添加+到facet结果(add + to facet result)

 有多种方法可以自动启动AWS EC2实例。 
 
 
 
 使用已安装的软件创建AMI，并使用AMI和AWS Web Console配置新服务器。 
 
 
 在“用户数据”一节中定义创建CloudFormation脚本并使用Shell脚本（或Windows中的命令行脚本）自动安装软件。 在这里，您可以重新使用S3中的CloudFormation存储来创建新的实例。 
 
 
 使用AWS CLI（包含脚本的Shell命令）或AWS SDK（例如Python boto3包）来配置环境。 为此，您需要创建一个IAM用户（或角色，如果脚本在EC2实例中执行），并具有设置资源所需的权限。 
 
 
 此外，您可以结合使用这些选项，以便于维护。 例如，如果您计划为每个部署设置VPC，网络等，则最好在CloudFormation中保留基础架构配置，同时可能是设置用Boto3编写的EC2实例。 您可以触发Boto3中CloudFormation和其他代码的执行。 
 
 请参阅文章使用Python自动化AWS和LinuxAcademy中的Boto3一步一步指南。 

There are multiple approaches to automate launching AWS EC2 instances.
 
 
 
Creating a AMI with the installed software, and using the AMI and AWS Web Console to provision new servers.
 
 
Creating a CloudFormation Script and having Shell Scripts(Or commandline scripts in Windows) to automate the installation of the software define in "User Data" section. Here you can re-use the CloudFormation storing in S3 for creating new instances.
 
 
Use AWS CLI (Shell commands with scripts) or AWS SDKs (e.g Python boto3 package) to provision the environments. For this you need to create a IAM user (Or Role, if the scripts executes inside an EC2 instance) with required permission to provision the resources.
 
 
In addition you can use a combination of these options, to make it easier to maintain. For example, if you plan to setup VPC, Network & etc. for each deployment, its better to keep the infrastructure provisioning in CloudFormation while, may be the setting up of EC2 instance written in Boto3. You can trigger the execution of both CloudFormation and other code in Boto3.
 
Refer the article Automating AWS With Python and Boto3 from LinuxAcademy for step by step guide.