Shulou(Shulou.com)06/03 Report--

First of all, our infrastructure is mainly composed of computing, storage and network. In our previous model, virtualization technology is mainly used. No matter which virtualization technology is used in the actual production environment, it mainly improves the delivery efficiency through templates, which are mainly composed of operating systems and applications.

What is Packer?

Packer is an open source tool for creating identical machine images for multiple platforms from a single source configuration. Packer is lightweight, runs on every major operating system, and can create machine images for multiple platforms in parallel. Packer does not replace configuration management like Chef or Puppet. In fact, when creating an image, Packer can install software on the image using tools such as Chef or Puppet.

An image is a single static unit containing a preconfigured operating system and installed software for quickly creating a new running machine. Mirrors can be created in different formats for different platforms. This includes AMI for EC2, VMDK / VMX files for VMware, OVF export for VirtualBox, etc.

Packer application scenarios

l Continuous delivery

Packer is a lightweight command-line tool that makes it a perfect tool for pipeline links, generating a brand new image for us when we deploy software using chef or puppet on a different platform. In the pipeline link, if the latest image can meet the requirements of the business system after testing and verification, it provides a stable and reliable infrastructure environment for the subsequent launch of the business system.

l Development and production environment level

Packer keeps development, test and production environments as consistent as possible, allowing you to deploy the same image on different platforms at the same time. If you use AWS and VMware platforms, Packer allows you to deploy the same image template on both platforms at the same time. Combining the above examples can make your infrastructure more flexible and achieve consistency from development to production.

l Demo Demo

Packer is ideal for Demo application delivery, as the application continues to upgrade, users can easily deploy the application Demo to different platforms at the same time through automated installation deployment software.

Without Packer, how would we do it:

Packer如何做：

软件安装

https://www.packer.io/downloads.html

制作镜像

Packer支持的平台

Alicloud ECS

Amazon EC2

Azure

CloudStack

DigitalOcean

Docker

File

Google Cloud

Hetzner Cloud

Hyper-V

LXC

LXD

NAVER Cloud

Null

1&1

OpenStack

Oracle

Parallels

ProfitBricks

QEMU

Scaleway

Triton

VirtualBox

VMware

Custom

使用案例

下面通过在阿里云上创建一个包含Redis数据库的镜像的简单实例来学习如何使用Packer。

创建quick-start.json 文件

编辑文件

{

"variables": {

"access_key": "{{env `ALICLOUD_ACCESS_KEY`}}",

"secret_key": "{{env `ALICLOUD_SECRET_KEY`}}"

},

"builders": [{

"type":"alicloud-ecs",

"access_key":"{{user `access_key`}}",

"secret_key":"{{user `secret_key`}}",

"region":"cn-beijing",

"image_name":"packer_test2",

"source_image":"centos_7_04_64_20G_alibase_201701015.vhd",

"ssh_username":"root",

"instance_type":"ecs.n1.tiny",

"io_optimized":"true",

"image_force_delete":"true"

}],

"provisioners": [{

"type": "shell",

"inline": [

"sleep 30",

"yum install redis.x86_64 -y"

]

}]

}

创建镜像

packer build quick-start.json

Packer支持的Provisioners

Ansible Local

Ansible Remote

Breakpoint

Chef Client

Chef Solo

Converge

File

PowerShell

Puppet Masterless

Puppet Server

Salt Masterless

Shell

Shell (Local)

Windows Shell

Windows Restart

Custom

Packer的价值

也许你会说我在不同的平台安装好云主机再部署好应用不就行了，何必要如此麻烦？如果你需要在多个平台更新镜像如何操作呢，是否需要一步一步的登录不同平台，生成云主机，更新应用，再生成镜像，最后通过镜像部署新的云主机呢？Packer要做的事情就是将不同平台的镜像转换为代码化管理，这样使镜像的修改和调整变的更为灵活。

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