PgConf.Russia 2019

In this master class, I will take you step-by step through a major upgrade of PostgreSQL. Through our practice we see a lot of different PostgreSQL servers in production environment and often, almost too often teams who once made PostgreSQL their database of choice never update it following the initial installation. The are many different reasons for it, the result, however, is the same - they all miss out on the new useful features of the newer releases and reduced database performance.
The goal of my masterclass is to equip attendees with necessary tools for performing PostgreSQL upgrade. I will take you through each step of the major upgrade and will dive into each executed command. I will also explain the particular order in which I perform an upgrade and explain the consequences of not following this order or missing a particular step. We will perform an upgrade of PostgreSQL 9.0 to 11. My hope is that following this masterclass number of outdated PostgreSQL database will reduce since participants will then go back to their databases and make sure that they are running the most recent version.

While doing development of one of our project we were asked to build HA database using Postgres, geographically distributed.

First our choice was obvious, we started to work with big 3 cloud providers, but soon it was quite understand that everything costs big enough for us. Also there were a bunch of incompatibilities with unsupported extensions as well as londiste replication we were heavily used.

I will talk about why we chose patroni, what types of problem we faced with and patroni's special features can dramatically simplify deploy and everyday usage.

Shared_buffers = 25% – is it too much or not enough? Or it's the right value?

How can we ensure that this – pretty much outdated – recommendation suit well our needs?

It is time to start apply enterprise-level approach to tuning postgresql.conf. Not using various blind auto-tuners or advices from old articles and blog posts, but based on the following two aspects:

1. comprehensive database experiments, conducted in automated fashion, repeated multiple times in conditions as close to production as possible, and
2. deep understanding of DBMS and OS internals.

Using Nancy CLI (https://gitlab.com/postgres.ai/nancy) we will consider a concrete example: infamous shared_buffers, under various circumstances, in various projects. We will try to figure out, how to optimize this settings for given infrastructure, database, and workload.

Patroni is getting art of state standard framework for building HA clusters with postgres now.

During session we will build simple 3 node cluster using mentioned stack.

We will discuss patroni's architecture, and most interesting parameters from it's configuration. We will check how actually failover works and how could you initialise cluster.

After session you will be able to built such cluster from scratch in minutes using given ansible playbooks.