gbartolini

It all depends on the storage underneath. If you have got good storage, with CNPG you have comparable results you get on bare metal PostgreSQL.

Barman Cloud was a convenient choice for CloudNativePG (CNPG) because it was developed by the same team that created Barman originally (I am part of both teams). When we started CNPG, we never anticipated it would become so popular, which has obviously resulted in some technical debt. The issue you mentioned concerns our decision not to integrate pgBackRest into CNPG's core, as we aimed to develop a pluggable interface (CNPG-I).

As a community, we have decided to support volume snapshot backups and offer the Barman Cloud plugin to ensure we provide the same level of service. Our aim is to encourage other organisations or developers to create plugins for their preferred backup solutions.

Currently, as maintainers of CNPG, we must concentrate on the core capabilities and allow the ecosystem to grow with both community and, potentially, commercial solutions based on CNPG-I.

As a founder and maintainer of CNPG, it is exciting to see it used here. I would love to know more! Thanks.

I actually do not understand the point here. And maybe you are not very familiar with the concept of transactions. Backups can only account for committed transactions.

However, we are talking about Postgres, here, not a generic database. PostgreSQL natively provides continuous backup, streaming replication, including synchronous (controlled at transaction level), cascading, and logical. You can easily implement with Postgres, even in Kubernetes with CloudNativePG, architectures with RPO=0 (yes, zero data loss) and low RTO in the same Kubernetes cluster (normally a region), and RPO <= 5 minutes with low RTO across regions. Out of the box, with CloudNativePG, through replica clusters.

We are also now launching native declarative support for Kubernetes Volume Snapshot API in CloudNativePG with the possibility to use incremental/differential backup and recovery to reduce RTO in case of very large databases recovery (like ... dozens of seconds to restore 500GB databases).

So maybe it is time to reconsider some assumptions.

The reason could be the last 4 years of evolution in Kubernetes. Have you heard of DoK Community (Data on Kubernetes)? Might be a good place where to start.

I agree with your view point and concerns.

That is why we took the approach to reduce the number of components and integrate everything in Kubernetes, especially with logging (we directly log in JSON to standard output) and the usage of application containers, which enables us to cover the case of troubleshooting via the fencing mechanism (your pods are up, you can access storage, but Postgres is down, giving you the possibility to check even possible data corruption issues).

Also, the status is directly available in Kubernetes, so in our view easier for Kubernetes administrators.

Finally, the source code is open source and directly available for inspection - if you want to understand what is happening.

Maintainer of CloudNativePG here.

Back then, we evaluated Crunchy Operator's source code. Being primarily imperative and using an external tool for failover, where the two main reasons we decided to start a new project in 2019 which was entirely declarative and purely based on the Kubernetes API server for cluster status. Such project was released open source last April under the name CloudNativePG and hopefully it will enter the CNCF Sandbox soon (fingers crossed).

Thank you!