Your server(s) is (are) a **resource**, you can consume or **utilize**, with your programs, the computation time on the CPUs, and the RAM memory available.

How much of the system resources do you want to be consuming/utilizing? It might be easy to think "not much", but in reality, you will probably want to consume **as much as possible without crashing**.

This way, containers consume **little resources**, an amount comparable to running the processes directly (a virtual machine would consume much more).

Containers also have their own **isolated** running processes (commonly just one process), file system, and network, simplifying deployment, security, development, etc.

## What is a Container Image

[containernetworking sample plugin](https://github.com/containernetworking/plugins/tree/main/plugins/sample)

The details for the deployment & installation of this plugin were pretty much lifted directly from the
[Calico CNI plugin](https://github.com/projectcalico/cni-plugin).

Specifically:

### Create the `Settings` object

Import `BaseSettings` from Pydantic and create a sub-class, very much like with a Pydantic model.

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

    return nextTask
  }

  private interface SerialTask {
    /** Returns true if this task is ready to start. */
    fun isReady() = true

    /** Do this task's work, and then start another, such as by calling [startNextTask]. */
    fun start()
  }

  private object TestThreadSerialTask : SerialTask {
    override fun start() = error("unexpected call")
  }

  inner class RunnableSerialTask(

      use, offer to sell, sell, import, and otherwise transfer the Work,
      where such license applies only to those patent claims licensable
      by such Contributor that are necessarily infringed by their
      Contribution(s) alone or by combination of their Contribution(s)
      with the Work to which such Contribution(s) was submitted. If You
      institute patent litigation against any entity (including a

production Python API, I would highly recommend **FastAPI**. It is **beautifully designed**, **simple to use** and **highly scalable**, it has become a **key component** in our API first development strategy and is driving many automations and services such as our Virtual TAC Engineer._"

<div style="text-align: right; margin-right: 10%;">Deon Pillsbury - <strong>Cisco</strong> <a href="https://www.linkedin.com/posts/deonpillsbury_cisco-cx-python-activity-6963242628536487936-trAp/" target="...

      use, offer to sell, sell, import, and otherwise transfer the Work,
      where such license applies only to those patent claims licensable
      by such Contributor that are necessarily infringed by their
      Contribution(s) alone or by combination of their Contribution(s)
      with the Work to which such Contribution(s) was submitted. If You
      institute patent litigation against any entity (including a

production Python API, I would highly recommend **FastAPI**. It is **beautifully designed**, **simple to use** and **highly scalable**, it has become a **key component** in our API first development strategy and is driving many automations and services such as our Virtual TAC Engineer._"

<div style="text-align: right; margin-right: 10%;">Deon Pillsbury - <strong>Cisco</strong> <a href="https://www.linkedin.com/posts/deonpillsbury_cisco-cx-python-activity-6963242628536487936-trAp/" target="...

* Muchas características extra (gracias a Starlette) como:
    * **WebSockets**
    * **GraphQL**
    * pruebas extremadamente fáciles con HTTPX y `pytest`
    * **CORS**
    * **Cookie Sessions**
    * ...y mucho más.

## Rendimiento