{ largeElement, factor ->
                    List(factor) { SmallSubprojectBucket(largeElement.subProject, parallelization(factor)) }
                },
                { list ->
                    SmallSubprojectBucket(list.map { it.subProject }, parallelization(1))
                },
                testCoverage.expectedBucketNumber,
                MAX_PROJECT_NUMBER_IN_BUCKET,
            )

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

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

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

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,...

* Google Compute Engine PD Detach fails if node no longer exists ([29358](https://github.com/kubernetes/kubernetes/issues/29358))
* Mounting (only 'default-token') volume takes a long time when creating a batch of pods  (parallelization issue) ([28616](https://github.com/kubernetes/kubernetes/issues/28616))
* Error while tearing down pod, "device or resource busy" on service account secret ([28750](https://github.com/kubernetes/kubernetes/issues/28750))

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 **replicados** que ejecutan...