PGConf.Russia 2022

The volume of data stored in Postgres Pro databases is growing rapidly. In some organizations, such databases have already exceeded tens of terabytes in size. The existing approaches to backups don't ensure timely backup and restore of data in such cases. We have supplemented the well-known and well-tested Postgres Pro backup tools with functionality that will allow users to backup and restore large databases. In addition to that, we have created our solution with the convenience of DBAs in mind.

Every DBMS stores its data on a hard disc, so you may face a situation when your data on disc gets corrupted. This can happen due to a controller failure, logical or physical data corruption; there are also other reasons. If it is just the index file that gets corrupted, the index recreation command will enable you to restore data consistency in your DBMS. If a table file or a file of a system section gets corrupted, data restore is impossible. In this case, you need to invent workarounds. You can try to restore this data from backup files, copy it from the corrupted table, or find another way to solve this problem. In this talk, we'll tackle several cases of data corruption on disc and describe the options for restoring the data from the corrupted tables.

Mamonsu is an active monitoring agent for PostgresSQL based on Zabbix. We are actively developing the agent: there are new unique metrics and visualization capabilities. But in addition to metrics collecting mechanism, Mamonsu has other useful features. I am going to briefly describe these features also known as "Mamonsu tools", the agent's advantages and the installation process.

Disaster-tolerant cluster implies minimal data loss in the event of the main data center disaster and switching to the backup data center. The data loss takes place due to the asynchronous replication between the main data center and the backup one. However, there's a solution that can resolve the existing problem and ensure zero data loss in the case of the main data center disaster. My talk covers this solution for zero data loss.