Several production cases during one night

We maintain large PostgreSQL databases with the total data volume exceeding 180 TB. Every instance in the cluster gets a workload of 15 thousand requests per second. These circumstances certainly impose limitations on the classical approach to updating database structures. The cost of a DBA error gets higher, as even a small error can lead to a sleepless night) In my talk, I will cover our existing limitations for changes in the production environment, non-classical DBMS behavior under heavy workloads, and will discuss PostgreSQL in general.

Switching to domestic CPUs while working with the DBMS. We are ready, what about you?

From Oracle to Postgres using Russian rails. Non-obvious nuances

We'll discuss our approaches to picking technical solutions for the systems we design. We'll consider their advantages and limitations. We'll share the facts about the changes in our engineering culture when import substitution requirements came into effect. We migrated the system with a classical three-tier architecture from Oracle to Postgres Pro DBMS. In my presentation I'll pay attention to data migration tools and peculiarities of development Java/Kotlin apps and SQL interoperability between two DBMSs.

Implementing partitioning without downtime

The built-in partitioning mechanism in PostgreSQL has been developing for several years. However, there is no magic button that would transform an ordinary table into a partitioned one. I will explain how to implement partitioning in a production system, how to prepare your table and apps for partitioning, and what pitfalls can make a DBA's life harder. We will also take a deep dive into various techniques of transferring data between partitions, also considering their pros, cons and limitation.