Deploying Java models for Decision Optimization

You can deploy Decision Optimization Java models by using the watsonx.ai Runtime REST API.

With the Java worker API, you can create optimization models with OPL, CPLEX, and CP Optimizer Java APIs. Therefore, you can easily create your models locally, package them and deploy them with watsonx.ai Runtime by using the boilerplate that is provided in the public Java worker GitHub.

The Decision Optimization Java worker GitHub contains a boilerplate with everything that you need to run, deploy, and verify your Java models with the watsonx.ai Runtime, including an example. You can use the code in this repository to package your Decision Optimization Java model in a .jar file that can be used as a Machine learning model. For more information about Java worker parameters, see the Java documentation.

You can build your Decision Optimization models in Java or you can use Java worker to package CPLEX, CPO, and OPL models.