Chapter 1 , Hardware Planning, sets the tone by covering the role that appropriate hardware selection plays in a successful PostgreSQL cluster of any size.
Chapter 2, Handling and Avoiding Downtime, provides safe settings and defaults for a stable cluster and explains basic techniques for responding to mishaps.
Chapter 3, Pooling Resources, presents PgBouncer and pgpool, two tools geared toward controlling PostgreSQL connections. Together, these can provide an abstraction layer to reduce the effect of outages and increase system performance.
Chapter 4, Troubleshooting, introduces a battery of common Unix and Linux tools and resources that can collect valuable diagnostic information. It also includes a couple of PostgreSQL views that can assist in finding database problems.
Chapter 5, Monitoring, further increases availability by adding Nagios, check_mk, collectd, and Graphite to watch active PostgreSQL clusters. Find potential problems before they happen and stay informed.
Chapter 6, Replication, discusses several PostgreSQL replication scenarios and techniques for more durable data. This includes logical replication tools such as Slony, Bucardo, Londiste, and the newly introduced pglogical.
Chapter 7, Replication Management Tools, brings WAL management to the forefront. Integrate Barman, OmniPITR, repmgr, or walctl into PostgreSQL to further prevent data loss and control complicated multi-server clusters. Or preserve your WAL data safely on the cloud with WAL-E.
Chapter 8, Simple Stack, proposes architecture comprised of HAProxy, Patroni, and etcd. This three-layer stack produces a self-healing and expandable cluster that’s easy to manage.
Chapter 9, Advanced Stack, explains how to combine LVM, DRBD, and XFS to build a solid and durable foundation. Keep data on two servers simultaneously to prevent costly outages. It's for OLTP systems where even PostgreSQL replication isn’t fast enough.
Chapter 10, Cluster Control, incorporates Pacemaker into the advanced stack. We fully automate PostgreSQL server migrations in case of impending maintenance or hardware failure. We add intricate rulesets to control outage and recovery protocols.
Chapter 11, Data Distribution, shows how PostgreSQL features like foreign data wrappers and materialized views can produce a scalable cluster. Included is a simple data sharding API technique to reduce dependency on a single PostgreSQL server.
