TeamCityParallelTests(
                        methodJsonNode.get("numberOfBatches").asInt(),
                    )

                else -> throw IllegalArgumentException("Unknown parallelization method")
            }
        }
    }
}

class FunctionalTest(
    model: CIBuildModel,
    id: String,
    name: String,
    description: String,
    val testCoverage: TestCoverage,

> even if you have Gradle or Develocity build caching enabled for the project.
> The Gradle Build Tool repository is massive, and it will take ages to build on
> a local machine without necessary parallelization and caching.
> The full test suites are executed on the CI instance for multiple configurations,
> and you can rely on it after doing initial sanity check and targeted local testing.

### Copyright and License

normally have **just one process** (e.g. a Uvicorn process running your FastAPI application). They would all be **identical containers**, running the same thing, but each with its own process, memory, etc. That way you would take advantage of **parallelization** in **different cores** of the CPU, or even in **different machines**.

And the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So,...

processus** (par ex. un processus Uvicorn exécutant votre application FastAPI). Ils seront tous des **conteneurs identiques**, exécutant la même chose, mais chacun avec son propre processus, sa mémoire, etc. De cette façon, vous profiterez de la **parallélisation** sur **différents cœurs** du CPU, voire sur **différentes machines**.

Et le système de conteneurs distribués avec l'**équilibreur de charge** **distribuera les requêtes** à chacun des conteneurs exécutant votre application **à tour...

normalmente tendría **solo un proceso** (e.g., un proceso Uvicorn ejecutando tu aplicación FastAPI). Todos serían **contenedores idénticos**, ejecutando lo mismo, pero cada uno con su propio proceso, memoria, etc. De esa forma, aprovecharías la **paralelización** en **diferentes núcleos** de la CPU, o incluso en **diferentes máquinas**.

Y el sistema de contenedores distribuido con el **load balancer** **distribuiría las requests** a cada uno de los contenedores con tu aplicación **en turnos**....