使用自动化部署、运维和监控,在多个区域管理 AWS EC2、S3、Lambda 和 CloudWatch 资源。
aws-cloud-toolkit.Name.en:AWS云工具包.zh:AWS云服务工具包是一项面向实际任务的技能,主要用于Description.en:AWS云资源管理综合工具包,支持EC2,S3,RDS,Lambda操作,并自动部署m。它将相关步骤、工具调用和结果整理方式集中到统一流程中,帮助使用者更快完成目标并减少重复操作。
实际使用前应先确认任务范围、数据来源、运行环境、必要权限和关键参数,再依据技能说明逐步执行;若输入条件不完整,应先补齐信息或采用保守配置,避免因错误假设导致结果偏离需求。
执行过程中需要关注工具调用是否成功、接口或依赖是否可用、输出格式是否符合预期,并对异常提示、缺失字段和边界情况进行处理;涉及批量任务时,还应保存进度,避免中断后重复操作。
工具: ec2_manager
描述: 管理 AWS EC2 实例——列出、启动、停止、创建、终止
输入 Schema:
{
"action": {"type": "string", "enum": ["list", "start", "stop", "create", "terminate"]},
"instance_id": {"type": "string"},
"instance_type": {"type": "string", "default": "t2.micro"},
"image_id": {"type": "string"},
"key_name": {"type": "string"},
"security_group_ids": {"type": "array", "items": {"type": "string"}},
"region": {"type": "string", "default": "us-east-1"}
}
示例:
{
"action": "list",
"region": "us-east-1"
}
工具: s3_manager
描述: 管理 AWS S3 存储桶——创建、删除、列出、上传、下载对象
输入 Schema:
{
"action": {"type": "string", "enum": ["list_buckets", "create_bucket", "delete_bucket", "list_objects", "upload", "download", "delete_object"]},
"bucket_name": {"type": "string"},
"object_key": {"type": "string"},
"local_path": {"type": "string"},
"region": {"type": "string", "default": "us-east-1"}
}
示例:
{
"action": "list_buckets",
"region": "us-east-1"
}
工具: lambda_manager
描述: 部署与管理 AWS Lambda 函数
输入 Schema:
{
"action": {"type": "string", "enum": ["list", "create", "update", "delete", "invoke"]},
"function_name": {"type": "string"},
"runtime": {"type": "string", "default": "python3.9"},
"handler": {"type": "string"},
"role_arn": {"type": "string"},
"code_path": {"type": "string"},
"region": {"type": "string", "default": "us-east-1"}
}
工具: cloudwatch_monitor
描述: 使用 CloudWatch 指标与告警监控 AWS 资源
输入 Schema:
{
"action": {"type": "string", "enum": ["get_metrics", "create_alarm", "list_alarms", "get_logs"]},
"namespace": {"type": "string"},
"metric_name": {"type": "string"},
"dimensions": {"type": "object"},
"alarm_name": {"type": "string"},
"threshold": {"type": "number"},
"region": {"type": "string", "default": "us-east-1"}
}
环境变量:
AWS_ACCESS_KEY_ID=your_access_key AWS_SECRET_ACCESS_KEY=your_secret_key AWS_DEFAULT_REGION=us-east-1
from aws_cloud_toolkit import EC2Manager, S3Manager, LambdaManager
# EC2 操作
ec2 = EC2Manager(region='us-east-1')
instances = ec2.list_instances()
ec2.start_instance('i-1234567890abcdef0')
# S3 操作
s3 = S3Manager(region='us-east-1')
s3.create_bucket('my-new-bucket')
s3.upload_file('my-bucket', 'data.csv', '/local/path/data.csv')
# Lambda 操作
lambda_mgr = LambdaManager(region='us-east-1')
lambda_mgr.deploy_function('my-function', 'python3.9', 'handler.lambda_handler')
pip install boto3 python-dotenv
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