Em 15 de setembro de 2026, todos os ambientes do Cloud Composer 1 e da versão 2.0.x do Cloud Composer 2 vão atingir o fim da vida útil planejado e não poderão mais ser usados. Recomendamos planejar a migração para o Cloud Composer 3.
Para mais informações sobre o escalonamento de ambientes, consulte
Ambientes de escala.
Ambientes de escalonamento automático
Os ambientes do Cloud Composer 2 são escalonados automaticamente em resposta às demandas
dos DAGs e tarefas executados:
Se o ambiente apresentar uma carga pesada, o Cloud Composer aumentará automaticamente o número de workers no ambiente.
Se o ambiente não usar alguns workers, eles serão removidos para economizar recursos e custos do ambiente.
É possível definir o número mínimo e máximo de workers no ambiente.
O Cloud Composer faz o escalonamento automático do seu ambiente dentro dos limites definidos. É possível ajustar esses limites a qualquer momento.
O número de workers é ajustado com base na métrica de Meta de fator de escalonamento. Essa métrica é calculada com base no seguinte:
Número atual de workers
Número de tarefas do Celery na fila que não foram atribuídas a um worker
Número de workers inativos
Opção de configuração do Airflow celery.worker_concurrency
O escalonamento automático do Cloud Composer usa três escalonadores automáticos diferentes fornecidos pelo GKE:
O Cloud Composer configura esses escalonadores automáticos no cluster do ambiente. Isso faz o escalonamento automático do número de nós no cluster, do tipo de máquina e do número de workers.
Parâmetros de escalonamento e desempenho
Além do escalonamento automático, é possível controlar os parâmetros de escalonamento e desempenho do ambiente ajustando os limites de CPU, memória e disco para programadores, servidores da Web e workers. Ao fazer isso, é possível escalonar o ambiente verticalmente, além do escalonamento horizontal fornecido pelo recurso de escalonamento automático. É possível ajustar os parâmetros de escalonamento e desempenho dos programadores, do servidor da Web e dos workers do Airflow a qualquer momento.
O parâmetro de desempenho tamanho do ambiente controla os
parâmetros de desempenho da infraestrutura gerenciada do Cloud Composer
que inclui o banco de dados do Airflow. Selecione um tamanho maior de ambiente se você quiser executar um grande número de DAGs e tarefas com um desempenho de infraestrutura mais alto. Por exemplo, o tamanho de um ambiente maior aumenta
a quantidade de entradas de registro de tarefas do Airflow que o ambiente pode processar com
atraso mínimo.
Vários programadores
O Airflow 2 pode usar mais de um programador do Airflow ao mesmo tempo. Esse
recurso do Airflow também é conhecido como programador de alta disponibilidade. No Cloud Composer 2, é possível definir o número de programadores do seu ambiente e ajustá-lo a qualquer momento. O Cloud Composer não escalona automaticamente o número de programadores no seu ambiente.
Para mais informações sobre como configurar o número de programadores
do seu ambiente, consulte Ambientes de escala.
Espaço em disco do banco de dados
O espaço em disco para o banco de dados do Airflow aumenta automaticamente para acomodar a
demanda.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-08-26 UTC."],[[["\u003cp\u003eCloud Composer 2 environments automatically scale the number of workers based on the demands of executed DAGs and tasks, increasing workers during heavy loads and removing them during inactivity.\u003c/p\u003e\n"],["\u003cp\u003eThe environment's scaling is governed by the Scaling Factor Target metric, which considers the current worker count, queued tasks, idle workers, and the \u003ccode\u003ecelery.worker_concurrency\u003c/code\u003e Airflow setting.\u003c/p\u003e\n"],["\u003cp\u003eCloud Composer 2 utilizes three GKE autoscalers (Horizontal Pod Autoscaler, Cluster Autoscaler, and Node auto-provisioning) to automatically adjust the number of nodes, machine types, and workers in the environment's cluster.\u003c/p\u003e\n"],["\u003cp\u003eIn addition to autoscaling, users can manually adjust the CPU, memory, and disk limits for schedulers, web servers, and workers to vertically scale the environment, and they can also choose the environment size to control the managed Cloud Composer infrastructure.\u003c/p\u003e\n"],["\u003cp\u003eCloud Composer 2 allows for the configuration of multiple Airflow schedulers (HA scheduler) to be used simultaneously, but the number of schedulers is not automatically scaled by the system.\u003c/p\u003e\n"]]],[],null,["# Environment scaling\n\n[Cloud Composer 3](/composer/docs/composer-2/composer/docs/composer-3/environment-scaling \"View this page for Cloud Composer 3\") \\| **Cloud Composer 2** \\| [Cloud Composer 1](/composer/docs/composer-1/environment-scaling \"View this page for Cloud Composer 1\")\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nThis page describes how environment scaling works in Cloud Composer 2.\n\nOther pages about scaling:\n\n- For a guide about selecting optimal scale and performance parameters for your environment, see [Optimize environment performance and costs](/composer/docs/composer-2/optimize-environments).\n- For information about scaling your environments, see [Scale environments](/composer/docs/composer-2/scale-environments).\n\nAutoscaling environments\n------------------------\n\nCloud Composer 2 environments automatically scale in response to the demands\nof your executed DAGs and tasks:\n\n- If your environment experiences a heavy load, Cloud Composer automatically increases the number of workers in your environment.\n- If your environment does not use some of its workers, these workers are removed to save environment resources and costs.\n- You can set the minimum and maximum number of workers for your environment. Cloud Composer automatically scales your environment within the set limits. You can adjust these limits at any time.\n\nThe number of workers is adjusted based on\nthe [Scaling Factor Target](/composer/docs/composer-2/monitor-environments#worker-metrics) metric. This metric is\ncalculated based on:\n\n- Current number of workers\n- Number of Celery tasks in the Celery queue, that are not assigned to a worker\n- Number of idle workers\n- `celery.worker_concurrency` Airflow configuration option\n\nCloud Composer autoscaling uses three different autoscalers\nprovided by GKE:\n\n- [Horizontal Pod Autoscaler (HPA)](/kubernetes-engine/docs/concepts/horizontalpodautoscaler)\n- [Cluster Autoscaler (CA)](/kubernetes-engine/docs/concepts/cluster-autoscaler)\n- [Node auto-provisioning (NAP)](/kubernetes-engine/docs/how-to/node-auto-provisioning)\n\nCloud Composer configures these autoscalers in the environment's\ncluster. This automatically scales the number of nodes in the cluster, the\nmachine type and the number of workers.\n\nScale and performance parameters\n--------------------------------\n\nIn addition to autoscaling, you can control the scale and performance\nparameters of your environment by adjusting the CPU, memory, and disk limits\nfor schedulers, web server, and workers. By doing so you can scale your\nenvironment vertically, in addition to the horizontal scaling provided by the\nautoscaling feature. You can adjust the scale and performance parameters of\nAirflow schedulers, web server, and workers at any time.\n\nThe *environment size* performance parameter of your environment controls the\nperformance parameters of the managed Cloud Composer infrastructure\nthat includes the Airflow database. Consider selecting a larger environment\nsize if you want to run a large number of DAGs and tasks with higher\ninfrastructure performance. For example, larger environment's size increases\nthe amount of Airflow task log entries that your environment can process with\nminimal delay.\n| **Note:** Environment size is different from the environment presets. Environment presets, which you can select when you create an environment, determine all limits, scale, and performance parameters of your environment, including the environment size. Environment size determines only the performance parameters of the managed Cloud Composer infrastructure of your environment.\n\nMultiple schedulers\n-------------------\n\nAirflow 2 can use more than one Airflow scheduler at the same time. This\nAirflow feature is also known as the **HA scheduler**. In Cloud Composer 2,\nyou can set the number of schedulers for your environment and adjust it at any\ntime. Cloud Composer does not automatically scale the number of\nschedulers in your environment.\n\nFor more information about configuring the number of schedulers for your\nenvironment, see [Scale environments](/composer/docs/composer-2/scale-environments#scheduler-count).\n\nDatabase disk space\n-------------------\n\nDisk space for the Airflow database automatically increases to accommodate the\ndemand.\n\n\nWhat's next\n-----------\n\n- [Scale environments](/composer/docs/composer-2/scale-environments)\n- [Cloud Composer pricing](/composer/pricing)\n- [Create environments](/composer/docs/composer-2/create-environments)\n- [Environment architecture](/composer/docs/composer-2/environment-architecture)"]]
