PgConf.Russia 2020

In my talk, I will tell how we built a geographically distributed system of personal data storage based on Open Source software and PostgreSQL. The concept of the inCountry business is to provide customers with a ready-to-use infrastructure for personal data storage. Our business customers are ensured that their customer’s personal data is securely stored within their country’s borders. We wrote an API and SDK and built a variety of services. Our system complies with generally accepted security standards (SOC Type 1, Type 2, PCI DSS, etc.). We built our infrastructure with Consul, Nomad, and Vault, used PostgreSQL, ElasticSearch as a storage system, Nginx, Jenkins, Artifactory, other tools to automate management and deployment. We have assembled our development and management teams - DevOps, Security, Monitoring, and DBA. We use both cloud providers and bare-metal servers located in different regions of the world. Development of the system architecture and ensuring the stability of the infrastructure, consistent and secure operation of all its components is the main task facing our teams.

In this tutorial, we will solve several programming problems using JSON functionality that extends SQL capabilities and virtually turns a relational database into an almost ready-to-use application server. :)
We will learn how to use aggregates, both standard and custom, as well as review possible benefits of JSON recursive structure.

PostgreSQL 13 Feature Freeze is scheduled for April 2020. Two more commitfests are still accepting new patches. What we can say about PostgreSQL 13. It's possible that rotation rule will work so that new release wouldn't have as many new features as PostgreSQL 12 have. If even it is do, that would be good evolutionary release with a lot of medium feature and infrastructure changes, which prepares postgres for new leap. In this talk I will overview expected novelties in PostgreSQL 13. It would be more or less accurate, since there would be only one commitfest left, which results are possible to forecast.

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.