```yaml
networkGateway: network-1
```

### Migrating from other installation methods

Installations from other installation methods (such as istioctl, Istio Operator, other helm charts, etc) can be migrated to use the new Helm charts
following the guidance below.
If you are able to, a clean installation is simpler. However, this often requires an external IP migration which can be challenging.

* Modèles **SQLAlchemy** (indépendants des extensions Flask, afin qu'ils puissent être utilisés directement avec des *workers* Celery).
* Modèle de démarrages basiques pour les utilisateurs (à modifier et supprimer au besoin).
* Migrations **Alembic**.
* **CORS** (partage des ressources entre origines multiples, ou *Cross Origin Resource Sharing*).
* *Worker* **Celery** pouvant importer et utiliser les modèles et le code du reste du backend.

## Create the tables

In this case, we are creating the tables in the same Python file, but in production, you would probably want to create them with Alembic, integrated with migrations, etc.

Here, this section would run directly, right before starting your **FastAPI** application.

* Create an `engine`.
* Create all the tables from the `metadata` object.

```Python hl_lines="25-28"

And it will work and will be useful **during development**.

But if your connection to the server is lost, the **running process** will probably die.

And if the server is restarted (for example after updates, or migrations from the cloud provider) you probably **won't notice it**. And because of that, you won't even know that you have to restart the process manually. So, your API will just stay dead. 😱

### Run Automatically on Startup

	FileRootSystemCACert = "file-root:system"
)

// TODO: For 1.8, make sure MeshConfig is updated with those settings,
// they should be dynamic to allow migrations without restart.
// Both are critical.
var (
	// Require3PToken disables the use of K8S 1P tokens. Note that 1P tokens can be used to request

Two approaches to migrations stand out:

 * Migrating the existing syntax of your build to Kotlin, bit by bit, while retaining the structure — what we call a _mechanical migration_
 * Restructuring your build logic towards Gradle best practices and switching to Kotlin DSL as part of that effort

Both approaches are viable.
A mechanical migration will be enough for simple builds.

+
The main downside is the extra work required to perform the migration, particularly if the existing build is complex and has many inter-project dependencies.
However, these builds often benefit the most from a switch to idiomatic Gradle.
In addition, Gradle provides many features that can ease the migration, such as the ability to <<ant#sec:using_ant_tasks,use core and custom Ant tasks>> directly from a Gradle build.

This may make migrating between the two seem intimidating, but migrations can be surprisingly easy because Gradle follows many of the same conventions as Maven -- such as the <<java_plugin#sec:java_project_layout,standard project structure>> -- and its dependency management works in a similar way.

Here we lay out a series of steps for you to follow that will help facilitate the migration of any Maven build to Gradle:

If in your use case there's no problem in running those previous steps **multiple times in parallel** (for example if you are not running database migrations, but just checking if the database is ready yet), then you could also just put them in each container right before starting the main process.

### Single Container

## Migration From Other Enterprise Search Systems

### Google Search Appliance (GSA) / Google Mini

Fess provides a [Google Search Appliance](https://enterprise.google.com/search/products/gsa.html) (GSA) compatible API. To enable this API, set `web.api.gsa=true` to system.properties. This will enable an enpoint at `<Fess Server Name>:8080/gsa`. When a search query is sent to `<Fess Server Name>:8080/gsa/?q=QUERY`, a GSA compatible response will be returned