# Deploying a  Decision Optimization model by using the user interface #

You can save a model for deployment in the  Decision Optimization experiment UI and promote it to your  Watson Machine Learning deployment space\.

## Procedure ##

To save your model for deployment:

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1.  In the  Decision Optimization experiment UI, either from the  Scenario or from the  Overview pane, click the menu icon ![Scenario menu icon](https://dataplatform.cloud.ibm.com/docs/content/DO/WML_Deployment/images/scenariomenu.jpg) for the scenario that you want to deploy, and select **Save for deployment**
2.  Specify a name for your model and add a description, if needed, then click **Next**\.
    
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    1.  Review the  Input and  Output schema and select the tables you want to include in the schema.
    2.  Review the  Run parameters and add, modify or delete any parameters as necessary.
    3.  Review the  Environment and  Model files that are listed in the  Review and save window. 
    4.  Click  Save.
    
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    The model is then available in the **Models** section of your project.

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To promote your model to your deployment space:

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3.  View your model in the  Models section of your project\.You can see a summary with input and output schema\. Click **Promote to deployment space**\.
4.  In the  Promote to space window that opens, check that the  Target space field displays the name of your deployment space and click **Promote**\.
5.  Click the link **deployment space** in the message that you receive that confirms successful promotion\. Your promoted model is displayed in the  Assets tab of your **Deployment space**\. The information pane shows you the Type, Software specification, description and any defined tags such as the Python version used\.

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To create a new deployment:

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6.  From the **Assets tab** of your deployment space, open your model and click **New Deployment**\.
7.  In the  Create a deployment window that opens, specify a name for your deployment and select a **Hardware specification**\.Click **Create** to create the deployment\. Your deployment window opens from which you can later create jobs\.

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## Creating and running  Decision Optimization jobs ##

You can create and run jobs to your deployed model\.

### Procedure ###

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1.  Return to your deployment space by using the navigation path and (if the data pane isn't already open) click the  data icon to open the data pane\. Upload your input data tables, and solution and kpi output tables here\. (You must have output tables defined in your model to be able to see the solution and kpi values\.)
2.  Open your deployment model, by selecting it in the Deployments tab of your deployment space and click **New job**\.
3.  Define the details of your job by entering a name, and an optional description for your job and click **Next**\.
4.  Configure your job by selecting a hardware specification and **Next**\.You can choose to schedule you job here, or leave the default schedule option off and click **Next**\. You can also optionally choose to turn on notifications or click  Next\.
5.  Choose the data that you want to use in your job by clicking Select the source for each of your input and output tables\. Click **Next**\.
6.  You can now review and create your model by clicking **Create**\.When you receive a successful job creation message, you can then view it by opening it from your deployment space\. There you can see the run status of your job\.
7.  Open the run for your job\.Your job log opens and you can also view and copy the payload information\.

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