Managing the deployment space

The current IBM's terraform module is in development and some features are still missing. So we will use a Python script to manage the IBM Watson's deployment space, including create, delete and get the space_id, which will be very important as it is used in other scripts.

Authentication

The following code is used to authenticate to the provider, note that it uses the same environment variable as terraform.

import os
import sys
from pprint import pprint
import json
from ibm_watson_machine_learning import APIClient

TERRAFORM_OUTPUT = '.terraform/terraform.tfstate'

def authentication():

    if os.getenv("IBMCLOUD_API_KEY"):

        wml_credentials = {
            "url": "https://us-south.ml.cloud.ibm.com",
            "apikey": os.environ.get("IBMCLOUD_API_KEY"),
        }
        client = APIClient(wml_credentials)  # Connect to IBM cloud

        return client

    raise Exception("API_KEY environment variable not defined")

Terraform output

To create a deployment space, we need to get some metadata from the resources created by the terraform script. Here we use the output defined on terraform.

def terraform_output(terraform_path=TERRAFORM_OUTPUT):

    output = dict(json.load(open(terraform_path)))['outputs']

    cos_crn = output["cos_crn"]["value"]
    wml_crn = output["wml_crn"]["value"]["crn"]
    wml_name = output["wml_crn"]["value"]["resource_name"]

    state = {
        "cos_crn" : cos_crn,
        "wml_name": wml_name,
        "wml_crn" : wml_crn
    }
    return state

Creating a space

Now with the metadata in hands, we can finally create a deployment space.

def create_deployment_space(
    client, cos_crn, wml_name, wml_crn, space_name="default", description=""
):

    ## Project info
    metadata = {
        client.spaces.ConfigurationMetaNames.NAME: space_name,  
        client.spaces.ConfigurationMetaNames.DESCRIPTION: description,
        client.spaces.ConfigurationMetaNames.STORAGE: {
            "type": "bmcos_object_storage",
            "resource_crn": cos_crn,
        },

        ## Project compute instance (WML)
        client.spaces.ConfigurationMetaNames.COMPUTE: { 
            "name": wml_name,
            "crn": wml_crn,
        },
    }

    space_details = client.spaces.store(meta_props=metadata)  # Create a space
    return space_details

Get the space_id

With the space created, now we have the space_id, the following function is used to retrieve it. This info will be used on other scripts that will be shown on next pages.

def update_deployment_space(client, new_name, space_id):

    metadata = {client.spaces.ConfigurationMetaNames.NAME: new_name}

    space_details = client.spaces.update(space_id, changes=metadata)
    return space_details

Note

To see the complete script click here