Sehen wir uns das alles anhand eines Beispiels an.

Stellen Sie sich vor, Sie entwickeln eine Anwendung, mit der Sie Rechnungen erstellen können.

Diese Rechnungen haben eine `id`, einen optionalen `title`, einen `customer` (Kunde) und ein `total` (Gesamtsumme).

Der Benutzer Ihrer API (ein externer Entwickler) erstellt mit einem POST-Request eine Rechnung in Ihrer API.

Dann wird Ihre API (beispielsweise):

policy/control/telemetry - so testing/staging of new settings and versions can be performed
by a different role than the prod version.

The intended users of this repo are users running Istio in production who want to select, tune
and understand each binary that gets deployed, and select which combination to use.

Note: each component can be installed in parallel with an existing Istio 1.0 or 1.1 installation in

### Short

It has sensible **defaults** for everything, with optional configurations everywhere. All the parameters can be fine-tuned to do what you need and to define the API you need.

But by default, it all **"just works"**.

### Validation

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).

This offered performance benefits that were too large to leave on the table, as well as opportunities to tune to our specific needs.

## Configuration protocol

Ztunnel, of course, needs to be dynamically configured in order to make decisions on how it should handle traffic.

    Die Klasse `FastAPI` selbst erbt direkt von der Klasse `Starlette`.

    Alles, was Sie also mit Starlette machen können, können Sie direkt mit **FastAPI** machen, da es sich im Grunde um Starlette auf Steroiden handelt.

### <a href="https://www.uvicorn.org/" class="external-link" target="_blank">Uvicorn</a>

Uvicorn ist ein blitzschneller ASGI-Server, der auf uvloop und httptools basiert.

# Downloaded from https://github.com/metallb/metallb/raw/v0.13.12/config/manifests/metallb-native.yaml
# With quay.io hub replaced with gcr.io/istio-testing
# And probes tuned to startup faster
apiVersion: v1
kind: Namespace
metadata:
  labels:
    pod-security.kubernetes.io/audit: privileged
    pod-security.kubernetes.io/enforce: privileged
    pod-security.kubernetes.io/warn: privileged
  name: metallb-system
---
apiVersion: apiextensions.k8s.io/v1

Here are some examples of when that could make sense:

#### A Simple App

You could want a process manager in the container if your application is **simple enough** that you don't need (at least not yet) to fine-tune the number of processes too much, and you can just use an automated default (with the official Docker image), and you are running it on a **single server**, not a cluster.

#### Docker Compose

build:linux --copt="-Wswitch"
build:linux --copt="-Werror=switch"
# Required for building with clang
build:linux --copt="-Wno-error=unused-but-set-variable"

# Linux ARM64 specific options
build:linux_arm64 --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3"


# On Windows, `__cplusplus` is wrongly defined without this switch
# See https://devblogs.microsoft.com/cppblog/msvc-now-correctly-reports-__cplusplus/

    under `tf.keras.dtensor` in this release (refer to the `tf.keras` entry).
    The tutoral and guide for DTensor will be published on
    https://www.tensorflow.org/. Please stay tuned.

*   [oneDNN CPU performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md)
    are available in Linux x86, Windows x86, and Linux aarch64 packages.

and may explain why type inference fails in unusual code situations.
But by and large these rules can be ignored when writing Go code:
type inference is designed to mostly "work as expected",
and the unification rules are fine-tuned accordingly.
</p>

<p>
Type unification is controlled by a <i>matching mode</i>, which may
be <i>exact</i> or <i>loose</i>.
As unification recursively descends a composite type structure,