PGConf.Russia 2022

Previously, we have explained the internals of Avito, discussed, where and how we store your classifieds, and how they appear on the search results. In the recent 3-4 a lot has changed in Avito. We got rid of logical replication, stopped using standby servers for reads, removed nearly all stored procedures and our custom failover solution, migrated all our classifieds into a sharded DBMS, switched from the monolith app to microservices. I'll explain why we made such decisions, list some of the problems we encountered and describe the current state of our development process.

A cloud provider operates with lots of hardware resources and network entities. It's one thing when a company runs dozens of Postgres Pro instances in an isolated loop for internal tasks. And it’s quite a different story when a cloud provider renders services to B2B users and maintains solutions for 500+ large companies.

Vitaliy will tell how the VK Cloud Solutions cloud provider currently employs Managed Postgres Pro. He will also demonstrate the solution's architecture and cover the challenges faced while creating the Postgres Pro solution in our cloud.

Every DBMS stores its data on a hard disc, so you may face a situation when your data on disc gets corrupted. This can happen due to a controller failure, logical or physical data corruption; there are also other reasons. If it is just the index file that gets corrupted, the index recreation command will enable you to restore data consistency in your DBMS. If a table file or a file of a system section gets corrupted, data restore is impossible. In this case, you need to invent workarounds. You can try to restore this data from backup files, copy it from the corrupted table, or find another way to solve this problem. In this talk, we'll tackle several cases of data corruption on disc and describe the options for restoring the data from the corrupted tables.

A modern database should be capable of storing big values. Storing itself is not a big deal, however, operations with big values or fields are a non-trivial task. PostgreSQL has several options for storing big values, but none of them is perfect. How do we respond to this challenge? Our presentation answers this question, let's see how to store big and complex values in Postgres properly, and how operate with them.