The “pattern” there is to either dump and reinsert the entire DB or upgrade by having two installations (old and new version), which doesn’t exactly work well in k8s. It’s possible, but seems hacky
I can’t think of any situation other than maybe wanting to get better indexing or changing the storage engine that I would need to re-create and re-insert that way so I’m not sure if you have a constraint that necessitates that or not but now I’m curious and I am always curious to find new or better methods so why do you do it that way?
At home to upgrade Postgres I would just make a temporary copy the data directory as a backup and then just change the version of the container and if it’s needed run pg_upgrade as jobs in kubernetes.
In a work environment there is more likely to be clustering involved so the upgrade path depends on that but it’s similar but there really isn’t a need to re-create the data, the new version starts with the same PVCs using whatever rollout strategy applies. Major version upgrades can sometimes require extra steps but the engine is almost always backwards compatible at least several versions.
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It’s about PostgreSQL upgrade.
The “pattern” there is to either dump and reinsert the entire DB or upgrade by having two installations (old and new version), which doesn’t exactly work well in k8s. It’s possible, but seems hacky
I can’t think of any situation other than maybe wanting to get better indexing or changing the storage engine that I would need to re-create and re-insert that way so I’m not sure if you have a constraint that necessitates that or not but now I’m curious and I am always curious to find new or better methods so why do you do it that way?
At home to upgrade Postgres I would just make a temporary copy the data directory as a backup and then just change the version of the container and if it’s needed run pg_upgrade as jobs in kubernetes.
In a work environment there is more likely to be clustering involved so the upgrade path depends on that but it’s similar but there really isn’t a need to re-create the data, the new version starts with the same PVCs using whatever rollout strategy applies. Major version upgrades can sometimes require extra steps but the engine is almost always backwards compatible at least several versions.