But still, the final experience is not the best. 😞

---

This would be the parallel equivalent story for burgers. 🍔

For a more "real life" example of this, imagine a bank.

Up to recently, most of the banks had multiple cashiers 👨‍💼👨‍💼👨‍💼👨‍💼 and a big line 🕙🕙🕙🕙🕙🕙🕙🕙.

All of the cashiers doing all the work with one client after the other 👨‍💼⏯.

        if (logger.isDebugEnabled()) {
            logger.debug("Deleted {} stale documents.", numOfDeleted);
        }
        return numOfDeleted;
    }

    /**
     * Refreshes the specified index to make recent changes visible for search.
     * This operation ensures that all pending writes are persisted and searchable.
     *
     * @param searchEngineClient the search engine client to use for refresh

In this example we are using the OAuth2 "password" flow.

This is appropriate when we are logging in to our own application, probably with our own frontend.

Because we can trust it to receive the `username` and `password`, as we control it.

// DeleteBucketOptions provides options for DeleteBucket calls.
type DeleteBucketOptions struct {
	NoLock     bool             // does not lock the delete bucket call if set to 'true'
	NoRecreate bool             // do not recreate bucket on delete failures
	Force      bool             // Force deletion
	SRDeleteOp SRBucketDeleteOp // only when site replication is enabled
}

// BucketOptions provides options for ListBuckets and GetBucketInfo call.

   * {@code Future} is cancelled, it will attempt to cancel the other two, and if either of the
   * other two is cancelled, the returned {@code Future} will receive a callback in which it will
   * attempt to cancel itself.
   *
   * @param input The future to transform
   * @param function A function to transform the result of the input future to the result of the

          startupTimers.put(service, Stopwatch.createStarted());
        }
      } finally {
        monitor.leave();
      }
    }

    /**
     * Marks the {@link State} as ready to receive transitions. Returns true if no transitions have
     * been observed yet.
     */
    void markReady() {
      monitor.enter();
      try {
        if (!transitioned) {

          startupTimers.put(service, Stopwatch.createStarted());
        }
      } finally {
        monitor.leave();
      }
    }

    /**
     * Marks the {@link State} as ready to receive transitions. Returns true if no transitions have
     * been observed yet.
     */
    void markReady() {
      monitor.enter();
      try {
        if (!transitioned) {

                                doSend0(req);
                            } while (req.hasMoreElements() && req.nextElement() != null);

                            /*
                             * Receive multiple fragments
                             */

                            long timeout = RESPONSE_TIMEOUT;
                            resp.expiration = System.currentTimeMillis() + timeout;

Durch die Berücksichtigung dieser Konzepte können Sie die beste Variante des Deployments **Ihrer eigenen APIs** **evaluieren und konzipieren**.

In den nächsten Kapiteln werde ich Ihnen mehr **konkrete Rezepte** für das Deployment von FastAPI-Anwendungen geben.

Aber schauen wir uns zunächst einmal diese grundlegenden **konzeptionellen Ideen** an. Diese Konzepte gelten auch für jede andere Art von Web-API. 💡

Those worker processes would be the ones running your application, they would perform the main computations to receive a **request** and return a **response**, and they would load anything you put in variables in RAM.

<img src="/img/deployment/concepts/process-ram.drawio.svg">