Book Image

PostgreSQL High Availability Cookbook - Second Edition

By : Shaun Thomas
Book Image

PostgreSQL High Availability Cookbook - Second Edition

By: Shaun Thomas

Overview of this book

Databases are nothing without the data they store. In the event of a failure - catastrophic or otherwise - immediate recovery is essential. By carefully combining multiple servers, it’s even possible to hide the fact a failure occurred at all. From hardware selection to software stacks and horizontal scalability, this book will help you build a versatile PostgreSQL cluster that will survive crashes, resist data corruption, and grow smoothly with customer demand. It all begins with hardware selection for the skeleton of an efficient PostgreSQL database cluster. Then it’s on to preventing downtime as well as troubleshooting some real life problems that administrators commonly face. Next, we add database monitoring to the stack, using collectd, Nagios, and Graphite. And no stack is complete without replication using multiple internal and external tools, including the newly released pglogical extension. Pacemaker or Raft consensus tools are the final piece to grant the cluster the ability to heal itself. We even round off by tackling the complex problem of data scalability. This book exploits many new features introduced in PostgreSQL 9.6 to make the database more efficient and adaptive, and most importantly, keep it running.
Table of Contents (18 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

Getting started with the Linux Volume Manager

The Linux Volume Manager (LVM) is something of an optional master control panel for Linux storage devices. It can combine several devices into one, allows arbitrary storage grouping far more granular than simple partitions, and provides functionality such as data snapshots and reorganization. It's very powerful, and in the right hands greatly improves potential server uptime.

It is also the first layer above the raw storage device in our stack. We start with LVM instead of DRBD, because DRBD at the device level is extremely messy. What do we gain by insulating DRBD from the raw storage device?

  • We can easily add storage to the LVM device group assigned to DRBD
  • DRBD can be resized while in an online state
  • We can perform storage migrations without taking PostgreSQL offline

None of this is possible unless LVM is the first layer. For a high-availability server, this is extremely desirable. Follow along to see how it works.

Getting ready

At this point, all...