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

Using LVM snapshots

One of the reasons we created a second layer of LVM on top of DRBD was to provide filesystem snapshot capabilities. When we create a snapshot, all files on a particular volume will appear static on that snapshot until one of the following two things happens:

  • We destroy the snapshot
  • The amount of changes on the source volume is larger than the space we reserved for the snapshot

This is the primary reason we left 5 percent space unused within our PostgreSQL volume group. If we create a snapshot, up to 5 percent of the database can change before we have to remove it. For larger storage devices, this should give us a lot of time to perform emergency restores, create byte-stable backups, or perform any other operation that requires consistent data.

In this recipe, we'll learn how to properly allocate, use, and remove an LVM snapshot.

Getting ready

For this recipe, we want a formatted and active XFS filesystem. Please follow the recipe in Formatting an XFS filesystem before continuing...