PgConf.Russia 2020

Everyone has probably heard about such a service as AWS RDS. I will talk about my experience by using the AWS RDS PostgreSQL Engine: the positive and negative aspects of the DBA work. This talk will focus on the tools that helped me create a comfortable environment in RDS. https://www.dropbox.com/s/v7udx5x96as5gbd/pgconf2020.pdf

I would like to present the main projects for the evolution of our database, how we execute the administration, the problems and pitfalls we found, and how we solve them,the number and how are the database clusters from Gitlab.com , and what is our planning for the future, sharding, kubernetes... Our environment is in an exponential growth, with millions of users and thousands of requests per second, and we keep our platform stable and scaling. Join our session and discover our how we are doing it!

I like stored procedures - it is great technology. But like any other technologies it allows to write not well optimized code. It is not easy to write optimized code, sql statements in complex large applications. On second hand, there are some tools, that can be used very easily, that can help. Postgres has built-in tracking functions possibility. There are PLProfiler and plpgsql_check. With these tools is easy work to detect slow part of applications.With this knowledge, the fix of performance issue is less magic.

An enterprise-grade PostgreSQL requires many complementary technologies to the database core: high availability and automated failover, monitoring and alerting, centralized logging, connection pooling, etc. That is, a stack of components around PostgreSQL. Kubernetes has enabled a new model to deploy software abstracting away the infrastructure. However, containers are not lightweight VMs, and the packing of software paradigms that work on VMs are not valid on containers/Kubernetes. How should be PostgreSQL and its stack be deployed on Kubernetes? Enter StackGres. An open source software that is the result of re-engineering PostgreSQL to become cloud native. Join this talk to learn and see demos of how to generate PostgreSQL minimal containers; how the sidecar pattern is used (abused) to integrate PostgreSQL’s stack components, and how the networking and storage are handled. More info: stackgres.io.