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PostgreSQL High Availability Cookbook

PostgreSQL High Availability Cookbook - Second Edition

By : Shaun Thomas
5 (2)
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PostgreSQL High Availability Cookbook

PostgreSQL High Availability Cookbook

5 (2)
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 (12 chapters)
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Introduction

Thus far in this book, we've discussed quite an array of functionality and methodology dedicated to keeping PostgreSQL systems online. By now, we have a burgeoning menagerie of replication utilities, system monitoring tools, connection pooling layers, and even a handful of troubleshooting tips.

Then we moved on to combining several of these techniques and a few others to create a software stack that automates and protects a PostgreSQL cluster. Yet despite the power demonstrated in the Chapter 8, Simple Stack, we're still reliant primarily on PostgreSQL replication to safeguard replicated data. If we have an extremely high transaction throughput, even PostgreSQL replication is too slow to fully resist data-loss in the event of a server outage.

What tools can we use to safeguard our critical data beyond the guarantees granted by PostgreSQL? Where do we go next?

As it turns out, simply...

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