# Configuring a custom solution in Amazon Personalize
<a name="customizing-solution-config"></a>

After you finish importing data, you are ready to create a solution. A *solution* refers to the combination of an Amazon Personalize recipe, customized training parameters, and one or more solution versions. A *solution version* refers to a trained machine learning model.

By default, all new solutions use automatic training to create a new solution version every 7 days. Automatic training occurs only if you imported bulk or real-time interaction data since the last training. This includes item interactions or, for solutions that use the Next-Best-Action recipe, action interactions data. Automatic training continues until you delete the solution. For more information, see [Configuring automatic training](solution-config-auto-training.md). 

If you have an existing solution, you can use the Amazon Personalize console to clone the solution. When you clone a solution, you can use the configuration of the existing solution as a starting point, such as the recipe and hyperparameters, and make any changes. For more information, see [Cloning a solution (console)](cloning-solution.md). 

You can create and configure a solution by using the console, AWS Command Line Interface (AWS CLI), or AWS SDKs. After you create a solution, you can view its configuration details on the solution's details page of the Amazon Personalize console, or with the [DescribeSolution](API_DescribeSolution.md) operation.

By default, all new solutions use automatic training. With automatic training, you incur training costs while your solution is active. To avoid unnecessary costs, when you are finished you can [update the solution](updating-solution.md) to turn off automatic training. For information about training costs, see [Amazon Personalize pricing](https://aws.amazon.com/personalize/pricing/).

**Topics**
+ [Creating a solution](create-solution.md)
+ [Configuring automatic training](solution-config-auto-training.md)
+ [Configuring columns used when training](custom-config-columns.md)
+ [Optimizing a solution for an additional objective](optimizing-solution-for-objective.md)
+ [Optimizing a solution with events configuration](optimizing-solution-events-config.md)
+ [Hyperparameters and HPO](customizing-solution-config-hpo.md)
+ [Choosing the item interaction data used for training](event-values-types.md)
+ [Cloning a solution (console)](cloning-solution.md)