Model deployment

In this phase you first package your Decision Optimization model with master data (optional) ready for deployment as a tar.gz or zip file.

This zip file includes the following optional files:
  1. Your model files
  2. Settings (see Solve parameters for more information)
  3. Master data
When registering your model in WML, you target a particular Decision Optimization runtime version:
  • do_12.9 runtime currently based on CPLEX V.12.9

the model type:

  • opl (do-opl_12.9)
  • cplex (do-cplex_12.9)
  • cpo (do-cpo_12.9)
  • docplex (do-docplex_12.9) using Python V.3.6

and upload the associated model archive if needed.

This Watson Machine Learning model can then be used in one or multiple deployments.

In summary, to deploy your model:

  1. Choose your desired Decision Optimization runtime.
  2. Package your Decision Optimization model with master data (optional) ready for deployment as a tar.gz or zip file.
  3. Upload your model archive (tar.gz or zip file) on Watson Machine Learning. See Model execution for information about input file types. You obtain a model-URL.
  4. Deploy your model using the model-URL and obtain a deployment-id.
  5. Monitor the deployment using the deployment-id. Deployment states can be: initializing, updating, ready, or failed.