企业级 Puppet 配置管理实战指南

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"Mastering Puppet(PACKT,2ed,2016)是关于 Puppet 配置管理系统及其语言的专业书籍，旨在帮助系统管理员高效管理大量系统并防止配置漂移。本书针对扩展 Puppet 以处理大量节点时遇到的问题进行了深入探讨，并教你如何将 Puppet 整合到企业环境中，支持多个开发者同时协作开发 Puppet 代码。此外，还涵盖了编写自定义事实（custom facts）和创建自定义模块来解决问题的方法。书中还将介绍进行报告和编排任务的流行选项，以及各种故障排查技术。无论组织规模大小，书中的概念都具有实用性。通过阅读本书，读者将学会处理规模问题、异常代码，自动化工作流程，并支持多人协同开发。" 在 Puppet 的世界里，配置管理是关键。Puppet 是一种用于系统管理的配置管理系统，它使用专门的语言，使得系统管理员能够有效地管理和维护大规模的系统集群。Puppet 的主要目标是确保系统的状态始终与预期保持一致，避免由于手动配置导致的不一致或错误。 "Mastering Puppet Second Edition" 深入讲解了 Puppet 的高级用法，包括： 1. **扩展 Puppet**：当需要管理的节点数量增加时，如何扩展 Puppet 的能力，使其能有效地处理大型部署。 2. **多开发者协作**：如何设计 Puppet 代码结构，以便多个开发者可以同时安全地工作，避免代码冲突。 3. **自定义事实**：编写自定义事实是为了获取系统特定的信息，这些信息可以被 Puppet 用于更精确的资源管理和决策。 4. **模块化开发**：学习如何创建自定义模块，以解决特定环境下的问题，提高 Puppet 的灵活性和可重用性。 5. **报告和编排**：探索不同的工具和技术，用于监控 Puppet 的执行情况，生成报告，以及执行复杂的自动化工作流。 6. **故障排查**：提供实用的故障排查技巧和方法，帮助读者快速定位和解决 Puppet 实施过程中遇到的问题。 7. **规模化挑战**：处理大规模部署时可能遇到的问题，如性能优化、错误处理和异常管理。本书适合已经对 Puppet 有一定基础的读者，通过学习，他们将能提升 Puppet 技能，更好地应用于企业级环境中。对于希望深入了解 Puppet 并将其应用到复杂环境的系统管理员和 DevOps 工程师来说，这本书是一份宝贵的资源。

Preface

[ ix ]

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Questions

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questions@packtpub.com, and we will do our best to address the problem.

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Chapter 1

[ 3 ]

When nodes connect to the Puppet master, they connect to the master service.

In prior versions of Puppet (versions 3.6 and older), the accepted method to run

the Puppet master service was through the Passenger framework. In Puppet 3.7

and above, this was replaced with a new server, puppetserver. Puppet version 4

and above have deprecated Passenger; support for Passenger may be completely

removed in a future release. puppetserver runs Puppet as a JRuby process within

a JVM that is wrapped by a Jetty web server. There are many moving parts in the

new puppetserver service, but the important thing is that Puppet Labs built this

service to achieve better performance than the older Passenger implementation.

A Puppet master running the puppetserver service can typically handle around

5,000 individual nodes; this is a vast improvement.

A quick word on versions, Puppet has now changed how they distribute

Puppet. Puppet is now distributed as an all-in-one package. This package

includes the required Ruby dependencies all bundled together. This new

packaging has resulted in a new package naming scheme, named Puppet

collections or PC. Numbering begins at 1 for the PC packages, so you

will see PC1 as the package and repository name, the version of Puppet

contained within those packages is version 4. Additionally, Puppet

Enterprise has changed its name to a year based system; the rst release of

that series was 2015.1, which had a PC release of 1.2.7. More information

on Puppet collections can be found at https://puppetlabs.com/

blog/welcome-puppet-collections.

puppetserver

The puppetserver uses the same design principles as PuppetDB. PuppetDB uses

a new framework named Trapperkeeper. Trapperkeeper is written in Clojure and

is responsible for managing the HTTP/TLS endpoints that are required to serve as

a Puppet master server. More information about Trapperkeeper is available at the

project website at https://github.com/puppetlabs/trapperkeeper.

Building a Puppet master

To build a split Puppet master conguration, we will rst start with an empty

machine running an enterprise Linux distribution, such as CentOS, RedHat

Enterprise Linux, or Springdale Linux. I will be using Springdale Linux 7 for my

example machines. More information on Springdale is available at https://

springdale.math.ias.edu/. I will start by building a machine named lb (load

balancer), as my rst Puppet master. The puppetserver process uses a lot of

memory; the lb machine needs to have at least 2.5GB of memory to allow the

puppetserver process to run.

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