I would go further than this and argue that most bugs during database migrations happen because of mismatched application behavior with the action of the migration, not because the DDL was wrong. E.g. removing something that was still being relied on by the application, or starting to backfill data to a new column before the application is fully writing it. The most insidious version of this is where one application server doesn't have it's code updated (or comes back from the dead, etc) and causes the problem.
At a previous job what I did to prevent that was to have a special DB table that would signal what capabilities the database has, and the code would read that table and compare to its own requirements. If a capability required by the database was not present in the code (e.g. code not updated for a new feature) the code would refuse to make any writes to the DB and error all incoming requests. Likewise if a capability required by the code was missing from the database (e.g. code deployed too soon and database migration not run yet) it again would refuse requests. Before setting a feature to required in the DB and preforming the migration with feature flags, we could check all known application servers were reporting compatibility with the new feature (if any were down or not reporting at the time, they will be blocked in the next step - prioritizing safety over liveness)
I believe there are patterns that always work, but might not be optimal for all circumstances.
Eg. you could have a mirror table that you keep in sync with triggers without any constraints or foreign keys, do the migration on it, and then switch them around when ready.
I came here to say this too. Most bugs I run into are when databases schema versions interact with multiple software versions. If you are a low availability service, you can just take down the service and update the schema atomically, but 90% of the time you actually need to write backwards compatible migrations and forwards compatible code and coordinate the rollout accordingly.
My rule of thumb is no more than two distinct software versions can share a database at the same time. This effectively rules out database sharing between services. That way you push the problem to an API layer, which is better equipped to handle maintaining compatibility between many client versions.