Postgres Performance for Application Developers
Principal Engineer on the Citus Cloud team at Citus Data, developing and operating a distributed PostgreSQL-as-a-Service.
Creator of pganalyze.com, hosted PostgreSQL Performance Monitoring, author of pg_query (Ruby extension to parse queries using the raw_parser) and other tools. I love working with PostgreSQL statistics and visualizing them.
No video of the event yet, sorry!
To many developers the database is a black box. You expect to be able to put data into your database, have it to stay there, and get it out when you query it... hopefully in a performant manner. When its not performant enough the two options are usually add some indexes or throw some hardware at it.
We'll walk through a bit of a clearer guide of how you can understand how your database is doing from a 30,000 foot perspective as well as how your application needs to be changed over time to keep your database performant.
In particular we'll cover:
- Postgres Caching & Indexing
- How to read EXPLAIN Plans
- Optimizing applications built on Django and Rails
- Scaling to 10GB -> 100GB -> 1TB
- 50 min
- PGConf US 2017 [PgConf.US]