*
     * @param cfg the configuration containing machine ID
     */
    public AvSingleHost(final Configuration cfg) {
        this(new byte[8], cfg.getMachineId());
    }

    /**
     * Constructs an AvSingleHost with custom data and machine ID
     *
     * @param customData custom data for the single host (8 bytes)
     * @param machineId the machine identifier (32 bytes)
     */

     * Should correctly encode custom data and machine ID.
     */
    @Test
    void testAvSingleHostCustomDataMachineIdConstructor() {
        byte[] customData = new byte[8];
        customData[0] = 0x01;
        customData[7] = 0x08;

        byte[] machineId = new byte[32];
        machineId[0] = 0x10;
        machineId[31] = 0x20;

## Server Machine and Server Program { #server-machine-and-server-program }

There's a small detail about names to keep in mind. 💡

The word "**server**" is commonly used to refer to both the remote/cloud computer (the physical or virtual machine) and also the program that is running on that machine (e.g. Uvicorn).

## Use Case { #use-case }

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

* **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande planilha com números e em multiplicar todos eles juntos e ao mesmo tempo.

## 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**.

For a **web API**, it normally involves putting it in a **remote machine**, with a **server program** that provides good performance, stability, etc, so that your **users** can **access** the application efficiently and without interruptions or problems.

### Server Memory { #server-memory }

For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.

And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨

        assertNotNull(defaultConfig.getRandom(), "Random should not be null");
        assertNotNull(defaultConfig.getLocalTimezone(), "Local timezone should not be null");
        assertNotNull(defaultConfig.getMachineId(), "Machine ID should not be null");
    }

    @Test
    @DisplayName("Test network configuration getters")
    void testNetworkConfigurationGetters() {
        assertEquals(0, config.getLocalPort());

 * Windows command prompt you can see
 * what names a host registers with the nbtstat command.
 *
 *  * <blockquote>
 *
 * <pre>
 * C:\&gt;nbtstat -a 192.168.1.15
 *
 *        NetBIOS Remote Machine Name Table
 *
 *    Name               Type         Status
 * ---------------------------------------------
 * JMORRIS2        &lt;00&gt;  UNIQUE      Registered
 * BILLING-NY      &lt;00&gt;  GROUP       Registered

-postgres-and-aws-app-runner-at-any-scale title: Deploy a Serverless FastAPI App with Neon Postgres and AWS App Runner at any scale - author: Kurtis Pykes - NVIDIA link: https://developer.nvidia.com/blog/building-a-machine-learning-microservice-with-fastapi/ title: Building a Machine Learning Microservice with FastAPI - author: Ravgeet Dhillon - Twilio link: https://www.twilio.com/en-us/blog/booking-appointments-twilio-notion-fastapi title: Booking Appointments with Twilio, Notion, and FastAPI -...