model in the configured custom Python environment, proceed as follows:

  1. Modify worker-*-python.yml. The worker-{profile}.yml file (for Python, worker-execution-python.yml) configures Worker run parameters.

  2. Deploy the model to your Control Tower (CT) instance:

Now, you can run the deployed model the same way as any other one on CT.