.. _real_world_fl:

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Real-World Federated Learning
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This section shows how to use NVIDIA FLARE to deploy and operate an FL system.
A reference application will be used here to show provisioning and basic operation
of the system through the FLARE console and FLARE API. To deploy on the cloud, see :ref:`cloud_deployment`.

For instructions on how to set up the :ref:`nvflare_dashboard_ui` to
help gather information to provision a project and distribute startup kits, see :ref:`dashboard_api`.

For more details on what you can do with apps with custom components and
the flexibility that the Controller and Worker APIs bring, see the :ref:`programming_guide`.

For setting up authorization policies, see :ref:`federated authorization <federated_authorization>`.

You can also see some :github_nvflare_link:`example applications <examples>` integrating with
`Clara Train <https://docs.nvidia.com/clara/clara-train-sdk/>`_ and
`MONAI <https://github.com/Project-MONAI/tutorials/tree/master/federated_learning/nvflare>`_
to see the capabilities of the system and how it can be operated.

.. toctree::
   :maxdepth: 1

   real_world_fl/overview
   real_world_fl/operation
   real_world_fl/application
   real_world_fl/job
   real_world_fl/workspace
   real_world_fl/cloud_deployment
   real_world_fl/containerized_deployment
   real_world_fl/kubernetes
   real_world_fl/notes_on_large_models
   user_guide/security/identity_security