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.

Our talk reviews the modern tools for administering PostgreSQL. It also covers the DBMS's performance bottlenecks and provides approaches to resolving the related issues. The presentation tackles the problems that occur while Oracle to Postgres migrations including the following: performance tuning tools (the analogues of AWR and ASH); monitoring tools (the analogues of Cloud Control); ensuring high availability and reliability of the database (grid infrastructure analogues); known "database performance bottlenecks"; an overview of options for technical support options SLAs.

Many books end with a wedding, but the reader has no idea about the future life of the heroes except that they lived happily ever after. In 2019, we successfully migrated distributed our railway application from Oracle 11g SE to vanilla PostgreSQL 11.9. But our story did not end with this successful migration - life went on, and sometimes we got startled because of "surprises". We encountered a number of problems, some of which were solved by reorganizing the data, some disappeared after we changed our stored procedures, and some got resolved after tuning the PostgreSQL parameters. Solving our problems would be impossible without the logging and profiling system built into our DB application. Our talk covers the examples of successful detection and resolving of the performance issues that occurred in our PostgreSQL-based application.

Mamonsu is an active monitoring agent for PostgresSQL based on Zabbix. We are actively developing the agent: there are new unique metrics and visualization capabilities. But in addition to metrics collecting mechanism, Mamonsu has other useful features. I am going to briefly describe these features also known as "Mamonsu tools", the agent's advantages and the installation process.