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PostgreSQL 12 High Availability Cookbook

PostgreSQL 12 High Availability Cookbook

By : Shaun Thomas
4.5 (2)
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PostgreSQL 12 High Availability Cookbook

PostgreSQL 12 High Availability Cookbook

4.5 (2)
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)
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Deciding whether multi-master is right for you

Multi-master PostgreSQL promises many exciting benefits that are hard to ignore. Despite this, there are some inherent limitations that could potentially prevent safe adoption within the application stack. Failure to account for these before deploying multi-master PostgreSQL could result in data loss or disruption of the cluster itself.

Consider, for example, what happens if two nodes accept a write for the same tuple. How should the conflict be resolved? Are there any necessary changes to the schema, or the application itself, before the adoption of the multi-master approach is safe? What else must we plan for?

While not an exhaustive resource, this recipe will attempt to answer many pressing concerns related to multi-master PostgreSQL. Some of these are based on theoretical cluster concepts.

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