Book Image

PostgreSQL 12 High Availability Cookbook - Third Edition

By : Shaun Thomas
Book Image

PostgreSQL 12 High Availability Cookbook - Third Edition

By: Shaun Thomas

Overview of this book

Databases are nothing without the data they store. In the event of an outage or technical catastrophe, immediate recovery is essential. This updated edition ensures that you will learn the important concepts related to node architecture design, as well as techniques such as using repmgr for failover automation. From cluster layout and hardware selection to software stacks and horizontal scalability, this PostgreSQL cookbook will help you build a PostgreSQL cluster that will survive crashes, resist data corruption, and grow smoothly with customer demand. You’ll start by understanding how to plan a PostgreSQL database architecture that is resistant to outages and scalable, as it is the scaffolding on which everything rests. With the bedrock established, you'll cover the topics that PostgreSQL database administrators need to know to manage a highly available cluster. This includes configuration, troubleshooting, monitoring and alerting, backups through proxies, failover automation, and other considerations that are essential for a healthy PostgreSQL cluster. Later, you’ll learn to use multi-master replication to maximize server availability. Later chapters will guide you through managing major version upgrades without downtime. By the end of this book, you’ll have learned how to build an efficient and adaptive PostgreSQL 12 database cluster.
Table of Contents (17 chapters)

Having enough IOPS

IOPS (stands for Input/Output Operations Per Second) describes how many operations a device can perform per second before it should be considered saturated. If a device is saturated, further requests must wait until the device has spare bandwidth. A server overwhelmed with requests can amount to seconds, minutes, or even hours of delayed results.

Depending on application timeout settings and user patience, a device with low IOPS appears as a bottleneck that reduces both system responsiveness and the perception of quality. A database with insufficient IOPS to service queries in a timely manner is unavailable for all intents and purposes. It doesn't matter if PostgreSQL is still online and serving requests in this scenario, as its availability has already suffered.

In this recipe, we will attempt to account for future storage and throughput needs based on...