# Deployment Once a modeling pipeline is ready for deployment, it is easy to deploy mlpack applications to a wide variety of settings due to its simple header-only nature. See also the [examples repository](https://github.com/mlpack/examples/), which contains a number of fully-working deployable example applications. The pages below provide guidance for how to deploy mlpack to a variety of relatively simple environments. * [***Compile an mlpack program***](compile.md): compile a standalone C++ program that uses mlpack. * [***Cross-compile to a Raspberry Pi***](../embedded/crosscompile_armv7.md): cross-compile an mlpack C++ application to an embedded or low-resource device. - See also the [cross-compilation setup page](../embedded/supported_boards.md). * [***Deploying mlpack on Windows***](deploy_windows.md): build a Windows application that uses mlpack. * [***Deploying mlpack to a Docker container***](deploy_docker.md): package an mlpack application inside of a lightweight Docker container for local usage or deployment in a cloud environment.