PGConf.Russia 2025

Although we often don't like to talk about it, database administration carries with it a large amount of stress. This is particularly true when we have to take on late night support duties. In this talk you will learn: 1. The basics of the physiology of stress. This is not a physiology lecture, but as engineers we need enough to build a mental model. 2. What kinds of mistakes we make when under stress. 3. How to measure stress in your own life and recognize it in others. 4. What tools are helpful to manage short- and long-term stressors. Managing short-term stress is important in avoiding becoming overwhelmed when problems occur, but managing longer-term stressors is just as important in avoiding problems in the first place.

Where I used to work, we had pushed ElasticSearch to its breaking point. We needed an even more scalable replacement for a write-heavy, read-seldom workload. So we built one on PostgreSQL. Now, many of us are building the successor as an open source project. 

This talk goes over the design of Bagger (named after the giant mining machines), which can manage logs into tens or hundreds of petabytes. More than just a review of the architecture, this talk focuses on the whys and the tradeoffs made in the design. 

The talk is intended both to showcase how programmable and powerful PostgreSQL is, but also illustrate the fundamental tradeoffs which must be faced when pushing any technology into the big data space.

Many developers often face performance issues in the systems they develop. One common solution for optimizing slow business processes is parallelization. But what do you do if the bottleneck is the data insertion into the database, which needs to maintain atomicity?

In this talk, I’ll explain how to speed up data insertion by parallelizing the process in Spring, while ensuring the atomicity of the entire operation. We'll cover batch updates in Spring and PostgreSQL, discuss why updates are heavy operations, and explore ways to speed up the process in the current tech stack. Additionally, I will present other approaches to maintaining atomicity and demonstrate their differences in benchmarks.

This will be useful for practicing engineers.

Sometimes, issues arise with the operation of PostgreSQL on Linux. We will define a classification of these scenarios and provide solutions, from simple to complex. Which failures lead to data corruption? Which scenarios are more dangerous than others, and what should be monitored? We will review logging examples from DBM.P Skala-R and analyze debugging scenarios, including OS libraries, Linux kernel, drivers, and kernel modules to identify causes and resolve errors.