* under the assumption that for long-running instances, observed
   * contention levels will recur, so the cells will eventually be
   * needed again; and for short-lived ones, it does not matter.
   */

  /**
   * Padded variant of AtomicLong supporting only raw accesses plus CAS. The value field is placed
   * between pads, hoping that the JVM doesn't reorder them.
   *

     */
    FAILED,
  }

  /**
   * A listener for the various state changes that a {@link Service} goes through in its lifecycle.
   *
   * <p>All methods are no-ops by default, implementors should override the ones they care about.
   *
   * @author Luke Sandberg
   * @since 15.0 (present as an interface in 13.0)
   */
  abstract class Listener {
    /** Constructor for use by subclasses. */
    public Listener() {}

`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are
tenant isolation, resource allocation, model sharing and hardware attacks.

### Tenant isolation

So we are going to use that same knowledge to document how the *external API* should look like... by creating the *path operation(s)* that the external API should implement (the ones your API will call).

/// tip

When writing the code to document a callback, it might be useful to imagine that you are that *external developer*. And that you are currently implementing the *external API*, not *your API*.

// isHostIP - helper for validating if the provided arg is an ip address.
func isHostIP(ipAddress string) bool {
	host, _, err := net.SplitHostPort(ipAddress)
	if err != nil {
		host = ipAddress
	}
	// Strip off IPv6 zone information.
	if i := strings.Index(host, "%"); i > -1 {
		host = host[:i]
	}
	return net.ParseIP(host) != nil
}

// extractHostPort - extracts host/port from many address formats

* el path `/`
* usando una <abbr title="un método HTTP GET"><code>get</code> operation</abbr>

/// info | Información sobre `@decorator`

Esa sintaxis `@algo` en Python se llama un "decorador".

Lo pones encima de una función. Como un bonito sombrero decorativo (supongo que de ahí viene el término).

Un "decorador" toma la función de abajo y hace algo con ella.

* Response payloads.

You would also have **inline errors** for everything.

And whenever you update the backend code, and **regenerate** the frontend, it would have any new *path operations* available as methods, the old ones removed, and any other change would be reflected on the generated code. 🤓

I'll tell you a bit more about these **concepts** here, and that would hopefully give you the **intuition** you would need to decide how to deploy your API in very different environments, possibly even in **future** ones that don't exist yet.

By considering these concepts, you will be able to **evaluate and design** the best way to deploy **your own APIs**.

        // spec says that we may repeat the request without modifications. Modern browsers also
        // repeat the request (even non-idempotent ones.)
        if (!client.retryOnConnectionFailure) {
          // The application layer has directed us not to retry the request.
          return null
        }

        val requestBody = userResponse.request.body

Para ver la diferencia, imagina la siguiente historia sobre hamburguesas:

### Hamburguesas Concurrentes

Vas con tu crush a conseguir comida rápida, te pones en fila mientras el cajero toma los pedidos de las personas frente a ti. 😍

<img src="/img/async/concurrent-burgers/concurrent-burgers-01.png" class="illustration">