PgConf.Russia 2020

If you care about Postgres performance, there are a number of hardware acceleration options to help with different use cases. Intel Optane DC persistent memory creates new tier in data hierarchy allowing developers to utilize performance of traditional memory combining with volume and persistency of block storage devices. Unlike traditional DRAM-only in-memory systems, where memory is small, expensive, and volatile, Intel Optane DC persistent memory makes it possible to run larger Postgres databases (terabytes) in memory for higher performance. FPGAs are integrated circuits that can be reprogrammed dynamically to accelerate a specific workload such as SQL execution and data compression. FPGA accelerators extend Postgres with hundreds of SQL reader and writer processes that work in parallel on the FPGA. It’s similar to adding hundreds new cores to boost parallel processing on your server.

In the report I will talk about how Zabbix appeared in our company, how we lived with Oracle, why we decided to switch to PostgreSQL, what problems we had during the transition, and what software seemed like a good choice for working with PostgreSQL.

The story about powering a 1.5 petabyte analytics application with 2816 cores and 18.7 TB of memory in the Citus cluster at the Microsoft. The Windows team measures the quality of new software builds by scrutinizing 20,000 diagnostic metrics based on data flowing in from 800 million Windows devices. At the same time, the team evaluates feedback from Microsoft engineers who are using pre-release versions of Windows updates. At Microsoft, the Windows diagnostic metrics are displayed on a real-time analytics dashboard called “Release Quality View” (RQV), which helps the internal “ship-room” team assess the quality of the customer experience before each new Windows update is released. Given the importance of Windows for Microsoft’s customers, the RQV analytics dashboard is a critical tool for Windows engineers, program managers, and execs.

From the very beginning, PostgreSQL in Avito has been solving very important tasks. All the main architecture components are built around DBMS. For over 10 years, the project has been actively evolving, and the infrastructure and architecture have changed a lot.

The talk will start with an overview of how PostgreSQL infrastructure and architecture have advanced in Avito over time and which challenges have been successfully resolved.

Then we'll discuss PostgreSQL usage scenarios in Avito in 2020: microservice architecture, sharding, hosting multiple databases on a single server instance, DBaaS (Database discovery, access control, failover, backup, archive, resource sharing, etc.), integration, and team evolution.
And finally, I'll share our backlog and wishlist.