# Aporia Docs

Data Science and ML teams rely on Aporia to **visualize** their models in production, as well as **detect and resolve** data drift, model performance degradation, and data integrity issues. 

Aporia offers quick and simple deployment and can monitor billions of predictions with low cloud costs. We understand that use cases vary and each model is unique, that’s why we’ve cemented **customization** at our core, to allow our users to tailor their dashboards, monitors, metrics, and data segments to their needs.

<figure><img src="https://691195388-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FMGlr0qI6TBrhv4rIjaKP%2Fuploads%2FzAQ9QLykq5UdqEb5DFqY%2F1_GPXT50Q_GL_wn-tyBDWvFw.png?alt=media&#x26;token=da68e117-b253-48d1-bbff-39006f770311" alt=""><figcaption></figcaption></figure>

## Monitor your models in 3 easy steps&#x20;

<table data-view="cards"><thead><tr><th></th><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Learn</strong></td><td>Learn about data drift, measuring model performance in production across various data segments, and other ML monitoring concepts.</td><td></td><td><a href="core-concepts/why-monitor-ml-models">why-monitor-ml-models</a></td></tr><tr><td><strong>Connect</strong></td><td>Connect to an existing database where you already store the predictions of your models.</td><td></td><td><a href="data-sources">data-sources</a></td></tr><tr><td><strong>Monitor</strong></td><td>Build a dashboard to visualize your model in production and create alerts to notify you when something bad happens.</td><td></td><td><a href="monitors-and-alerts">monitors-and-alerts</a></td></tr></tbody></table>