PgConf.Russia 2019

It's so good when database behaves predictable. When the performance is lacking, you just add CPU cores, terabytes of RAM and millions of IOPS, and everything becomes good again. But it's rather unpleasant, when server have plenty of free resources, while database is still running slow. And it's especially sad if stress testing detects no problems, while real life workload of the same volume makes your database hang.

In this talk I will consider bottlenecks of PostgreSQL, which we met in our practice, and which causes sad behavior described above. I'll also explain what can be done at user level in order to evade these bottlenecks, and what developers are planning to do in order to eliminate those bottlenecks. I'm also planning give some recipes of stress testing, which could have to evade surprises in production.

Magic tricks followed by exposure (1C+PG):

• Focus number one. How to convince the accounting department to buy a new server.
• Focus number two. How to show that MS SQL is faster than PostgreSQL.
• Focus number three. How to show that PostgreSQL is faster than MS SQL Server.

In this session we will deep dive into the exciting features of Amazon RDS for PostgreSQL, including new versions of PostgreSQL releases, new extensions, larger instances. We will also show benchmarks of new RDS instance types, and their value proposition. We will also look at how high availability and read scaling works on RDS PostgreSQL. We will also explore lessons we have learned managing a large fleet of PostgreSQL instances, including important tunables and possible gotchas around pg_upgrade.

Brendan Gregg’s USE (Utilization, Saturation, Errors) method for monitoring is quite known. There’s also Tom Wilkie’s RED (Rate, Errors, Durations) method, which is suggested to be better suited to monitor services than USE. I want to talk about how we employ these methodologies when we develop our Postgres monitoring in okmeter.io.