[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-04-02。"],[[["Cloud 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."],["The environment's scaling is governed by the Scaling Factor Target metric, which considers the current worker count, queued tasks, idle workers, and the `celery.worker_concurrency` Airflow setting."],["Cloud 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."],["In 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."],["Cloud 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."]]],[]]
