12 — Cloud Tasks y Scheduler

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Cloud Tasks es una cola de tareas gestionada para trabajos en segundo plano. Cloud Scheduler activa el worker en un horario. Este capítulo crea ambos con Terraform.

Cómo encajan juntos

Django (solicitud web)
    │
    ├── Encola tarea a la cola de Cloud Tasks
    │
    └── Responde al usuario inmediatamente

Cola de Cloud Tasks
    │
    └── Cloud Scheduler (activa cada minuto)
              │
              ▼
         Cloud Run Job (worker)
              │
              └── Extrae tareas de la cola
                    │
                    └── Las procesa (enviar email, etc.)

Crear la cola de Cloud Tasks

Agrega a infrastructure/main.tf:

# Cloud Tasks queue
resource "google_cloud_tasks_queue" "default" {
  name     = "mycoolproject-default"
  location = var.region

  # Retry configuration (if a task fails, retry it)
  retry_config {
    min_backoff = "10s"
    max_backoff = "600s"
    max_attempts = 5
    max_retry_duration = "600s"
  }
}

output "cloud_tasks_queue_name" {
  value = google_cloud_tasks_queue.default.name
}

Ejecuta terraform apply para crear la cola.

Crear el worker de Cloud Tasks (Cloud Run Job)

Cloud Tasks contiene tareas, pero un Cloud Run Job realmente las procesa. Agrega a main.tf:

# Cloud Run Job for processing Cloud Tasks
resource "google_cloud_run_v2_job" "worker" {
  name     = "mycoolproject-worker"
  location = var.region

  service_account = google_service_account.worker.email

  template {
    launch_stage = "GA"

    template {
      spec {
        service_account = google_service_account.worker.email

        containers {
          image = "${google_artifact_registry_repository.app.repository_url}/app:latest"
          command = ["uv", "run", "django_q", "cluster"]
          args = []
        }

        resources {
          limits {
            cpu    = "1"
            memory = "512Mi"
          }
        }

        timeout = "3600s"
        max_instance_count = 3
      }

      annotations = {
        "cloud.google.com/location" = var.region
      }
    }
  }

  ingress = "INGRESS_TRAFFIC_ALL"
}

resource "google_cloud_run_v2_job_iam_member" "worker_invoker" {
  location = google_cloud_run_v2_job.worker.location
  name     = google_cloud_run_v2_job.worker.name
  role     = "roles/run.invoker"
  member   = "serviceAccount:${google_service_account.scheduler.email}"
}

output "worker_job_name" {
  value = google_cloud_run_v2_job.worker.name
}

Cloud Scheduler para activar el worker

Agrega a main.tf:

# Service account for Cloud Scheduler
resource "google_service_account" "scheduler" {
  account_id   = "mycoolproject-scheduler"
  display_name = "MyCoolProject Scheduler Service Account"
}

resource "google_project_iam_member" "scheduler_cloud_run_invoker" {
  project = var.project_id
  role    = "roles/run.invoker"
  member  = "serviceAccount:${google_service_account.scheduler.email}"
}

# Cloud Scheduler job - triggers worker every minute
resource "google_cloud_scheduler_job" "worker_trigger" {
  name        = "mycoolproject-worker-trigger"
  description = "Trigger the Cloud Tasks worker every minute"
  region      = var.region
  schedule    = "* * * * *"

  http_target {
    uri         = "https://${var.region}-run.googleapis.com/v2/projects/${var.project_id}/locations/${var.region}/jobs/${google_cloud_run_v2_job.worker.name}:run"
    http_method = "POST"

    oidc_token {
      service_account_email = google_service_account.scheduler.email
    }
  }

  retry_config {
    min_backoff_duration  = "10s"
    max_backoff_duration  = "60s"
    max_retry_duration    = "60s"
    retry_count           = 3
  }

  time_zone = "UTC"
}

output "scheduler_job_name" {
  value = google_cloud_scheduler_job.worker_trigger.name
}

Ejecuta terraform apply para crear el job del scheduler.

El formato de horario cron

* * * * * significa "cada minuto." El formato es:

┌───────────── minuto (0-59)
│ ┌───────────── hora (0-23)
│ │ ┌───────────── día del mes (1-31)
│ │ │ ┌───────────── mes (1-12)
│ │ │ │ ┌───────────── día de la semana (0-6, Domingo=0)
│ │ │ │ │
* * * * *

Horarios comunes:

Horario	Significado
`* * * * *`	Cada minuto
`0 * * * *`	Cada hora en el minuto 0
`0 9 * * *`	Cada día a las 9am
`0 9 * * 1-5`	Entre semana a las 9am
`/15 * * *`	Cada 15 minutos

Cómo Django encola tareas

Django usa la librería cliente de Google Cloud Tasks para encolar tareas:

from google.cloud import tasks_v2
import os

def send_welcome_email(user_id):
    client = tasks_v2.CloudTasksClient()
    queue_name = f"projects/{os.environ['GCP_PROJECT']}/locations/{os.environ['GCP_REGION']}/queues/mycoolproject-default"

    task = {
        "http_request": {
            "http_method": tasks_v2.HttpMethod.POST,
            "url": f"{os.environ['APP_URL']}/tasks/send-email/",
            "headers": {"Content-Type": "application/json"},
            "body": json.dumps({"user_id": user_id}).encode(),
        }
    }

    client.create_task(request={"parent": queue_name, "task": task})

La tarea apunta a una URL en tu app Django. El worker (Cloud Run Job) ejecuta django_q cluster que sondea la cola y procesa tareas.

Alternativa: Usar Django-Q directamente

Django-Q (django-q2) es una librería de cola de tareas construida sobre el ORM de Django. Puede usar Cloud Tasks como su broker en lugar de la base de datos:

# In settings/prod.py
Q_CLUSTER = {
    "name": "mycoolproject",
    "workers": 4,
    "timeout": 60,
    "broker": "cloudtasks",
    "project": os.environ["GCP_PROJECT"],
    "location": os.environ["GCP_REGION"],
    "queue": "mycoolproject-default",
}

Resumen: qué creamos

Cola de Cloud Tasks (mycoolproject-default)
Cloud Run Job para worker (mycoolproject-worker)
Job de Cloud Scheduler (activa worker cada minuto)
Service accounts e IAM para los tres