Connecting Watson Machine Learning Accelerator to Watson Machine Learning

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After deploying both the Watson Machine Learning service and the Watson Machine Learning Accelerator service, you can connect the two services to share training resources and use Watson Machine Learning resources with Watson Machine Learning Accelerator.

Procedure

  1. In WML, run the updateWMLClusterdetails.sh command line utility which allows WML to locate and use a WML Accelerator instance. Use ibm-wml-cpd-4.7.0.tgz located in WML CASE packages.
    1. Obtain and extract the WML files from the CASE package (ibm-wml-cpd-4.7.0.tgz). 
      tar -zxvf ibm-wml-cpd-4.7.0.tgz
    2. Navigate to the ibm-wml-cpd/inventory/wmlOperatorSetup/files directory.
    3. Export the Watson Machine Learning namespace. 
      export NAMESPACE=wml-namespace
      where wml-namespace is the name of the Watson Machine Learning namespace.
    4. Run the updateWMLClusterdetails.sh script. 
      • sh updateWMLClusterdetails.sh wmla-ingress.wmla-namespace.svc port wml-ig wml-ig-edt internal-service-name.cpd-namespace.svc:port
        where:
        • port is the port number of the wmla-ingress service. To obtain the port number, run: 
          oc get svc/wmla-ingress -n cpd-namespace
          For example: 
          NAME           TYPE        ...   PORT(S)
wmla-ingress   ClusterIP   ...   30746/TCP
        • internal-service-name:port is the internal service name and the port number. To the internal service name and port number, run: 
          oc get svc/internal-nginx-svc -n cpd-namespace
          For example:
          NAME                 TYPE        ...   PORT(S)
internal-nginx-svc   ClusterIP   ...   12443/TCP
        For example: 
        sh updateWMLClusterdetails.sh wmla-ingress.wmla.svc 30746 wml-ig wml-ig-edt internal-nginx-svc.cpd-instance.svc:12443
  2. Verify that the connection was successful by checking that the Deep Learning experiment option is available.

What to do next