In the next chapter about [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank} I'll tell some strategies you could use to handle the other **deployment concepts**.

I'll also show you the **official Docker image** that includes **Gunicorn with Uvicorn workers** and some default configurations that can be useful for simple cases.

A wildcard rule was added with a wildcard that is not in leftmost position! We'll need to change the ${PublicSuffixDatabase::class.java.name} to handle this."""
    }
    check(rule.indexOf(WILDCARD_CHAR, 1) == -1) {
      """Wildcard Assertion Failure: '$rule'
A wildcard rule was added with multiple wildcards! We'll need to change ${PublicSuffixDatabase::class.java.name} to handle this."""
    }

* Memory
* Previous steps before starting

We'll see how they would affect **deployments**.

In the end, the ultimate objective is to be able to **serve your API clients** in a way that is **secure**, to **avoid disruptions**, and to use the **compute resources** (for example remote servers/virtual machines) as efficiently as possible. 🚀

	}

	return nil
}

type logLevelState struct {
	client         *ControlzClient
	outputLogLevel string
}

func (ll *logLevelState) run(_ io.Writer) error {
	scopeInfos, err := newScopeInfosFromScopeLevelPairs(ll.outputLogLevel)
	if err != nil {
		return err
	}
	err = ll.client.PutScopes(scopeInfos)
	if err != nil {
		return err
	}
	return nil
}

type stackTraceLevelState struct {

* Also don't worry about style rules, there are already automatized tools checking that.

And if there's any other style or consistency need, I'll ask directly for that, or I'll add commits on top with the needed changes.

### Check the code

* Check and read the code, see if it makes sense, **run it locally** and see if it actually solves the problem.

That's what we'll solve, let's load the model before the requests are handled, but only right before the application starts receiving requests, not while  the code is being loaded.

## Lifespan

You can define this *startup* and *shutdown* logic using the `lifespan` parameter of the `FastAPI` app, and a "context manager" (I'll show you what that is in a second).

   * the internal list.
   */
  @JvmStatic
  fun fragmentBuffer(buffer: Buffer): Buffer {
    // Write each byte into a new buffer, then clone it so that the segments are shared.
    // Shared segments cannot be compacted so we'll get a long chain of short segments.
    val result = Buffer()
    while (!buffer.exhausted()) {
      val box = Buffer()
      box.write(buffer, 1)
      result.write(box.copy(), 1)
    }
    return result
  }

                    Thread.sleep(10);
                } catch (InterruptedException e) {
                    // ignore
                }
                metadataFile.delete(); // if this fails, forget about it, we'll try to overwrite it anyway so no need
                // to delete on exit
            }
        } else if (metadataFile.exists()) {
            try (InputStream input = Files.newInputStream(metadataFile.toPath())) {

But it's not possible to have a running container without **at least one running process**. If the main process stops, the container stops.

## Build a Docker Image for FastAPI

Okay, let's build something now! 🚀

I'll show you how to build a **Docker image** for FastAPI **from scratch**, based on the **official Python** image.

This is what you would want to do in **most cases**, for example:

* Using **Kubernetes** or similar tools

					resp, err = setupEnvoyLogConfig(kubeClient, "", podName, podNamespace)
				} else {
					if ll, ok := destLoggerLevels[defaultLoggerName]; ok {
						// update levels of all loggers first
						resp, err = setupEnvoyLogConfig(kubeClient, defaultLoggerName+"="+levelToString[ll], podName, podNamespace)
					}
					for lg, ll := range destLoggerLevels {
						if lg == defaultLoggerName {
							continue
						}