# Deployment { #deployment }

Deploying a **FastAPI** application is relatively easy.

## What Does Deployment Mean { #what-does-deployment-mean }

To **deploy** an application means to perform the necessary steps to make it **available to the users**.

stapi-you-should-try-7c0ac7eebb3e title: 5 Advanced Features of FastAPI You Should Try - author: Kaustubh Gupta author_link: https://medium.com/@kaustubhgupta1828/ link: https://www.analyticsvidhya.com/blog/2021/06/deploying-ml-models-as-api-using-fastapi-and-heroku/ title: Deploying ML Models as API Using FastAPI and Heroku - link: https://jarmos.netlify.app/posts/using-github-actions-to-deploy-a-fastapi-project-to-heroku/ title: Using GitHub Actions to Deploy a FastAPI Project to Heroku author_link:...

See our web documentation on [Deploying MinIO in Standalone Mode](Deploy Standalone MinIO in a Container) for a more structured tutorial on deploying MinIO in a container.

## Prerequisites

Docker installed on your machine. Download the relevant installer from [here](https://www.docker.com/community-edition#/download).

Standalone MinIO servers are best suited for early development and evaluation. Certain features such as versioning, object locking, and bucket replication
require distributed deploying MinIO with Erasure Coding. For extended development and production, deploy MinIO with Erasure Coding enabled - specifically,

Up to this point, with all the tutorials in the docs, you have probably been running a **server program**, for example, using the `fastapi` command, that runs Uvicorn, running a **single process**.

When deploying applications you will probably want to have some **replication of processes** to take advantage of **multiple cores** and to be able to handle more requests.

# FastAPI in Containers - Docker { #fastapi-in-containers-docker }

When deploying FastAPI applications a common approach is to build a **Linux container image**. It's normally done using <a href="https://www.docker.com/" class="external-link" target="_blank">**Docker**</a>. You can then deploy that container image in one of a few possible ways.

Using Linux containers has several advantages including **security**, **replicability**, **simplicity**, and others.

/// tip

     * When set to <code>false</code>, only the consumer POM will be deployed, and the build POM
     * will be excluded from deployment. This is useful to avoid deploying internal build information
     * that is not needed by consumers of the artifact.
     * <br/>
     * Default: <code>"true"</code>.
     *
     * @since 4.1.0
     */

# Deployments Concepts { #deployments-concepts }

When deploying a **FastAPI** application, or actually, any type of web API, there are several concepts that you probably care about, and using them you can find the **most appropriate** way to **deploy your application**.

Some of the important concepts are:

* Security - HTTPS
* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

          <association>
            <type>DeploymentRepository</type>
          </association>
        </field>
        <field>
          <name>site</name>
          <description>Information needed for deploying the web site of the project.</description>
          <version>4.0.0+</version>
          <association>
            <type>Site</type>
          </association>
        </field>
        <field>

* Add article [Deploying a scikit-learn model with ONNX and FastAPI](https://medium.com/@nico.axtmann95/deploying-a-scikit-learn-model-with-onnx-und-fastapi-1af398268915) by [Nico Axtmann](https://www.linkedin.com/in/nico-axtmann). PR [#438](https://github.com/tiangolo/fastapi/pull/438) by [@naxty](https://github.com/naxty)....