小编Tam*_*eem的帖子

我们有32个V-CPU，RAM为28 GB，Local Executor但是气流仍然在利用所有资源，这导致资源的过度利用，最终破坏了系统的执行。

以下是根据内存使用情况排序的ps -aux输出。

   PID %CPU %MEM    VSZ   RSS TTY      STAT START   TIME COMMAND
  1336  3.5  0.9 1600620 271644 ?      Ss   Feb18  23:41 /usr/bin/python /usr/local/bin/airflow webs
  9434 32.3  0.9 1835796 267844 ?      Sl   03:09   0:31 [ready] gunicorn: worker [airflow-webserver
 10043  9.1  0.9 1835796 267844 ?      Sl   03:05   0:33 [ready] gunicorn: worker [airflow-webserver
 25397 17.4  0.9 1835796 267844 ?      Sl   03:08   0:30 [ready] gunicorn: worker [airflow-webserver
 30680 13.0  0.9 1835796 267844 ?      Sl   03:06   0:36 [ready] gunicorn: worker …

我正在尝试在Google Cloud Compute引擎实例上部署Airflow。

为了部署脚本，初始化操作中有一些特定的更改（用于初始化云VM的Shell脚本）。我想知道我是否可以使用Terraform处理此问题。

这是我的Terraform脚本。

provider "google" {
  region      = "${var.region}"
  project     = "${var.project_name}"
  credentials = "${file("${var.credentials_file_path}")}"
  zone        = "${var.region_zone}"
}

resource "google_sql_database_instance" "master" {
  name = "${var.db_instance}"
  region = "${var.region}"
  settings {
    tier = "db-n1-standard-1"
  }
}


resource "google_sql_user" "users" {
  name     = "${var.db_user}"
  instance = "${google_sql_database_instance.master.name}"
  host     = "%"
  password = "${var.db_password}"
  depends_on = ["google_sql_database_instance.master"]
}


resource "google_sql_database" "airflow" {
  name      = "${var.db_name}"
  instance  = "${google_sql_database_instance.master.name}"
  charset   = "utf8"
  collation = "utf8_general_ci"
  depends_on = ["google_sql_database_instance.master"]
}

resource "google_compute_instance" …