使用通知控制资源用量

本文档介绍了如何使用预算通知来有选择地控制资源使用情况。

为项目停用结算功能后，所有服务都会停止，且所有资源最终会被删除。如果您需要更精细的回答，则可以有选择地控制资源。例如，您可以停止某些 Compute Engine 资源，但 Cloud Storage 资源保持不变。仅停止部分资源可降低费用，而不会完全停用您的环境。

在以下示例中，项目使用许多 Compute Engine 虚拟机 (VM) 运行研究，并将结果存储在 Cloud Storage 存储分区中。此 Cloud Run 函数使用预算通知作为触发器，在超出预算后会关停所有 Compute Engine 实例，但不会影响存储的结果。

准备工作

在开始之前，您必须完成以下任务：

  1. 启用 Cloud Billing API
  2. 创建预算
  3. 设置程序化预算通知

设置 Cloud Run 函数

  1. 完成创建 Cloud Run 函数中的步骤。确保您将触发器类型设置为预算将使用的同一 Pub/Sub 主题。

  2. 添加以下依赖项：

    Node.js

    将以下内容复制到 package.json 文件中：

    {
  "name": "cloud-functions-billing",
  "private": "true",
  "version": "0.0.1",
  "description": "Examples of integrating Cloud Functions with billing",
  "main": "index.js",
  "engines": {
    "node": ">=16.0.0"
  },
  "scripts": {
    "compute-test": "c8 mocha -p -j 2 test/periodic.test.js --timeout=600000",
    "test": "c8 mocha -p -j 2 test/index.test.js --timeout=5000 --exit"
  },
  "author": "Ace Nassri <anassri@google.com>",
  "license": "Apache-2.0",
  "dependencies": {
    "@google-cloud/billing": "^4.0.0",
    "@google-cloud/compute": "^4.0.0",
    "google-auth-library": "^9.0.0",
    "googleapis": "^143.0.0",
    "slack": "^11.0.1"
  },
  "devDependencies": {
    "@google-cloud/functions-framework": "^3.0.0",
    "c8": "^10.0.0",
    "gaxios": "^6.0.0",
    "mocha": "^10.0.0",
    "promise-retry": "^2.0.0",
    "proxyquire": "^2.1.0",
    "sinon": "^18.0.0",
    "wait-port": "^1.0.4"
  }
}

    Python

    将以下内容复制到 requirements.txt 文件中：

    slackclient==2.9.4
google-api-python-client==2.131.0

  3. 将以下代码复制到 Cloud Run 函数中：

    Node.js 

    const {CloudBillingClient} = require('@google-cloud/billing');
const {InstancesClient} = require('@google-cloud/compute');

const PROJECT_ID = process.env.GOOGLE_CLOUD_PROJECT;
const PROJECT_NAME = `projects/${PROJECT_ID}`;
const instancesClient = new InstancesClient();
const ZONE = 'us-central1-a';

exports.limitUse = async pubsubEvent => {
  const pubsubData = JSON.parse(
    Buffer.from(pubsubEvent.data, 'base64').toString()
  );
  if (pubsubData.costAmount <= pubsubData.budgetAmount) {
    return `No action necessary. (Current cost: ${pubsubData.costAmount})`;
  }

  const instanceNames = await _listRunningInstances(PROJECT_ID, ZONE);
  if (!instanceNames.length) {
    return 'No running instances were found.';
  }

  await _stopInstances(PROJECT_ID, ZONE, instanceNames);
  return `${instanceNames.length} instance(s) stopped successfully.`;
};

/**
 * @return {Promise} Array of names of running instances
 */
const _listRunningInstances = async (projectId, zone) => {
  const [instances] = await instancesClient.list({
    project: projectId,
    zone: zone,
  });
  return instances
    .filter(item => item.status === 'RUNNING')
    .map(item => item.name);
};

/**
 * @param {Array} instanceNames Names of instance to stop
 * @return {Promise} Response from stopping instances
 */
const _stopInstances = async (projectId, zone, instanceNames) => {
  await Promise.all(
    instanceNames.map(instanceName => {
      return instancesClient
        .stop({
          project: projectId,
          zone: zone,
          instance: instanceName,
        })
        .then(() => {
          console.log(`Instance stopped successfully: ${instanceName}`);
        });
    })
  );
};

    Python 

    import base64
import json
import os
from googleapiclient import discovery
PROJECT_ID = os.getenv("GCP_PROJECT")
PROJECT_NAME = f"projects/{PROJECT_ID}"
ZONE = "us-west1-b"


def limit_use(data, context):
    pubsub_data = base64.b64decode(data["data"]).decode("utf-8")
    pubsub_json = json.loads(pubsub_data)
    cost_amount = pubsub_json["costAmount"]
    budget_amount = pubsub_json["budgetAmount"]
    if cost_amount <= budget_amount:
        print(f"No action necessary. (Current cost: {cost_amount})")
        return

    compute = discovery.build(
        "compute",
        "v1",
        cache_discovery=False,
    )
    instances = compute.instances()

    instance_names = __list_running_instances(PROJECT_ID, ZONE, instances)
    __stop_instances(PROJECT_ID, ZONE, instance_names, instances)


def __list_running_instances(project_id, zone, instances):
    """
    @param {string} project_id ID of project that contains instances to stop
    @param {string} zone Zone that contains instances to stop
    @return {Promise} Array of names of running instances
    """
    res = instances.list(project=project_id, zone=zone).execute()

    if "items" not in res:
        return []

    items = res["items"]
    running_names = [i["name"] for i in items if i["status"] == "RUNNING"]
    return running_names


def __stop_instances(project_id, zone, instance_names, instances):
    """
    @param {string} project_id ID of project that contains instances to stop
    @param {string} zone Zone that contains instances to stop
    @param {Array} instance_names Names of instance to stop
    @return {Promise} Response from stopping instances
    """
    if not len(instance_names):
        print("No running instances were found.")
        return

    for name in instance_names:
        instances.stop(project=project_id, zone=zone, instance=name).execute()
        print(f"Instance stopped successfully: {name}")

  4. 将入口点设置为要执行的正确函数：

    Node.js

    将入口点设置为 limitUse。

    Python

    将入口点设置为 limit_use。

  5. 查看自动设置的环境变量列表，并确定是否需要手动将 GCP_PROJECT 变量设置为运行虚拟机的项目。

  6. 设置 ZONE 参数。此参数是指超出预算时停止实例的地区。

  7. 点击部署。

配置服务账号权限

Cloud Run 函数作为自动创建的服务账号运行。为了控制使用量，您需要将服务账号权限授予项目中需要修改的任何服务，方法是完成以下步骤：

  1. 查看 Cloud Run 函数的详细信息，确定正确的服务账号。服务账号显示在页面底部。

  2. 前往 Google Cloud 控制台中的 IAM 页面，以设置相应权限。

    转到 IAM 页面

测试实例是否已停止

如需确保函数按预期运行，请按照测试 Cloud Run 函数中的步骤操作。

如果成功， Google Cloud 控制台中的 Compute Engine 虚拟机将停止。

后续步骤

查看其他程序化通知示例，了解如何执行以下操作：