PGConf.Russia 2018

Azure Database for PostgreSQL is a managed database service built for developers using the community PostgreSQL database technology you love. Learn how you can leverage the managed service and the key capabilities that the service offers which enables you as a developer to focus on developing apps. Using customer stories and experiences including live demos, we will walk through best practices and demonstrate how this service integrates with the other Azure services.

For over 15 years JetBrains have strived to make effective developer tools. IntelliJ IDEA for java is the most popular of them. IntelliJ supports databases as well, and finally we in JetBrains decided to bring this functionality and our experience in programming languages to the world of SQL. That’s how DataGrip appeared. In my talk I will tell how DataGrip helps developers by automating routine checks and corrections and speeds up developer’s production. I will also show how to extend IDE’s functionality and try to understand which actual problems we can solve in future.

Liquibase is a very convenient tool for sequential database migration, used both on our projects and in a large number of other projects and frameworks. It allows you to keep the code of the database together with the application code in VSC, track the attempts of repeated migrations and much, much more. But sooner or later the project grows, the data occupy terabytes, and liquibase still rolls the migration sequentially.

We could not afford to deploy migrations for 100 hours and came up with a framework for liquibase that expanded its capabilities and allowed to execute a whole series of scripts in parallel or to split one large migration into small partitions and migrate them in parallel.

I would like to share experience in runing PostgreSQL in dockerized environments, describe the specific issues and tools you will need to solve them.

• Which problems could be solved by Docker for PostgreSQL, e.g. PostgreSQLPro.9.6
• Work of IT team with Docker in development, testing and production environments
  • Using image repository and build servers for image testing
• Issues in production environment:
  • With network activity
  • With persistent repositories for Docker
  • With additional services
  • With load balancing and fail-safety
• Running PostgreSQL-base applications, such as:
  • SonarQube
  • Gitlab
  • 1С platform