Yes, I know about this tool, it's great.
I watched videos about how it was developed, what difficulties there
were in achieving delta backups, and how the developers also spent a ton of
time studying the PostgreSQL source code. And I studied the Wal-G source code myself.
I just never had to use it at work, since I was used to pgBackRest and, a
bit later, to Barman. Wal-G focuses on cloud and universality
(i.e., it's not only used for PG, but has a unified interface for many different storage systems).
Initially, I didn't even have the idea of making a complete, reliable tool.
Over time, I started striving toward exactly that.
When there was an available hypervisor at work, I set up k8s there and
ran my receiver for several dev databases, just to test its operation 24/7,
setting aggressive config parameters (frequent compression, unloading, cleanup,
frequent backups, etc.). At the same time, I was choosing not small
databases, but quite real production ones, with various nightly integrations
for data population (external APIs, Airflow, and all that), blobs/tablespaces.
And of course I read your articles, and watched a lot of videos
Yes, I know about this tool, it's great. I watched videos about how it was developed, what difficulties there were in achieving delta backups, and how the developers also spent a ton of time studying the PostgreSQL source code. And I studied the Wal-G source code myself. I just never had to use it at work, since I was used to pgBackRest and, a bit later, to Barman. Wal-G focuses on cloud and universality (i.e., it's not only used for PG, but has a unified interface for many different storage systems).
Initially, I didn't even have the idea of making a complete, reliable tool. Over time, I started striving toward exactly that. When there was an available hypervisor at work, I set up k8s there and ran my receiver for several dev databases, just to test its operation 24/7, setting aggressive config parameters (frequent compression, unloading, cleanup, frequent backups, etc.). At the same time, I was choosing not small databases, but quite real production ones, with various nightly integrations for data population (external APIs, Airflow, and all that), blobs/tablespaces.
And of course I read your articles, and watched a lot of videos