PgConf.Russia 2019

Managed database services are gaining in popularity. In this session we look at how best to configure Amazon RDS for PostgreSQL and also look at common user operations of using RDS for PostgreSQL. We will also look beyond common user operations and into some specific optimizations related to upgrade, logical replication, performance, and reducing downtime.

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.

1. Principles of searching for troublesome queries in PostgreSQL.
2. Evaluation of hypothetical indexes and their impact on query plans.
3. The most common errors in 1C-programming.
4. Basic methods of code refactoring, taking into account the features of PostgreSQL.
5. Storing analytical information from the PostgreSQL log to assess the quality of refactoring

Python may not be the fastest programming language on the CPU, but its fast and easy development saves a lot of costs between the keyboard and the chair. Since database clients spend most of their time waiting for a response from the database server, Python's asynchronous functionality available in the recent versions (3.5+) may help to optimize the application's runtime considerably by working on something else while server's response is being prepared. The asynchronous interface between Python and PostgreSQL is called "asyncpg". In the workshop we'll explore this library and write a short application using some of its useful features.